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| By: Dev Kambhampati ISBN: 3527305971 Publisher: Wiley-VCH Release Date: 19 March, 2004 Bioscience book rank: 1275961 | In support of this book it was pretty clear and did a very good job citing relevant papers and companies producing the technology. I'm not saying it's good or bad but this book focuses heavily on surface plasmon resonance (SPR) detection of analyte. By this I mean about 1/3 of its ~230 pages are on SPR. SPR has its own advantages and disadvantages but if you're not planning to use it, this probably isn't the book for you. Check out Schena's Protein Microarrays if you're looking for less specific coverage (about twice as many pages and cost me 1/4 the price). | |
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| By: Terry Speed ISBN: 1584883278 Publisher: Chapman & Hall/CRC Release Date: 26 March, 2003 Bioscience book rank: 692289 | Microarray studies are becoming the preferred research tools in many areas, including cancer research, development studies, and studies in organisms' responses to their environments. Because of differences between organisms or between experiments, microarray data is always statistical in nature. The problem is that the data aren't well suited to traditional statistics. Instead of studying a few characteristics in large numbers of individuals, microarray studies typically yield thousands of data values for a few dozen samples.
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<br />That mismatch, between current statistical practice and microarray analysis requirements, seem to be driving many innovations in statistical analysis. This book is a brief survey of four of those areas of analysis: model-based analysis, experimental design, classification, and clustering.
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<br />The first section, on model-based analysis, is brief. Mostly, it seems to establish the language used in later sections. The next, on experimental design, deals with ways for getting the most information out of the fewest samples. The costs of arrays and processing are dropping, but still high. More analysis on less data makes good economic sense. The DNA samples analyzed also have costs - some can only be prepared in minute amounts, others must be extracted surgically from human patients. Either way, it's important to maximize the knowledge harvested from limited amounts of biologcal material.
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<br />The next section, on discrimination, is a bit longer. It briefly summarizes a wide variety of techniques for deciding which category best represents any one sample. This section gives a good review of analytic approaches: Fisher classifiers and their descendants, principal components, support vectors, and decision trees. Within trees, the authors note that the number of missing values in typical microarray data may interfere with standard analysis, and that surrogate variables may be needed in many cases. AI and data mining techniques aren't broadly represented, but this chapter is still very informative.
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<br />The final section, on clustering, was shorter. It was reasonably informative, and I gleaned a few new facts from it. Mostly, though, it seemed to present techniques that are already well known.
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<br />This book is a survey, so it emphasizes breadth over depth. Many algorithms described only briefly, and some are just mentioned by name. The developer will need to chase references to find an implementable level of detail. Still, the book has value as an index to references and as a comparison of techniques.
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<br />//wiredweird Thorough converage of statistics involved in microarray data analysis. It presents important knowledge for biologists who use data analysis tools but would like to know what is behind the scene. Understanding the book needs some statistical background and hence not a easy book for biologists and genetists who do not have that knowledge. <br>I would like to emphasize that experiment design issue is presented in a very clear way and should be read by all who plan to start project related to gene expression. Clustering and classification are two major analysis methods for microarray data, and the comprehensive discussion of the statistical mechanisms for each method in the last two chapters will help analysts to choose the right methods when mining the data. The first chapter seems to be a little out of the place, because it mainly discusses model-based genechip data analysis. This chapter touches a little about preprocessing and gene selection but far from complete.<br>A chapter with thorough discussion of pre-processing techniques and gene selection techniques would make this a prefect book. Overall it is a great reference for anyone who is interested in microarray data analysis! | |
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| By: Alan R. Kimmel, Brian Oliver ISBN: 0121828158 Publisher: Academic Press Release Date: 28 August, 2006 Bioscience book rank: 1272222 | ||
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| By: Steen Knudsen ISBN: 0471784079 Publisher: Wiley-Liss Release Date: 11 September, 2006 Bioscience book rank: 1238097 | ||
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| By: Steen Knudsen ISBN: 0471656046 Publisher: Wiley-Liss Release Date: 02 March, 2004 Bioscience book rank: 1014362 | True to its stated purpose: best used as a roadmap by mathematically unsophisticated newcomers to analysis of microarray data. Somewhat superficial, and it becomes more so in later chapters. Does not explore harder issues in detail. Does not touch upon future directions of the technology. Its advocacy of the Unix awk program is anachronistic; tellingly, the reference cited for awk is from 1988. Not a groundbreaking book, just solid practical advice. "...This useful little book .... I'd recommend anyone setting out to use this methodology to buy a copy for the lab." (British Society for Developmental Biology Newsletter) "...I'd recommend anyone setting out to use this methodology to buy a copy for the lab." (British Society for Cell Biology Newsletter) | |
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| By: Pierre Baldi, G. Wesley Hatfield, Wesley G. Hatfield ISBN: 0521800226 Publisher: Cambridge University Press Release Date: 30 September, 2002 Bioscience book rank: 841079 | This book tries to combine a practical and theoretical point of view concering microarray expermiments and the data analyis thereof. This is a very honourable goal. Unfortunatelly, it fails. An indicator for this can already be seen in the low number of pages. This book has less than 140 pages (I exclude the last chapter and the appendix). It is clear, that it is impossible to discuss in detail this topic in this limited number of pages. Hence, during reading the chapters one gets the feeling, that one reads short essays which are stringed together. At no point the authors go into detail but give only a short idea and references.
