Microarray Gene Expression Data Analysis: A Beginner's Guide

Book Description

Microarray technology is arguably the most important recent breakthrough in molecular biology. It enables researchers to obtain snapshots of gene expression for all the genes in a genome in a single experiment. Microarray experiments generate massive amounts of data that can be analysed to extract new knowledge about the underlying biological processes.This guide covers aspects of designing microarray experiments and analysing the data generated, and includes information on some of the tools that are available from non-commercial sources. Concepts and principles underpinning gene expression analysis are emphasised, and wherever possible the mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression.

Customer Reviews:

A good introduction to the topic .......2007-05-20

Microarrays are a tool for monitoring gene expression levels for thousands of genes in parallel. This technology is very useful since patterns in the gene expression can be used for molecular characterization of phenomena that range from disease states and response to stimuli to the differences between cells of different types. The amount of information obtained from one microarray experiment can be large. These large amounts of information present new challenges in the areas of data storage, management, and analysis by biologists who are not accustomed to dealing with this much data. Also, the software used for data analysis is usually written by mathematicians and statisticians that have a minimum of training in biology.

This book addresses some of the issues faced by researchers who are beginning their first microarray experiments. It covers various aspects of designing and analyzing the results of microarray experiments. Microarrays are not limited to the study of gene expression, but this remains the most common use of the technology and therefore is the only use of arrays discussed here. This book attempts to explain the underlying concepts and principles routinely used in analysis of gene expression data. The book should be accessible by statisticians, computer scientists, and students of bioinformatics who want a grounding in the types of analysis currently used to study microarray data.

The book begins with an introductory chapter which is followed by three major chapters. As with any technology that has the capacity to detect small changes in a highly dynamic system, the underlying experimental design and the manner in which an experiment is conducted is critical for obtaining high quality data. Chapter two addresses these issues. The raw data from microarray experiments are images that must be transformed and organized into gene expression matrices. These transformations are the subject of chapter 3. Finally, in chapter 4, the common methods used for analyzing gene expression data matrices with the goal of obtaining new insights into biology are discussed. The book does a pretty good job of providing the reader with a general understanding of the nature of microarray data and how it can be analyzed. It was never meant to be a reference book or a comprehensive review, just a gentle introduction.

Well written, short explanations but nevertheless understandable.......2005-07-06

Certainly, this book can not give a complete description of microarrays, neither from an experimental nor a theoretical side. Nevertheless, the issues presented and discussed provide the reader with a solid basis for more advanced studies.

In my opinion, this book is well written, the explanations given are descriptive and understandable and its overall organization is plausible. I recommend this book as an introduction for the analysis of microarray data, because it provides a good overview of existing methods in this field. A warning: This does not mean, that all these methods are thorougly expained! It just provides an overview!! If you want to learn, e.g., clustering methods, you should consult another book (probably no other book about microarrays but a decent book dealing only with data analysis in general or clustering methods...)

Bioinformatics: Sequence and Genome Analysis

Average customer rating:

One of the worst text-books I have ever read
more challenging than trying to unravel the human genome.
Leaves something to be desired
Bioinformatics: Sequence and Genome Analysis by David W. Mount [Paperback]
A good book despite criticism

Bioinformatics: Sequence and Genome Analysis
David W. Mount
Manufacturer: Cold Spring Harbor Laboratory Press
ProductGroup: Book
Binding: Paperback

Bioinformatics | Biological Sciences | Science | Subjects | Books

Genetics | Evolution | Science | Subjects | Books

General | Science | Subjects | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids
An Introduction to Bioinformatics Algorithims (COMPUTATIONAL MOLECULAR BIOLOGY)
Beginning Perl for Bioinformatics
Bioinformatics for Dummies (For Dummies Series)
Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins

ASIN: 0879697121

Book Description

As more species' genomes are sequenced, computational analysis of these data has become increasingly important. The second, entirely updated edition of this widely praised textbook provides a comprehensive and critical examination of the computational methods needed for analyzing DNA, RNA, and protein data, as well as genomes. The book has been rewritten to make it more accessible to a wider audience, including advanced undergraduate and graduate students. New features include chapter guides and explanatory information panels and glossary terms. New chapters in this second edition cover statistical analysis of sequence alignments, computer programming for bioinformatics, and data management and mining. Practically oriented problems at the ends of chapters enhance the value of the book as a teaching resource. The book also serves as an essential reference for professionals in molecular biology, pharmaceutical, and genome laboratories.

Customer Reviews:

One of the worst text-books I have ever read.......2007-07-05

I used this book in an introduction level class to bioinformatics and it was worse then useless. The book is much more a survey of literature then anything else and so if you are not already very familiar with the topics the book does not provide enough details for you to get very far at all. Although to be fair most of the books on bioinformatics out at the time and the two years after were not much better, but I felt this was near the bottom of the pile. "Fundamental Concepts of Bioinformatics", ISBN: 0-8053-4633-3 when it came out was miles better, although even that book had tons of warts. If you are looking for a reference then this book is okay, but by the time I am writing this review you assuredly can find a more modern book.

Part of the problem with books on bioinformatics is that, every book makes very different assumptions on your base level of knowledge of the various critical subjects needed: biology, chemistry, computer science and math. Most strike a pretty poor balance on the assumptions made and vary from way too basic to useless to anyone who is not already familiar with the field. My suggestion is to check out any book you are considering because how good the book is will vary greatly on your background.

more challenging than trying to unravel the human genome........2006-06-08

I used this book to teach a bioinformatics course in a foreign language because it was only one of two available in both english and chinese. I'm not sure it wouldn't have been less confusing to simply use a english textbook and let the students translate the text for themselves. To give the author credit, he has compiled an enormous quantity of information and made it available in a single location and that is no mean feat. At the very least, it is a valuable starting point to find both useful references to better explanations and software appropriate to almost any analysis you might want to do. On the downside, the prose is a tangled mess and is beyond comprehension in places. there are points where, even though i understand the underlying theories used throughout the book, i still couldn't figure out some of the examples used to illustrate particular methods. For example, there are some figures which have captions which run for a page and a half. Finally, in the majority of cases, the figures are taken directly from key papers on each topic, and associated explanations consist of sentences copied verbatim from the text. I may be doing the author a gross injustice here, but in many of the explanations, i was left with the same impression i get when reading students papers when they have copied something out of a textbook, without really understanding what is going on. Having said all of the above, i would still recommend taking a look at this book, but be ready to access the excellent list of references if you want a more insightful understanding of many of the methods described throughout.

