Bioinformatics: Managing Scientific Data (The Morgan Kaufmann Series in Multimedia Information and Systems) Review

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Bioinformatics: Managing Scientific Data (The Morgan Kaufmann Series in Multimedia Information and Systems) ReviewThe book compiles chapters written by different authors all of whom are experts in the area of managing life science and/or scientific data. The variety of approaches, the clear description, and the details make this book an important source for those who want to know more about the "state-of-the-art" data management in the area of bioinformatics. By presenting such a great mixtures the reader can reflect on hes/her own requirements thus using this book as a first step for making a decision how to manage one's own data in this realm.
Those who are active in managing life science data will find this book to be a great resource and a great starting point to get a comprehensive overview of alternative solutions and their strength and weaknesses.Bioinformatics: Managing Scientific Data (The Morgan Kaufmann Series in Multimedia Information and Systems) Overview

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Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins Review

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Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins Review"The novice user of bioinformatics tools needs a guide that answers several fundamental questions - what are these tools designed for and what can they do; what are their limitations; how does one access them, and where can one find further information. For each of the basic sub-fields of bioinformatics, Bioinformatics provides a survey, a list of world wide web addresses (URLs), and a list of monographs and reviews to which the reader may go for further information. Each chapter covers fundamental definitions and makes no assumptions about prior knowledge.... The book provides a broad overview of the basic tools for sequence analysis. It is a good starting point for the reader who wants to learn about the types of tools used in bioinfomatics and how to get started. For biologists approaching this subject for the first time, it will be a very useful handbook to keep on the shelf after the first reading, close to the computer." --Terry Gaasterland, The Rockefeller UniversityBioinformatics: A Practical Guide to the Analysis of Genes and Proteins OverviewReviews of the Second Edition"In this book, Andy Baxevanis and Francis Ouellette . . . have undertaken the difficult task of organizing the knowledge in this field in a logical progression and presenting it in a digestible form. And they have done an excellent job. This fine text will make a major impact on biological research and, in turn, on progress in biomedicine. We are all in their debt."--Eric Lander, from the Foreword to the Second Edition"The editors and the chapter authors of this book are to be applauded for providing biologists with lucid and comprehensive descriptions of essential topics in bioinformatics. This book is easy to read, highly informative, and certainly timely. It is most highly recommended for students and for established investigators alike, for anyone who needs to know how to access and use the information derived in and from genomic sequencing projects."--Trends in Genetics"It is an excellent general bioinformatics text and reference, perhaps even the best currently available . . . Congratulations to the authors, editors, and publisher for producing a weighty, authoritative, readable, and attractive book."--Briefings in Bioinformatics"This book, written by the top scientists in the field of bioinformatics, is the perfect choice for every molecular biology laboratory."--The Quarterly Review of BiologyThis fully revised version of a world-renowned bestseller provides readers with a practical guide covering the full scope of key concepts in bioinformatics, from databases to predictive and comparative algorithms. Using relevant biological examples, the book provides background on and strategies for using many of the most powerful and commonly used computational approaches for biological discovery. This Third Edition reinforces key concepts that have stood the test of time while making the reader aware of new and important developments in this fast-moving field. With a new full-color and enlarged page design, Bioinformatics, Third Edition offers the most readable, up-to-date, and thorough introduction to the field for biologists.This new edition features:* New chapters on genomic databases, predictive methods using RNA sequences, sequence polymorphisms, protein structure prediction, intermolecular interactions, and proteomic approaches for protein identification* Detailed worked examples illustrating the strategic use of the concepts presented in each chapter, along with a collection of expanded,more rigorous problem sets suitable for classroom use* Special topic boxes and appendices highlighting experimental strategies and advanced concepts* Annotated reference lists, comprehensive lists of relevant Web resources, and an extensive glossary of commonly used terms in bioinformatics, genomics, and proteomicsBioinformatics, Third Edition is essential reading for researchers, instructors, and students of all levels in molecular biology and bioinformatics, as well as for investigators involved in genomics, clinical research, proteomics, and computational biology.

