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.
Average customer rating:
- Up to Date and Very Well Done
- Poorly Written, Good graphics
- The future may view this text as a foundation for GS
- Excellent overview of Functional and Structural Genomics
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A Primer of Genome Science, 2nd Edition
Greg Gibson , and
Spencer V. Muse
Manufacturer: Sinauer Associates
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Discovering Genomics, Proteomics and Bioinformatics (2nd Edition) (The Genetics Place Series)
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Genomes 3
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Bioinformatics For Dummies (For Dummies (Math & Science))
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Beginning Perl for Bioinformatics
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The Evolution of the Genome
ASIN: 0878932321 |
Book Description
Genome science as a discipline is less than five years old, but has already spawned a revolution in the way in which genetics is taught in universities, approached by academic researchers, and applied by pharmaceutical and agricultural research companies. While over a dozen new journals devoted to genomics have appeared in the last few years, no introductory textbook that covers the range of disciplines incorporated into genome science has materialized, until now. A Primer of Genome Science bridges the gap between standard genetics textbooks and highly specialized, technical, and advanced treatments of the subdisciplines. It provides an affordable and up-to-date introduction to the field that is suited to advanced undergraduate or early graduate courses. Bioinformatic principles and experimental strategies are explained side-by-side with the experimental methods, establishing a framework that allows teachers to explore topics and the literature at their own pace.
The Primer is organized into six chapters. Each chapter includes: exercises that can be worked by students using the internet and freely available software for analysis of genomic data; discussion questions; a summary; and suggestions for further reading. An Appendix includes a glossary of terms, with a brief review of key genetic concepts.
Customer Reviews:
Up to Date and Very Well Done.......2005-08-11
With the basic science being so new and changing so rapidly, this second edition is timely and welcome. Virtually every chapter has been re-written to bring it up to date. The result is a text suitable for use in upper under grad or beginning grad level course in functional genomics or bioinformatics. The six chapter headings are:
Genome Projects: Organization and Objectives
Genome Sequencing and Annotation
SNPs and Variation
Gene Expression and the Transcriptome
Proteomics and Functional Genomics
Integrative Genomics.
The book is well written and profusely illustrated with color drawings and photographs. The book is closely allied with the web in form of accessable databases and the like which may keep it from going out of date so fast.
With most text books being so expensive, this book is a definite sleeper in the field.
Poorly Written, Good graphics.......2004-01-09
The book is very poorly written and is too difficult to follow to be called a "primer." Authors often focus on actual software tools and how to use them rather than the science behind them.
To be fair, the graphics offered in the book are excellent and sometimes are the only way to understand a difficult concept.
The preface says to be familiar with "the content of a typical 300 level undergraduate course in genetics" -- it should be a definite prerequisite for reading this book.
The future may view this text as a foundation for GS.......2003-05-15
Every technician and/or PI should own a copy of this text for their lab. With the logical diagrams and full explanation of the text, this book is really condensed and assumes some knowledge of molecular biology. This book does not assume knowledge of genomics, but rather serves as a manual.
Excellent overview of Functional and Structural Genomics.......2002-03-20
This somewhat understated book may be overlooked based on its title, and yet it represents the best book currently in print to provide a solid overview of the science and issues in genome science, functional and structural genomics, and the subdiscipline proteomics. Chapter 1 describes current progress with mapping genomes, including the human genome and other genomes in plants and animals. Chapter 2 describes sequencing approaches and gene identification. Chapter 3 deals with gene expression and technologies. Chapter 4 focuses on proteomics including brief introductions to 2D-PAGE and mass spectrometry. This chapter also briefly introduces the reader to structural genomics, or the prediction of protein structure based on sequence through threading and modeling. After a chapter on single nucletide polymorphisms and genotyping the book concludes with a chapter on integrating genome studies including the use of in silico approaches.
Although scant in detail in parts, a major strength of the book is the wide coverage given to science of genomics and its offshoots. Overall an excellent course text for undergraduate or early postgraduate students or others interested in these emerging disciplines. I am not aware of any competing texts which such coverage and certainly not at the price of this one.