Leaves something to be desired.......2006-01-28

I took Dr. Mount's class at the U. or Arizona, and he's a really smart guy, but the man can't explain anything. It's not just his book either; his lectures are just as cryptic. I went to class thinking I understood the concepts, but then I got totally confused when he lectured. I would try to clarify things with the book, and again, I'd get even more confused. Someone who reviewed this book earlier said that he tends to use 10 words where he should use 1; I couldn't agree more. The figures in this book also need a major overhaul, and he should definitely include more examples of the many complex concepts he talks about. While I have no doubt that there is plenty of useful information in there, getting anything out of it is a chore. I would only recommend this book to someone who already had a strong knowledge of bioinformatics concepts.

Bioinformatics: Sequence and Genome Analysis by David W. Mount [Paperback].......2005-09-24

Book is a good reference textbook for Bioinformatics. Of course the material covered is technical and dense, but that is unavoidable for the subject matter that the book covers.

A good book despite criticism.......2005-09-01

I don't understand such a lot of bad comments about this book. In this book concepts are presented in an intelligent way, because the book is as quantitative as the biologist's requirements are. Everithing is sufficient to comprehend which are the things' mathematical basis but avoiding time-comsuming and ready-to-forget extra info. Other books are only for matematicians because they are sometimes full of numbers and complicated equations, while other ones are so simple that I imagine them usefull only for non-biologists (matematicians again above all).
This is a book that is usefull as an introduction for the initial graduate level bioinformatician (biologist) and as a short description of the techniques that we use to matematicians aimed to collaborate.

Finally I am not in agreement with some coments about what is Bioinformatics. Most of them carried out by some non-biologists here. Bioinformatics is Biology. Of course we use mathematics, but as far as we USE them, bioinformatics is not mathematics. We do not develope Mathematics, but Biology state of the art. Bioinspired algorithms, in the other hand, are pure mathematical concepts, even if they are insipred in biology. Let Bioinformatics be what it is, a quantitative and statistical part of pure Biology.

This is a good book if you are not an expert in Bioinformatics but you have in mind to be one. Study this book entirely as your first one and go directly to the difficult ones. For me, it is the shorter reading path to bioinformatics expertise nowadays.

History: Fiction or Science? (Chronology, No. 1)

Average customer rating:

Calculations are only as good as your numbers
Pants on fire?
Accepted History & Chronology Must Be Changed.
Very Interesting
History as Science Fiction

History: Fiction or Science? (Chronology, No. 1)
Anatoly Fomenko
Manufacturer: Mithec
ProductGroup: Book
Binding: Paperback

Chinese | Ethnic & National | Biographies & Memoirs | Subjects | Books

Irish | Ethnic & National | Biographies & Memoirs | Subjects | Books

Japanese | Ethnic & National | Biographies & Memoirs | Subjects | Books

Women | Specific Groups | Biographies & Memoirs | Subjects | Books

Doctors & Medicine | Humor | Entertainment | Subjects | Books

Lawyers & Criminals | Humor | Entertainment | Subjects | Books

Love, Sex & Marriage | Humor | Entertainment | Subjects | Books

Assyria, Babylonia & Sumer | Ancient | History | Subjects | Books

Early Civilization | Ancient | History | Subjects | Books

General | Ancient | History | Subjects | Books

Historiography | Historical Study | History | Subjects | Books

General | World | History | Subjects | Books

French | Erotica | Literature & Fiction | Subjects | Books

Victorian | Erotica | Literature & Fiction | Subjects | Books

Epic | Poetry | Literature & Fiction | Subjects | Books

German | Poetry | Literature & Fiction | Subjects | Books

Russian | Poetry | Literature & Fiction | Subjects | Books

Spanish | Poetry | Literature & Fiction | Subjects | Books

Chinese | Classics | Literature & Fiction | Subjects | Books

Conspiracy Theories | Current Events | Nonfiction | Subjects | Books

War on Drugs | Crime & Criminals | Nonfiction | Subjects | Books

English (All) | Dictionaries & Thesauruses | Reference | Subjects | Books

Science | Dictionaries & Thesauruses | Reference | Subjects | Books

Online Research | Genealogy | Reference | Subjects | Books

Native American | Earth-Based Religions | Religion & Spirituality | Subjects | Books

General | Science | Subjects | Books

General | History & Philosophy | Science | Subjects | Books

History of Science | History & Philosophy | Science | Subjects | Books

Magic & Wizards | Fantasy | Science Fiction & Fantasy | Subjects | Books

Sailor Moon | Popular Characters | Children's Books | Subjects | Books

Pilates | Exercise & Fitness | Health, Mind & Body | Subjects | Books

History | Fashion | Arts & Photography | Subjects | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

History: Fiction or Science? Chronology 2 (Chronology)
History: Fiction or Science? Astronomical methods as applied to chronology. Ptolemy's Almagest. Chronology III
Discovering the Mysteries of Ancient America: Lost History And Legends, Unearthed And Explored
Before the Pharaohs: Egypt's Mysterious Prehistory
They Cast No Shadows: A Collection of Essays on the Illuminati, Revisionist History, and Suppressed Technologies

ASIN: 2913621058

Book Description

Recorded history is a finely-woven magic fabric of intricate lies about events predating the sixteenth century. There is not a single piece of evidence that can be reliably and independently traced back earlier than the eleventh century. This book details events that are substantiated by hard facts and logic, and validated by new astronomical research and statistical analysis of ancient sources.

Customer Reviews:

Calculations are only as good as your numbers.......2007-08-03

Yes, we can all agree that mainstream history is nearly 100% BS due to politics, economics, ego, problems with dating techniques, and various conspiracies. Agreed. But, I've been researching the distinct possibility that human history (in terms of civilizations) are much more ancient than we've been told, so coming across this book was very interesting to me. I wondered how Fomenko could be wrong (if at all) because he is very persuasive in his presentations. Then it dawned on me. If at previous times in prehistory, due to the various catastrophies that are well documented (comets, asteroids, planetary disruptions, plasma discharge, pole reversals, etc) the Earth was in a different position in relation to the sun, different tilt on its axis, different orbit, different rotation (in terms of velocity and DIRECTION), and the continents were in different positions, then would this not cause the ancients to see the sky (constellations) differently? In other words, is Fomenko making erronious assumptions about the physics of the Earth in pre-history, which then corrupt his data with regards to dating the relevant astrology? The last event to seriously disrupt our planet occured roughly 3500 years ago, according to other good researchers, so is it possible Fomenko has been confused by this? The vastly different physics of our planet in the not so distant past may explain this confusion, which is not to say the "mainstream" version of history is correct; on the contrary. I am not an expert in these fields, but wanted to see if this idea could spark discussion.