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Principles of Biomedical Informatics Review

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Principles of Biomedical Informatics ReviewThis is an *excellent* book. I read it enthusiastically and I'm glad that it was available for me to do so. I think it fills a unique niche in the informatics book market in two ways:
- it is a book with significant attention to clinical informatics that has a strong computer science angle.
- it is an informatics "monograph"
While informatics is often described as the intersection between something like computer science, life science/medicine and library science books rarely position themselves squarely at this intersection. I have found that it is easier to find bioinformatics books that have a strong computer science angle than it is to find clinical informatics books with a strong CS/implementation angle. This book is the exception to that rule. It has an unabashedly serious approach to the computing inherent in clinical informatics (one should take author's choice of Lisp as telling) and a clinical focus. The treatment of library science topics, while less rigorous, is present and credible.
Unlike the standard textbooks in the area (ex: Shortliffe) it is not an edited volume; rather, it hangs together page after page as a single work by a single author. Because it has the hand of an individual it a much more pleasant book to read from cover-to-cover.
The physical book is very appealing. The pager is glossy and thick, the binding is substantial, the dimensions are pleasant, the figures are clear, and the typesetting (as with all LaTeX books) beautiful. Unfortunately unlike most LaTeX books it is hard to read. While the pages look wonderful I found that function was sacrificed in the process. The vertical spacing is cramped, the margins are small, and the lines are long. This makes the going slow and difficult which detracts from an otherwise excellent book. If it was 50 pages longer with a bit more generous white space the book would be a complete home run.
In short, I have nothing but positive things to say about the content of this book and mixed emotions about the physical book. I would suggest that the ideal reader has some background in informatics. For total novices the larger edited volumes are a better starting point. Additionally, while a reasonable introduction to Lisp is provided some background knowledge of the language is helpful.
If you care about informatics, have a soft spot for Lisp and want to really hold the field in your hands this is a book that cannot be overlooked.Principles of Biomedical Informatics OverviewThis book provides a foundation for understanding the fundamentals of biomedical informatics, which deals with the storage, retrieval, and use of biomedical data for biological problem solving and medical decision making. It covers the application of these principles to the three main biomedical domains of basic biology, clinical medicine, and public health. The author offers a coherent summary, focusing on the three core concept areas of biomedical data and knowledge representation, biomedical information access, biomedical decision making, and information and technology use in biomedical contexts.* Develops principles and methods for representing biomedical data, using information in context and in decision making, and accessing information to assist the medical community in using data to its full potential* Provides a series of principles for expressing biomedical data and ideas in a computable form to integrate biological, clinical, and public health applications* Includes a discussion of user interfaces, interactive graphics, and knowledge resources and reference material on programming languages to provide medical informatics programmers with the technical tools to develop systems

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Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics) Review

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Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics) ReviewThis second edition of Shortliffe's textbook is an excellent overview of the field. Although I used it as a course text, it is extremely readable. The chapters are not overly technical, as befits an introductory text, but by no means is this a "Dummmies" book either.
There are now a variety of introductory/overview books on medical informatics. However, of the ones I've read (including van Bemmel's Handbook of Medical Informatics and Coiera's Guide to Medical Informatics), this book is by far the best.Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics) OverviewThis book focuses on the role of computers in the provision of medical services. It provides both a conceptual framework and a practical approach for the implementation and management of IT used to improve the delivery of health care. Inspired by a Stanford University training program, it fills the need for a high quality text in computers and medicine. It meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. Completely revised and expanded, this work includes several new chapters filled with brand new material.

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Principles of Health Interoperability HL7 and SNOMED (Health Informatics) Review