Average customer rating:
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Handbook of Genome Research: Genomics, Proteomics, Metabolomics, Bioinformatics, Ethical & Legal Issues
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Bioinformatics For Dummies (For Dummies (Math & Science))
ASIN: 3527313486 |
Book Description
In this unique presentation of a revolutionary field of science, the first section introduces the domains of application for genomics and bioinformatics, such as sequencing and the comparative sequence analysis of model organisms, investigating genetically influenced diseases, the development of new active substances, agri-food and environmental genomics.
There then follows an overview of current topics central to DNA technologies, proteomics, metabolomics and bioinformatics, including such hot topics as DNA chip fabrication, yeast two hybrid analysis, tools for gene expression studies, metabolic networks and systems biology.
The whole is rounded off by four chapters on the ethical, legal and social aspects of this sensitive topic.
Book Description
Computational Genome Analysis: An Introduction presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book is appropriate for a one-semester course for advanced undergraduate or beginning graduate students, and it can also introduce computational biology to computer scientists, mathematicians, or biologists who are extending their interests into this exciting field.
This book features:
Topics organized around biological problems, such as sequence alignment and assembly, DNA signals, analysis of gene expression, and human genetic variation
Presentation of fundamentals of probability, statistics, and algorithms
Implementation of computational methods with numerous examples based upon the R statistics package
Extensive descriptions and explanations to complement the analytical development
More than 100 illustrations and diagrams (some in color) to reinforce concepts and present key results from the primary literature
Exercises at the end of chapters
Michael S. Waterman is a University Professor, a USC Associates Chair in Natural Sciences, and Professor of Biological Sciences, Computer Science, and Mathematics at the University of Southern California. A member of the National Academy of Sciences and the American Academy of Arts and Sciences, Professor Waterman is Founding Editor and Co-Editor in Chief of the Journal of Computational Biology. His research has focused on computational analysis of molecular sequence data. His best-known work is the co-development of the local alignment Smith-Waterman algorithm, which has become the foundational tool for database search methods. His interests have also encompassed physical mapping, as exemplified by the Lander-Waterman formulas, and genome sequence assembly using an Eulerian path method.
Simon Tavaré holds the George and Louise Kawamoto Chair in Biological Sciences and is a Professor of Biological Sciences, Mathematics, and Preventive Medicine at the University of Southern California. Professor Tavaré's research lies at the interface between statistics and biology, specifically focusing on problems arising in molecular biology, human genetics, population genetics, molecular evolution, and bioinformatics. His statistical interests focus on stochastic computation. Among the applications are linkage disequilibrium mapping, stem cell evolution, and inference in the fossil record. Dr. Tavaré is also a professor in the Department of Oncology at the University of Cambridge, England, where his group concentrates on cancer genomics.
Richard C. Deonier is Professor Emeritus in the Molecular and Computational Biology Section of the Department of Biological Sciences at the University of Southern California. Originally trained as a physical biochemist, His major research has been in areas of molecular genetics, with particular interests in physical methods for gene mapping, bacterial transposable elements, and conjugative plasmids. During 30 years of active teaching, he has taught chemistry, biology, and computational biology at both the undergraduate and graduate levels.
Customer Reviews:
"Computational genome analysis: An Introduction" Deonier R., Tavare S., Waterman M. Springer-Verlag New York, Inc., Secaucus, NJ.......2006-07-08
This textbook was based on the authors' instructional experiences in undergraduate Computational Biology courses for Bachelor seniors, first-year Master's, and Ph.D. students at the University of Southern California. Readers could also include investigators in medical schools, computer scientists, biologists, applied mathematicians, biochemists, and persons working in the biotechnology industry.
This text is based on the classic man-machine-work model in which a human performs laboratory-level work while also interacting with a digital computer. The complete inventory of all DNA that determines the identity of an organism is known as the genome. The computer or 'machine' utilizes the R language and produces statistical solutions dealing with genomes. The objects analyzed fall into these categories: the basic unit of life or the cell; the chemical energy stored in ATP (Adenosine triphosphate), the genetic information encoded by DNA (Deoxyribonucleic Acid) , and that information transcribed into RNA (Ribonucleic Acid). Since all life on the planet is based on cells, except for viruses, one can see why this volume is an important contribution to the scientific knowledge base particularly with reference to the evolution of species.