Pants on fire?.......2007-07-19

Will people ever read before spamming? Yes, Jesuits could not rewrite world history alone, they had help. Anyway, Dr Prof Acad A.Fomenko does not point to jesuits as the driving force of world wide history manipulation in published volumes 1,2,3;, actually he barely mentions the poor devils. Check it with 'Search inside' feature, please. China is rarely mentioned either, in fact, Dr Fomenko is completely eurocentric. Right, his theory contradicts all mainstream schools of history, because in their actual state they are all built on blatantly erroneus chronology. You don't need a mysterious cabal (conspiracy) to falsify history, the falsification is its modus operandi. It is inherent to history(ians) to falsify (distort) events, as it is inherent to humans to boast as it is inherent to power (authority) to legimize itself by referrring to glorious past made to its own order. Dr Prof Fomenko and team have identified scores of instances of such manipulation in Russian, European, etc.. history, and delivered valid statistical proof thereof. His own 'reconstruction' is completely another story. Forget c14 as a valid method of dating. W.Libby has initially discovered a brilliant method of INDEPENDENT dating. Too bad, c14 method has become a joke after a forced marrige with dendrochronology with consensual chronological scale inbuilt. Radiocarbon method can't stand blind tests, but is so very productive as a rubberstamp.

Accepted History & Chronology Must Be Changed. .......2007-04-09

There is no doubt that history as most know it is a sham, & institution's version of History both University & Church is fradulent & inaccurate. Everything was established with an agenda, The real "Dark Ages" are now when we have access to incredible amounts of information past authorities & more important 'common folk' didn't have but our institutions & educators are slow to evolve because of what has ignorantly & arrogantly been taught for too long. This is on many subjects not just Chronology.

For anyone to question "Why would a Mathematician have anything credible to say of History?" The answer is from Dr. Fomenko's preface in the book: "It would be worthwhile to remind the reader that in the XVI-XVII century Chronology was considered to be a subdivision of Mathematics." These volumes could possibly be some of the most important works to date & should be read by everyone with an interest in History, especially professors & educators who have a duty to the public. I have read both books & must say that 'Chronology 1' has some very eye opening & revolutionary information. Even if these volumes are part true the implications are profound & opens the doors to further investigations & questions which must be done. I speak several different lanquages & must say the logic Dr. Fomenko uses with "inflection" of words & words being read from left to right in one region & right to left in another then written backwards, the removal of vowels & get down to basics of words, or different cities & locations having the same name etc. is correct. Vowel usage has always been optional & varied, actually complicating linquistics & study. The first thing one has to understand is that words never had a fixed spelling in history like we do now, the spelling of words was mutable & regional, as well as names & titles of people were vast, varied & changed, NOTHING WAS FIXED or understood linear. Matters of Life & Death as well as financial profiteering yesterday & today were & are made with ignorant, illogical & conspiratorial views of history & reality, it's time people get closer to the Truth & society collectively grow up.

Very Interesting.......2007-03-07

It is a good proposal and I believe it will mature into something even better in the future. I think it deserves to be read.

History as Science Fiction.......2007-01-10

Anatoly Fomenko has written a very intriguing book, full of pictures, charts, and computer 'proof' of his thesis: backwards of AD900 we don't really know what happened or when. Between AD900 and AD1600 there is more certainty, but there is still a lot of fuzzy ground, and things don't get reliable until we get past the 1600's where the printing press made it very difficult for the perpetrators of this timeline manipulation to change anything that had been committed to print. The Dark Ages did not happen. Books were burned for a reason. One organization has doubled the actual length of its existence by expanding the real chronology. Read why.

I had always wondered why Christ died about AD33 and yet men waited until the 11th century to form the Knights Templar, the Cathars, etc and go after the Holy Land by force. Why the 1000 year gap? Turns out there wasn't more than a 10-12 year gap and he proves it using astronomy. This also implies that the planet is not as old as we have been told, and current Christian and other creationist scientists are already championing that idea without being aware of Fomenko's book. The two groups, creationist scientists and the Russian mathematical analysts corroborate each other. Fascinating.

Of course, all this flies in the face of what we have been told traditionally is the 'proper' chronology of western civilization, and most readers will experience 'cognitive dissonance' in reading this book. It means that our history going backwards from AD1600 becomes progressively more incorrect and unreliable until it cannot be trusted at all... in the space of 700-800 years.

Naturally, the curious, open-minded reader will want to know WHO did this, WHY, and did any of the events we think of as really ancient ever happen?
Dr. Fomenko is a respected scientist/mathematician at Moscow State University who has already answered these questions to the satisfaction of his initially skeptical colleagues. Most of them are now believers, a few still refuse to believe (the usual diehards), and of course the western press has ignored Fomenko's work -- for obvious reasons when you read the book. The ones who perpetrated this chronology ruse have a lot to answer for. They are still with us. That's why this book is a well-kept secret.

I gave the book a 4-star rating because I was unable to check out some of his claims; those I checked were as he said. But if even 1/3 of his claims are true, this punches a big hole in what we think is our history, the meaning of western civilization, our educational process (for repeating the ruse as gospel), and the trustworthiness of the organization that perpetrated this ruse, well-intentioned or not.

This book relates to current research into a Young Earth paradigm, to John Keel's discoveries about our planet, and Fr Malachi Martin's insights (in his now out-of-print books). We are indeed sheep who are manipulated and kept ignorant -- for a reason. While knowing what these men have to say may be the "booby prize" (as in: 'what can you do with this knowledge?'), it will provide interesting reading. Didn't someone say: "...and the Truth will set you free."?? For you to judge if this book contains the truth.

Average customer rating:

Get a solid foundation for microarray data analysis.
a great book to read about microarray data analysis
Simple Great
Excellent book. Highly recommended!
Introduction to Statistical Data Analysis of Microarrays

Data Analysis Tools for DNA Microarrays
Sorin Draghici
Manufacturer: CRC Press
ProductGroup: Book
Binding: Hardcover

Biochemistry | Biological Sciences | Science | Subjects | Books

Biotechnology | Biological Sciences | Science | Subjects | Books

Genetics | Evolution | Science | Subjects | Books

General | Science | Subjects | Books

General | Mathematics | Science | Subjects | Books

General | Databases | Computers & Internet | Subjects | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Computers & Internet | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

Microarray Bioinformatics
Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health)
Microarray Gene Expression Data Analysis: A Beginner's Guide
Statistics for Microarrays: Design Analysis and Inference
Design and Analysis of DNA Microarray Investigations