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Principles of Health Interoperability HL7 and SNOMED (Health Informatics) ReviewThis is a revised review. I reviewed this book shortly after it came out and give it four stars. That was, however, a bit of a grumpy review. Since then I've made this book the mainstay of the health informatics lectures I do for the U of Minnesota. I would now give it four stars without reservation. In this domain there's no rival to this text.
Overall it is a book aimed at an informatics student, written in a telegraphic style that is a good fit for a rather dry but terribly important topic. Only a portion of the book is about HL7 and SNOMED however. Of the 225 pages I found
- 74 on modeling and markup topics better addressed in other books
- 12 pages on SDOs
- 81 pages on HL7 and CDA/CCR/CCD
- 26 on SNOMED
- 8 pages on using HL7 and SNOMED together
Although I would prefer much less coverage of modeling and markup and more on HL7/SNOMED integration, there's still more than enough material to occupy a typical first class in health informatics. This is a better book for my purposes that the informatics textbooks I've used to date.
I hope there will be a 2nd edition. I know I'd buy it!Principles of Health Interoperability HL7 and SNOMED (Health Informatics) OverviewJoined-up healthcare makes information available when and where it is needed to improve safety, efficiency and effectiveness. Politicians may take interoperability between healthcare computer systems for granted, but it is non-trivial. Healthcare integration projects are notoriously under-estimated and come in over-budget and over-time. Joined-up healthcare depends on standards. The two leading standards are the SNOMED CT, which is a clinical terminology (semantics) and HL7 Version 3, which is a specialised healthcare interoperability language (syntax). Both are new, complex and fit for purpose.Tim Benson believes there is an unmet need for a book on Healthcare Integration. Some health informatics textbooks include chapters on HL7 and/or SNOMED, but these are usually quite short and cannot provide even an adequate introduction. There is little of much value on the Internet, or in journals or conference proceedings.

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R Programming for Bioinformatics (Chapman & Hall/CRC Computer Science & Data Analysis) Review

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R Programming for Bioinformatics (Chapman & Hall/CRC Computer Science & Data Analysis) ReviewThis is a strange little book in that it seems somewhat directed toward statisticians who want to develop R packages. The OOP section takes up 50 pages and discusses "S3 and S4" implementations of OOP in R in great detail, all of which is not doubt important for those few dozen accomplished statisticians who wish to write packages. However, by the time you are ready to actually write an R function that other people will use I can't imagine you wouldn't already be familiar with some of the basic commands discussed elsewhere in this book. So I am wondering who the intended audience is.
I think the majority of R users (biologists and programmers) want to run through some common statistical routines in a procedural fashion and produce reports that perform some analysis and show some graphs. The difficulty with R is learning how to massage data into a form that an existing statistical function will accept. That will invariably involve helper R-specific helper functions that do not exist in programming languages (e.g. unsplit) or that require a precise understanding of input (e.g. xtabs), and statistical routines that almost never return meaningful errors (glm). Manipulating data structures in R is not particularly intuitive (e.g. as.numeric(levels(f))[f]), so tons of examples are a must. However this book simply does not include enough R code - probably fewer than 250 lines.
In some instances commands are discussed at length in the space it would take to simply show the command. For example, a beginner would want to know how to save a data frame. Instead of providing a useful example like:
save(myDataFrame,file="myDataFrame.frame.RData",compress=TRUE)
there is a bizarre paragraph called "Working with R's binary format", in which save and load are discussed in theory as if they are planned for a distant release.
There is no chapter on using Sweave to develop pdf reports despite the book being actually written in Sweave. The author is more focused on "vignettes" which appear to be for documentation akin to POD files.
This book does include excellent sections on string manipulation, connecting to databases, and C integration. I learned some things about some neat Bioconductor functions available but a dedicated chapter would be nice.
At no point do you ever sense the author does not know what he is talking about - he just doesn't know who he is talking to. I hope in the future "R Programming For Bioinformatics" is split this into two more comprehensive books: "Developing R Packages" and "R for Biologists"R Programming for Bioinformatics (Chapman & Hall/CRC Computer Science & Data Analysis) OverviewDue to its data handling and modeling capabilities as well as its flexibility, R is becoming the most widely used software in bioinformatics. R Programming for Bioinformatics explores the programming skills needed to use this software tool for the solution of bioinformatics and computational biology problems.Drawing on the author's first-hand experiences as an expert in R, the book begins with coverage on the general properties of the R language, several unique programming aspects of R, and object-oriented programming in R. It presents methods for data input and output as well as database interactions. The author also examines different facets of string handling and manipulations, discusses the interfacing of R with other languages, and describes how to write software packages. He concludes with a discussion on the debugging and profiling of R code.With numerous examples and exercises, this practical guide focuses on developing R programming skills in order to tackle problems encountered in bioinformatics and computational biology.

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