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<br />I see no reason, why I should recommend this book to anyone. It is in its current form just immature. My prediction: There will be no second edition because even its basic substance is very weak.
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<br />Some words to the last chapter (systems biology). This is indeed the most interesting and best chapter of the book (35 pages) without going into details as the rest of the book. I think according to this chapter one realize under which premise this book was written. Unfortunatelly, combining buzz worlds in short essays is not enough for a good book. Sorry guys, I think you can do better! This book has a good balance between experimental and computational methods. It provides a description of DNA microarray technologies, experimental protocols, and the multiple sources of noise and variability. The book contains an insightful overview of the computational issues and available algorithms for data analysis from differential expression, to dimensionality reduction and visualization (e.g. PCA), to clustering (e.g. hierarchical). New methods are described to gether with a good overview of available software, data bases, web sites, and other resources, as well as several "walk through" examples. I particularly enjoyed the last chapter on Systems Biology. "Very complete : covers both the experimental and the computational methods with specific examples. Written by two top scientists who have worked hard at complementing each other's strengths. I particularly enjoyed the last chapter on Systems Biology which provides a masterful overview of current resaerch trends." | |
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| By: Mark Schena ISBN: 0199637768 Publisher: Oxford University Press, USA Release Date: 26 August, 1999 Bioscience book rank: 1158963 | I am basically a newbie in this area and was hoping to learn the basics of using microarrays for sequencing and expression analysis. While it was somewhat helpful for me, I think that it is aimed at a more expert audience already well versed in molecular biology techniques. I found the documentation and other info on the Affymetrix site to be more comprehensive and explanatory. This book is a good primer on microarrays. | |
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| By: Mei-Ling Ting Lee ISBN: 0792370872 Publisher: Springer Release Date: 30 April, 2004 Bioscience book rank: 1074708 | ||
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| By: Marck, Ed. Schena ISBN: 1881299376 Publisher: EATON PUBLISHING Release Date: 15 April, 2000 Bioscience book rank: 1264400 | This book is little more than a series of plugs from biotech firms trying to sell their technologies. It's seriously outdated anyway, so don't bother. _Microarray Biochip Technology_ provides a nice summary of microarray technologies at the time of publication (early 2000) from one of the persons (Mark Schena) who ought to know. To learn the latest and greatest, you'll still have to find the most recent review articles. However, this book is a useful handbook for getting started with the basics of microarray technologies.<p>The focus is on the hardware for spotting, not as much on scanning or data analysis. I like it somewhat better as a practical guide for the basics than Rampal's _DNA Arrays_, which covers a alternate uses of microarrays. This book is quite basic and it does not have specific protocols however it does give you a general overview to methods of several players in the field. You just have to keep on reminding yourself that each company presents itself so everything is seen through the optimistic point of view. | |
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| By: Stuart Handwerger, Bruce Aronow ISBN: 1588296512 Publisher: Humana Press Release Date: 18 December, 2007 Bioscience book rank: 1756017 | ||
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methods in molecular biology, PCR, RT-PCR and real-time quantitative PCR, Differential Display, recombinant DNA, gene therapy, virus protocols, lentivirus methods, gene targeting, mouse knock-out and knock-in, transgenic technology, phenotyping, gene delivery and transfer, transcriptional regulation, RNA methods, RNA Polymerase, gene expression, protein translation regulation, protein kinase, protein phosphorylation, genomics, genomics methods, epigenetics, DNA methylation, DNA sequencing, RNA interference, microarray
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