ASIN: 1584883154

Book Description

Technology today allows the collection of biological information at an unprecedented level of detail and in increasingly vast quantities. To reap real knowledge from the mountains of data produced, however, requires interdisciplinary skills-a background not only in biology but also in computer science and the tools and techniques of data analysis. To help meet the challenges of DNA research, Data Analysis Tools for DNA Microarrays builds the foundation in the statistics and data analysis tools needed by biologists and provides the overview of microarrays needed by computer scientists. It first presents the basics of microarray technology and more importantly, the specific problems the technology poses from the data analysis perspective. It then introduces the fundamentals of statistics and the details of the techniques most commonly used to analyze microarray data. The final chapter focuses on commercial applications with sections exploring various software packages from BioDiscovery, Insightful, SAS, and Spotfire. The book is richly illustrated with more than 230 figures in full color and comes with a CD-ROM containing full-feature trial versions of software for image analysis (ImaGene, BioDiscovery Inc.) and data analysis (GeneSight, BioDiscovery Inc. and S-Plus Array Analyzer, Insightful Inc.). Written in simple language and illustrated in full color, Data Analysis Tools for DNA Microarrays lowers the communication barrier between life scientists and analytical scientists. It prepares those charged with analyzing microarray data to make informed choices about the techniques to use in a given situation and contribute to further advances in the field.

Customer Reviews:

Get a solid foundation for microarray data analysis........2007-02-18

I'm more than 2/3 through the book and I've never encountered a topic that I feel could have been better presented. My definition of a Great book is that I can understand and follow it, and this definitely is a Great book! Thanks to the author for writing such readable text. This text has not made it to my bookshelf at work, it stays on my desk.

a great book to read about microarray data analysis.......2006-08-07

I have entered the area of microarray data analysis three years ago, having an engineering/machine learning background which includes good knowledge of statistics. After reading many journal papers about particular algorithms for microarray data analysis, I felt the need to read a book so that I could get the big picture of the field. At the beginning I was skeptical about reading Draghici's book because it was recommended to me as "excellent" by a biologist. I was pretty sure that given my background I will get bored of it quickly. My intuition failed me in this case because after reading it, I found it too as being far from ordinary, and answering my needs as well.

The book is an easy-to-follow introduction to the area of microarray data analysis covering areas from image analysis and preprocessing, to differential expression, clustering, and high level analysis such as ontological analysis. The book is particularly useful in underlying common pitfalls with microarray data. Examples include failing to correct for multiple testing in microarray experiments and the misuse or overuse of the clustering algorithms. Abounding examples and clear illustration are given to support every single aspect treated in the text. In my opinion, graduate level students in biology, bioinformatics and statistics can greatly benefit from the lecture of this book.

Another positive aspect is the fact that, with the exception of one chapter about the available commercial software, this book was written by just one author. This gives a continuity of ideas and a consistency of notations and terms throughout the entire book. This is usually not found in many other books on this topic as they are sometimes just edited collections of chapters written independently by different authors (see for instance the text by Berrar et. al which has about 40 contributors).

A great incentive for me in writing this review was reading an overzealous critique to this book, written by Eric Wu in this webpage. I found some of his comments to be particularly misleading and out of context. For instance he says "the book only deals with the bare minimum of data analysis". Compared with other books in the field, the topics about data analysis covered in the book are not only more numerous but much more thoroughly explained. This book does not expedite the reader to some references but cares about explaining the things. If this book is the "bare minimum" at 500 pages, how is Mr. Wu going to characterize the other well known books in the field such as Knudsen, Simon, Speed, Baldi, etc. which have at most half as many as this book has. Knudsen, for instance, takes the reader from absolute measurements to and including ANOVA in 17 pages. Draghici covers the same topics in 7 chapters or about 250 pages, and that would be without counting the chapters on the basic statistics or image analysis. Another example of biased assessment is when Mr. Wu says "Exploratory data visualizing and data mining algorithms are not covered thoroughly in this book. For example, principal component analysis (PCA) is presented as a subsection of a chapter." The PCA description in the book is more than just fine to me. The book is not supposed to be an encyclopedia of statistics. What the reader needs to know is how PCA can help with the visualization of these multidimensional data sets and not necessarily give all the details about PCA.
A last example I give of superficial judgment in Mr. Wu's view is the so called "inflation of Type I error rate". Mr. Wu says: "... if the probability of making a correct conclusion excludes the probability of making Type II errors, 1 - p should be stated as the probability of not making Type I errors".. In general, this statement would be true. However, the paragraph from the book to which Mr. Wu is referring to actually starts by saying: "When the t statistic for a gene is more extreme than the threshold..." etc. If the observed statistic is more extreme than the threshold, the statistical reasoning requires us to reject the null hypothesis. In this case type II errors (false negatives) CANNOT occur. Hence, in this case, the probability of drawing the correct conclusion is indeed 1-p, exactly as stated in the book.

Overall, I find that the value you get per dollar spent when buying this book is high, and thereby I would strongly recommend it.

Dr. Adi L. Tarca, Windsor (CANADA)

Simple Great.......2006-05-16

This book is a must to understand fundamental statistical analysis of microarray data. Must have it.

Excellent book. Highly recommended!.......2006-04-04

Being a book worm, as soon as I started working with microarrays I bought a bunch of books on the subject. After six months working with this technique and reading chapters on all the books I've bought I can say with certainty that Draghici's is the best introductory book on microarrays. Other books around are better at describing protocols or explaining the math involved in microarray data analysis but Draghici's book does a very good job at explaining how to analyse microarray data for the biologist (and maybe for other publics but statisticians). Everytime some friend ask me for hints on chapters or books to read for learning (or re-learning) statistics I suggest this book. The first chapters are an excellent review of the basics of statistics necessary for day to day practice. The only complain I have is that the shareware software that comes with the book does not work anymore (it's trial period has already expired and therefore it is not possible to install it even if you get a brand new book). I read this book from cover to cover and I think that, considering how readable it is, anyone could do it.

Introduction to Statistical Data Analysis of Microarrays.......2004-09-28

The targeted audience of this book is biologists who are eager to get an understanding of the analysis tools they use for microarrays. The book does an excellent job addressing this tier of audience.

The book has plenty of examples. Almost all the examples, whether fake or real, are microarray-related. Whenever needed, figures or charts are provided to illustrate ideas. A few chapters that introduce basic statistical concepts provide solved problems and exercises. All these efforts are worthwhile making difficult statistical concepts easy to understand in the context of microarrays and making the book especially valuable for biologists who do not have strong background in statistics.

This book has an emphasis on major statistical aspects of microarray data analysis. There are 17 chapters in this book. About 8 of them are directly related to statistics. Especially, there is one whole chapter devoted to multiple hypothesis testing, one chapter for ANOVA, and one chapter for experimental design. The above subjects are presented in a thorough, yet easy-to-follow style. Statistical issues are often not well addressed in published papers using microarrays. This book on microarray data analysis does an excellent job emphasizing this aspect.

The title of the book indicates "data analysis". However, since this is not a clearly defined term, you should be aware that the book only deals with "the bare minimum" of data analysis. That is routines, such as normalization, transformation, statistical testing, and clustering, that have to be carried out each and every time. Exploratory data visualizing and data mining algorithms are not covered thoroughly in this book. For example, principal component analysis (PCA) is presented as a subsection of a chapter. It does not provide explanations on concepts such as loading factors nor scree test. Series data (e.g. time series) are on two pages only and there is no mention of Fourier transformation. Support vector machine (SVM), which is widely used today as a supervised classification method, is not presented at all.

As I mentioned at the beginning, the targeted audience is biologists. If you are a statistician or a bioinformatician who wants to mathematically explore data analysis algorithms, you should look somewhere else. You may be disappointed that many concepts are not rigorously or accurately defined in this book. For example, the book uses capital letters to denote random variables. But the concept of random variables is not rigorously defined in the book. One of the consequences is the weak definition of mathematical expectation. Another example is the inflation of Type I error rate. On page 220, the author claims that the probability of "drawing the correct conclusion" is 1 - p, where p is the calculated probability of a statistic versus a parameter. However, if the probability of making a correct conclusion excludes the probability of making Type II errors, 1 - p should be stated as the probability of not making Type I errors.

In summary, this is a good book on microarray analysis tools for biologists using microarrays. However, people who are seeking in-depth descriptions of these algorithms should look somewhere else.

Average customer rating:

Very nice book
Very Practical & Useful Users Guide
Blast User's Bible
useful for comparative sequence alignment tasks
How does sequence alignment actually work?

Blast
Ian Korf , Mark Yandell , and Joseph Bedell
Manufacturer: O'Reilly Media, Inc.
ProductGroup: Book
Binding: Paperback

Biotechnology | Biological Sciences | Science | Subjects | Books

Bioinformatics | Biological Sciences | Science | Subjects | Books

Genetics | Evolution | Science | Subjects | Books

General | Computers & Internet | Subjects | Books

General | Databases | Computers & Internet | Subjects | Books

General | Software | Computers & Internet | Subjects | Books

General | Programming | O'Reilly | By Publisher | Books
Similar Items:

Mastering Perl for Bioinformatics
Beginning Perl for Bioinformatics
Sequence Analysis in a Nutshell
Developing Bioinformatics Computer Skills
Bioinformatics for Dummies (For Dummies Series)

ASIN: 0596002998

Book Description

Sequence similarity is a powerful tool for discovering biological function. Just as the ancient Greeks used comparative anatomy to understand the human body and linguists used the Rosetta stone to decipher Egyptian hieroglyphs, today we can use comparative sequence analysis to understand genomes. BLAST (Basic Local Alignment Search Tool), is a sophisticated software package for rapid searching of nucleotide and protein databases. It is one of the most important software packages used in sequence analysis and bioinformatics. Most users of BLAST, however, seldom move beyond the program's default parameters, and never take advantage of its full power. BLAST is the only book completely devoted to this popular suite of tools. It offers biologists, computational biology students, and bioinformatics professionals a clear understanding of BLAST as well as the science it supports. This book shows you how to move beyond the default parameters, get specific answers using BLAST, and how to interpret your results. The book also contains tutorial and reference sections covering NCBI-BLAST and WU-BLAST, background material to help you understand the statistics behind BLAST, Perl scripts to help you prepare your data and analyze your results, and a wealth of tips and tricks for configuring BLAST to meet your own research needs. Some of the topics covered include:

BLAST basics and the NCBI web interface
How to select appropriate search parameters
BLAST programs: BLASTN, BLASTP, BLASTX, TBLASTN, TBLASTX, PHI-BLAST, and PSI BLAST
Detailed BLAST references, including NCBI-BLAST and WU-BLAST
Understanding biological sequences
Sequence similarity, homology, scoring matrices, scores, and evolution
Sequence Alignment
Calculating BLAST statistics
Industrial-strength BLAST, including developing applications with Perl and BLAST

BLAST is the only comprehensive reference with detailed, accurate information on optimizing BLAST searches for high-throughput sequence analysis. This is a book that any biologist should own.

Customer Reviews:

Very nice book.......2006-11-08

This is a very good book. It goes into the gory details of all the BLAST features. There is a very nice introduction (Part II of the book) that explores the theoretical background that is at the foundation of BLAST before diving into the practical use of this powerful tool. Moreover, you can find some useful tips on how to handle the setup and administration of locally installed BLAST databases. It's worth having it on your bookshelf.

Very Practical & Useful Users Guide.......2006-07-12

From a users-perspective this book serves its purpose well - it explains what it is that BLAST is doing "under-the-hood" so that one may better customize Blast's search behavior. All I know is that I really learned a lot of basic fundamental core concepts here that I previously just took for granted.

The book discusses the biology, statistics, algorithms, and computer science issues involved in explaining blast. I liked this approach because it does not head super far into any one core area but rather sticks to a strong fundamental overview of each topic. The other strong aspect of this book is that the author thoroughly compares NCBI and WU Blast throughout, characterizing instances where one may choose one over the other and/or how to tweak the parameters for both in those situations.

I orginally bought the book b/c I wanted an overview on PAM and BLOSUM matrices and to understand how Blast Statistics work. It really served as an informative contextual tutorial that has definitely raised my overall understanding on not only Blast, but to better grasp the very interdisciplinary nature concerning sequence alignment for in-silico biological research.

Blast User's Bible.......2006-01-29

This is the place to start for anyone using NCBI BLAST. It's a thorough description of the various BLAST programs for nucleotides, amino acids, and codons.

The book offers a biology refresher early on, but this is aimed mainly at people with serious interest in BLAST - people who normally won't need that. Next, it discusses traditional dynamic programming alsorithms for local and global alignment. Then, in just a few pages, it summarizes the mathematical meanings and derivations of the various BLAST scores (raw scores, P-values, ane E-values). The discussion just skims the theory, but will help the reader make sense of the programs' output.

Those 75 pages set the background; the next 250 contain the real meat of the book. They cover the various BLAST programs, options, and outputs. More than that, these sections discuss setting up experiments based on BLAST, and how to deal with the problems you're likely to encounter. This could be a bit more explicit about how PSI_BLAST works (and why it sometimes doesn't), but coverage is generally strong.

A few things are weak, like emphasis on the fact that experiments aren't strictly repeatable. For example, if you exactly replicate today's test next week, even if all of the other output is identical, you might still get different (and worse) E values, since they depend on the size of the database. PSSMs get little if any discussion. Also, details about internals are weak - but this is a user's book, not an implementor's, so that's a matter of scope rather than suffiency.

Most of the book's points are illustrated with actual output or with Perl code - the lingua franca of bioinformatics, for some reason. If you're serious about using BLAST and about understanding what it's really telling you, this is the book to own.

//wiredweird

useful for comparative sequence alignment tasks.......2004-01-20

BLAST is a well-known tool for bioinformatics (biological sciences+computer sciences). In this book contains a concepts of central dogma of molecular biology, sequence aligment, sequece similarity, practical BLAST programs (divide into 5 programs), and how to install and use BLAST tool. Moreover, it also offers enough tips to improve my BLAST searches usage. I think this book's content is well-writing and well-organizing for comparative sequeces alignment tasks. I use this book to begin in bioinformatics and it can help me to learn about this. But this book does not contain all of things that I want to known on bioinformatics or computational biology.

How does sequence alignment actually work?.......2003-11-24

If you want to understand the nuts and bolts of how sequence alignment works, then this is the book for you. It will be especially useful for BLAST users who want to understand how it actually works and also for developers who don't know much biology, struggle with the math, but have no problem reading a perl script.

The book is basically divided into:
0. A Foreword by Stephen Altschul (the co-creator of BLAST)
1. A quick web intro to a BLAST search
2. Sequence alignment and how the algorithms work
3. Blast and how the Blast statistics are calculated
4. The different types of Blast e.g. WU-Blast
5. Approaches to Performance speedup
6. Reference sections on BLAST parameters

The real key is that this book neatly splits the difference between academic texts and papers which are quite often too difficult to read without sufficient background (and they are not precise about the implementation anyway) and the user-manual type texts which don't discuss the theory at all.

One of the best chapters (in my view) is chapter three, where they explain and illustrate the workings of the Needleman-Wunsch and Smith-Waterman algorithms for global and local alignment. If you read the text, then study and run the included perl code, you WILL understand how they work, but be prepared to spend several hours trying different examples. The real advantage of this approach is that you get a deep, practical understanding of how alignment actually works, that you just can't get from reading a mathematical treatment of the subject. Once you understand this chapter, you are actually sufficiently expert to get inside alignment code and modify it for your own purposes.

Ian Korf does continually emphasize that the algorithms may look clever, but they are, in the end, robotic in that they will quite happily align complete rubbish if you are not careful about controlling the algorithm and thinking carefully about the results you get.

There are a couple of mistakes in the diagrams (chap 3), that are addressed in the errata, but the perl code is correct.

Book Description

Genetic Data Analysis, first published in 1990, became the standard reference for ways to interpret discrete population genetic data. Genetic Data Analysis II retains the strengths of the original book and, based upon the suggestions of users, includes many new features, notably the revision of Chapter 10 (Phylogeny Reconstruction) to incorporate newer methods, and new chapters on Linkage and Individual Identification.

Genetic Data Analysis II features an expanded set of Exercises, with solutions, and an expanded list of references. In addition, a suite of Windows-based programs written by Paul O. Lewis and Dmitri Zaykin is available without charge from the Web site maintained by the program in Statistical Genetics at North Carolina State University.

Bioinformatics for Geneticists: A Bioinformatics Primer for the Analysis of Genetic Data
Average customer rating:

A Timely Primer for Researchers about the Analysis of Genetic Data

Bioinformatics for Geneticists: A Bioinformatics Primer for the Analysis of Genetic Data
Michael R., Ed. Barnes
Manufacturer: John Wiley & Sons
ProductGroup: Book
Binding: Paperback

General | Biology | Biological Sciences | Science | Subjects | Books
Bioinformatics | Biological Sciences | Science | Subjects | Books
Genetics | Evolution | Science | Subjects | Books
General | Science | Subjects | Books
Genetics | Evolution | Professional Science | Professional & Technical | Subjects | Books
All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

Statistical Genomics: LINKAGE, MAPPING, AND QTL ANALYSIS

Bioinformatics for Dummies (For Dummies Series)

Essential Bioinformatics

The Genie in Your Genes: Epigenetic Medicine and the New Biology of Intention

Principles of Gene Manipulation and Genomics

ASIN: 0470026200

Book Description

A fully revised version of the successful First Edition, this one-stop reference book enables all geneticists to improve the efficiency of their research.

The study of human genetics is moving into a challenging new era. New technologies and data resources such as the HapMap are enabling genome-wide studies, which could potentially identify most common genetic determinants of human health, disease and drug response. With these tremendous new data resources at hand, more than ever care is required in their use. Faced with the sheer volume of genetics and genomic data, bioinformatics is essential to avoid drowning true signal in noise. Considering these challenges, Bioinformatics for Geneticists, Second Edition works at multiple levels: firstly, for the occasional user who simply wants to extract or analyse specific data; secondly, at the level of the advanced user providing explanations of how and why a tool works and how it can be used to greatest effect. Finally experts from fields allied to genetics give insight into the best genomics tools and data to enhance a genetic experiment.

Hallmark Features of the Second Edition:

Illustrates the value of bioinformatics as a constantly evolving avenue into novel approaches to study genetics
The only book specifically addressing the bioinformatics needs of geneticists
More than 500f chapters are completely new contributions
Dramatically revised content in core areas of gene and genomic characterisation, pathway analysis, SNP functional analysis and statistical genetics
Focused on freely available tools and web-based approaches to bioinformatics analysis, suitable for novices and experienced researchers alike

Praise for the First Edition:

”…a very valuable and important resource for bringing bioinformatics into the work practice of geneticists… we strongly recommend this book…” CLINICAL CHEMISTRY, 2004

”…a useful addition to the library of a seasoned scientist… a useful resource in itself, cataloguing the ‘how’ and ‘why’…” BRIEFINGS IN BIOINFORMATICS, June 2004

Bioinformatics for Geneticists, Second Edition describes the key bioinformatics and genetic analysis processes that are needed to identify human genetic determinants. The book is based upon the combined practical experience of domain experts from academic and industrial research environments and is of interest to a broad audience, including students, researchers and clinicians working in the human genetics domain.

Customer Reviews:

A Timely Primer for Researchers about the Analysis of Genetic Data.......2007-08-23

This book is a welcomed addition to the literature of bioinformatics. It helps one become familiar with how to find and use genetic data. This is a dauting task for most investigators who must navigate through the sea of genetic data now being produced. Analyzing genetic data is not an easy task but this book helps one identify resources and map a course.

Practical Methods for Design and Analysis of Complex Surveys (Statistics in Practice)

Average customer rating:

Practical Methods for Design and Analysis of Complex Surveys (Statistics in Practice)
Risto Lehtonen
Manufacturer: John Wiley & Sons
ProductGroup: Book
Binding: Hardcover

Methodology | Social Sciences | Nonfiction | Subjects | Books

Research | Social Sciences | Nonfiction | Subjects | Books

Statistics | Social Sciences | Nonfiction | Subjects | Books

Genetics | Evolution | Science | Subjects | Books

General | Science | Subjects | Books

General | Reference | Subjects | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Business & Investing | Qualifying Textbooks - Fall 2007 | Stores | Books

Nonfiction | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Reference | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

Analysis of Survey Data (Wiley Series in Survey Methodology)
Analysis Of Health Surveys (Wiley Series in Probability and Statistics)
Survey Methodology (Wiley Series in Survey Methodology)
Analyzing Complex Survey Data (Quantitative Applications in the Social Sciences)
Sampling of Populations: Methods and Applications (Wiley Series in Survey Methodology)

ASIN: 0470847697

Book Description

Large surveys are becoming increasingly available for public use, and researchers are often faced with the need to analyse complex survey data to address key scientific issues. For proper analysis it is also important to be aware of the different aspects of the design of complex surveys. Practical Methods for Design and Analysis of Complex Surveys features intermediate and advanced statistical techniques for use in designing and analysing complex surveys. This extensively updated edition features much new material, and detailed practical exercises with links to a Web site, helping instructors and enabling use for distance learning.

Provides a comprehensive introduction to sampling and estimation in descriptive surveys, including design effect statistic and use of auxiliary data.
Includes detailed coverage of complex survey analysis, including design-based ANOVA and logistic regression with GEE estimation.
Contains much new material, including handling of non-sampling errors, and model-assisted estimation for domains.
Features detailed real-li fe case studies, such as multilevel modeling in a multinational educational survey.
Supported by a Web site containing software codes, real data sets, computerized exercises with solutions, and online training materials.

Practical Methods for Design and Analysis of Complex Surveys provides a useful practical resource for researchers and practitioners working in the planning, implementation or analysis of complex surveys and opinion polls, including business, educational, health, social, and socio-economic surveys and official statistics. In addition, the book is well suited for use on intermediate and advanced courses in survey sampling.

Download Description

"Statistical complex survey analysis is a means to analyse the results, and gain information about a large population based on a complex survey of a sample of that population. A complex survey is a sample survey that divides the population into subgroups and collecting information from clusters within each subgroup and combining the results. Since the publication of the first edition in 1994, the field has changed considerably and the topic is now relevant beyond the narrow circle of survey statisticians. With large surveys becoming increasingly available for public use, researchers with little experience in survey methods are often faced with analyzing data from surveys to address scientific and programmatic issues. This practical book fills a niche by providing advanced statistical techniques for use in survey analysis, making complex surveys accessible to those working in statistics, business, economics, and the health and social sciences. "

Microarrays for an Integrative Genomics (Computational Molecular Biology)

Average customer rating:

A helpful and informative overview
Well written
Not well written...
lots of important stuff
Amazing

Microarrays for an Integrative Genomics (Computational Molecular Biology)
Isaac S. Kohane , Alvin Kho , and Atul J. Butte
Manufacturer: MIT Press
ProductGroup: Book
Binding: Hardcover

Biochemistry | Biological Sciences | Science | Subjects | Books

Bioinformatics | Biological Sciences | Science | Subjects | Books

Genetics | Evolution | Science | Subjects | Books

General | Science | Subjects | Books

General | Computers & Internet | Subjects | Books

General | Databases | Computers & Internet | Subjects | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

Microarrays and Gene Expression
Bioinformatics: Sequence and Genome Analysis
Structural Bioinformatics (Methods of Biochemical Analysis, V. 44)
Microarray Bioinformatics
The Analysis of Gene Expression Data

ASIN: 026211271X

Book Description

Functional genomics--the deconstruction of the genome to determine the biological function of genes and gene interactions--is one of the most fruitful new areas of biology. The growing use of DNA microarrays allows researchers to assess the expression of tens of thousands of genes at a time. This quantitative change has led to qualitative progress in our ability to understand regulatory processes at the cellular level.

This book provides a systematic introduction to the use of DNA microarrays as an investigative tool for functional genomics. The presentation is appropriate for readers from biology or bioinformatics. After presenting a framework for the design of microarray-driven functional genomics experiments, the book discusses the foundations for analyzing microarray data sets, genomic data-mining, the creation of standardized nomenclature and data models, clinical applications of functional genomics research, and the future of functional genomics.

Customer Reviews:

A helpful and informative overview.......2006-01-05

The authors of this book are very excited about the prospects of the field of functional genomics and DNA microarray technology. Their optimism however is tempered by a large degree of caution, for they make it clear in the first few paragraphs of the book that expression profiling using microarrays is still in its infancy and that there have been exaggerated reports of its success. They wrote this book with the intent of giving the reader a more realistic view of microarray technology and have succeeded in their goal. They target the book specifically to experienced biologists and bioinformaticians with limited experience in using microarrays, and to students who are entering the field of bioinformatics. Most importantly, they emphasize that functional genomics is an experimental science, and that highly sophisticated algorithms from data mining or other areas of artificial intelligence will be of no assistance if the experimental information is not there in the first place. They do encourage however further development of these algorithms, in order to be able to extract the data as it becomes available, and as microarray technology itself matures. Even with the current technology, enormous amounts of data are generated, and if sense is to be made of this data, one will have to develop more effective algorithms than what are currently available.

To perform successful experiments, the authors describe a `functional genomics pipeline', and list the characteristics that it must have, consisting of both `wet' (laboratory) and `dry' (computational) steps. They devote a lot of space in the book describing how to develop an effective genomic experiment. Crucial to such investigations they say is a design that maximizes the possibility of observing relevant gene expression patterns, and the `experiment design space', which encapsulates all possible conditions that a particular biological system could be influenced by. Also important to the design is the `expression space', which is the collection of all potential expression values of all genes in a given genome. One could view the expression space as a vector space of high dimension, with each dimension corresponding to a single gene. Of great interest, and widely discussed in the general bioinformatics literature under the guise of the new field of `systems biology' is a subset of the expression space called the `transcriptome.' This subset models the expression of a cellular system under all stimuli. Considering that one might have to deal with 30,000 genes in the case of a human, the characterization of the transcriptome will be a formidable project. Interactions between the genes will complicate the analysis even further. The authors view each experiment as being an exploration of the space of all possible expression patterns, and describe good experimentation as being the `maximal exercise' of the genome. This consists of finding those correlations between the genes that have the greatest impact on the process under scrutiny.

A book on microarrays would not be complete if it did not discuss how they actually function. This is done in a fair detail in chapter three of the book. The authors do not favor a particular vendor but rather discuss what biological assumptions all microarray technology is based on. One of these assumptions is, as expected, that there is a direct connection between mRNA transcription and the protein translation associated with it.

In any laboratory experiment one has to deal with experimental uncertainty or "noise." This involves the influence of unknown external perturbations that result in variability in the outcomes of the experiment. As further evidence that the authors are careful experimenters, they discuss noise in detail, noting first that expression experiments deal with information that is both digital (DNA sequence information) and analog (mRNA expression levels). They distinguish between `intra-chip' noise, which arises when one probe feature influences another, improper scanning techniques, and manufacturing defects, and `inter-chip' noise, which arises from sample variation. Normalization issues are also discussed. Readers should take particular attention to the discussion on fold calculation and significance because of its connection with statistical analysis and because it sets the tone for the rest of the book. In particular, this discussion leads to the very important topic of dissimilarity and similarity measures. This part of the book is more sophisticated mathematically than what has been encountered so far, dealing for example with the concept of a metric space, which may appear to be somewhat abstract by readers who are not mathematically astute. Linear correlation and mutual information are two examples of metrics that are discussed.

Data mining is of course heavily discussed in the book, along with the new field of `ontological engineering' and how the latter is used functional genomics. Data mining is of course a vast field, but the authors give the reader a good taste of how some of its techniques can be applied to analyze microarray experiments. Both unsupervised and supervised learning is discussed, along with `self-organizing maps.' The authors end the book with their vision of future developments. Naturally they point to further refinements in microarray technology, the need for educating a new generation of bioinformaticists, and the push towards the development of new data mining algorithms. Certainly all of these are important, and one can expect other technological developments to occur in the coming years that may prove superior to microarrays in their application to functional genomics. In addition, and there are indications of this even at the present time, one can expect technologies that fully automate the study of gene expression. This includes the generation of hypotheses that characterize scientific investigation, the development and construction of the experiments themselves, and the analysis of the resulting data.

Well written.......2004-06-29

This is a well written book that gives an overview of the technology of microarrays and their use as investigative tools in functional genomics experiments. I found the technical and analytical descriptions very easy to follow. This is still the only book around that can bring any investigator with little knowledge of molecular biology, data analysis, and/or microarrays up to speed in the field. It is also a good text book for a graduate level course on microarray data analysis.

Not well written..........2004-02-27

I am not an informatics researcher, however I hold a doctorate in biotechnology related areas, as well a law degree. I routinely purchase books and journals to keep up. However, the problem with this book is its presentation. It is written in an almost stereotypically pretentious manner to the extent that it clearly detracts from the subject matter's presentation. Did you know that a tissue or cell type may be "interrogated"? Coincedentally, I happened upon a brief review article by the same author in Nature Biotech. Again the writing was such that it was too much of an effort to extract what was being said. For those who feel drawn to this book, check the internal pages on Amazon's site.

lots of important stuff.......2004-01-21

This book contains lots of important topical information on the design and analysis of microarray experiments. It calls attention to a lot of important but sometimes subtle issues that many biologists appear to be overlooking. It appears to be a must-read for researchers who want to avoid expensive dead ends. But it's not perfect...

A well-informed computer scientist will recognize that quite a few computational statements are just plain wrong (e.g., p 180,
"[Dendrograms] require the comprehensive precomputation of the dissimilarity measure for all pairs of genes, which grows on the order of N^2" Wrong! Try bucketing. Or p 139, a dissimilarity function based on linear correlation coefficients is "definite". No! If x is a vector and C is a scalar, then clearly x=/=Cx, but d(x,Cx)=0, contrary to the definition of "definite". The "pseudocode" in Chapter 4 is not any clearer than the text, and it is not structured in a way that would allow it to be elaborated into well-engineered code. So rely on this book for big ideas and references, not for details. The book also reinforces my preconception that MIT Press doesn't employ editors... 'way too many typos, for starters.

You have to know the basics of molecular biology for this book, and it wouldn't hurt to have a basic understanding of DNA chips as well. It's definitely not the first step for a mathematical scientist hoping to become a bioinformatician. (But why should it be? :c)

Amazing.......2002-10-14

This is the book we have all been waiting for. The authors do an amazing job of describing, in understandable terms, how to perform meaningful microarray experiments. I highly recommend this seminal work.

Exploration and Analysis of DNA Microarray and Protein Array Data (Wiley Series in Probability and Statistics)

Average customer rating:

Excellent!

Exploration and Analysis of DNA Microarray and Protein Array Data (Wiley Series in Probability and Statistics)
Dhammika Amaratunga
Manufacturer: John Wiley & Sons, Inc
ProductGroup: Book
Binding: Hardcover

Biochemistry | Biological Sciences | Science | Subjects | Books

Genetics | Evolution | Science | Subjects | Books

Research | Education | Science | Subjects | Books

Methodology & Statistics | Experiments, Instruments & Measurement | Science | Subjects | Books

General | Science | Subjects | Books

Biotechnology | Special Topics | Medicine | Subjects | Books

Biostatistics | Research | Medicine | Subjects | Books

All Titles | Qualifying Textbooks - Fall 2007 | Stores | Books

Medicine | Qualifying Textbooks - Fall 2007 | Stores | Books

Professional | Qualifying Textbooks - Fall 2007 | Stores | Books

Science | Qualifying Textbooks - Fall 2007 | Stores | Books
Similar Items:

Statistics for Microarrays: Design Analysis and Inference
Data Analysis Tools for DNA Microarrays
Design and Analysis of DNA Microarray Investigations
Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health)
Statistical Analysis of Gene Expression Microarray Data

ASIN: 0471273988

Book Description

The emergence of genomics, the study of genes, is one of the major scientific revolutions of this century. Microarrays, a method used to analyze numerous DNA samples rapidly, enables scientists to make sense of this mountain of data using statistical analysis. They are being used in such areas of biomedical research as studying patterns for gene activity that cause cancers to spread. This book presents a comprehensive methodology for analyzing DNA microarray and protein array data.
The most comprehensive treatment of this important emerging field, Exploration and Analysis of DNA Microarray and Protein Array Data includes:
A review of basic molecular biology and a chapter introducing microarrays and their preparation
Chapters on processing scanned images, preprocessing microarray data, group comparative experiments, and other designs
Discussions of clustering, protein arrays, and applications for diagnostic tools
Ample exercises assist absorbtion

Customer Reviews:

Excellent!.......2004-03-30

This book provides an excellent overview of various methods in DNA microarray analysis. It explains most of the theories behind the algorithms, so that you know why the analyses are done in certain way. In fact, I find I get more insights from the book as compare to the research papers which tend to be brief.

Books:

Books Index

Books Home

Recommended Books