The R language developed at Bell Laboratories is used throughout the text. R is a probability statistics environment available for free download and can be used with Windows, Macintosh, and Linux operating systems. It functions very much like the S-PLUS statistics package. Since the reader would need to know how to actually implement the concepts in computational biology to fully understand them, the authors include examples of computations using R. This volume is described as a "roll up your sleeves and get dirty" introduction to the computational side of genomics and bioinformatics. It is intended to provide a foundation for an intelligent application of the available computational tools and for intellectual growth as new experimental approaches lead to new computational tools.
One must accept the fact that analyzing cells, DNA, and RNA is based on probability statistics. The text utilizes 1% algebra, 1 % integral calculus and 98% probability statistics --- the 98% being processed in R language. It isn't intended to describe the laboratory processes and protocols used to manipulate the samples but it does directly connect the computer solutions to the laboratory or work activity. Each chapter ends with a number of problems; while this is typical of the classical textbook, it would have been helpful if a teacher's answer book had been appended.
The Chapter headings are: Biology in a Nutshell; Words, Word Distributions and Occurences; Physical Mapping of DNA; Genome Rearrangements; Sequence Alignment; Rapid Alignment Methods: FASTA and BLAST; DNA Sequence Assembly; Signals in DNA; Similarity, Distance, and Clustering; Measuring Expression of Genome Information; Inferring the Past: Phylogenetic Trees; Genetic Variation in Populations; Comparative Geonomics; Glossary; A Brief Introduction to R; Internet Bioinformatics Resources; Miscellaneous Data.
Leonard C. Silvern
Systems Engineering Laboratories
Clarkdale, AZ
Customer Reviews:
Beyond the Central Dogma.......2007-07-08
This book is an exciting series of chapters which illustrate how far science has come from the discovery of the double helix structure and the triplet code which were thought to enable DNA to be read like a long string of text. Research discussed in the book indicates that there are levels of information encoded by genomes beyond the linear chain of bases, and hints that learning to interpret these additional levels of information will provide a wealth of insight into evolution, disease, and life itself.
This book is written in a technical style, the layperson might prefer Darwin In the Genome: Molecular Strategies in Biological Evolution
Average customer rating:
- Fascinating Book on a Totally New Concept
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Trading the Genome: Investigating the Commodification of Bio-Information
Bronwyn Parry
Manufacturer: Columbia University Press
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The Politics of Life Itself: Biomedicine, Power, and Subjectivity in the Twenty-First Century (In-formation)
ASIN: 0231121741 |
Book Description
Major changes in scientific, technological, and regulatory domains have fundamentally altered the way collected biological materials are used industrially. New technological artifacts are being created -- cell lines, cryogenically stored tissue samples, biochemical extracts, and even sequenced DNA stored on databases -- each of which contains highly sought after genetic and biochemical information. Able to be cloned, copied, synthesized and engineered, rented, downloaded, viewed, and exchanged, these bio-informational "proxies" may be transacted thousands of times in any given month or year. The result is an extremely lucrative, albeit largely invisible, resource economy in bio-information.
But who will benefit from this new trade? Many suppliers of the genetic and biochemical resources from which this information is drawn come from economically vulnerable developing countries. The Biodiversity Convention obliges signatory states to ensure that suppliers of genetic and biochemical resources receive "a just and equitable" share of the profits that accrue from the commercialization of their resources -- but it is not clear that they do. In a groundbreaking work that draws on anthropology, history, philosophy, business, and law, Bronwyn Parry links a firsthand investigation of the operation of the bioprospecting industry to a sophisticated analysis of broader economic, regulatory, and technological transformations: the rise of an information economy, global intellectual property rights and benefit-sharing regimes, and the progressive molecularization of approaches to biological research. Parry reveals how a failure to monitor this new global trade in bio-information could have potentially disastrous consequences for the suppliers of genetic and biochemical resources -- transforming the complex dynamics of collecting, as well as the politics and practice of biological resource exploitation.
Customer Reviews:
Fascinating Book on a Totally New Concept.......2005-04-19
Every once in a while a book come at you totally out of the blue. This is one.
Suppose you have a plant, corn let's say. Someone then delivers to you another variety of corn that has some valuable characteristic: resistance to disease, ability to grow with less water or in a salty soil. But the new corn doesn't produce as high a yield as the corn you have. You take this new variety, isolate the gene that provides this capability and merge it with your older variety to produce a new strain that combines the good features of both.
The Biodiversity Convention obliges a signatory state to ensure that suppliers of genetic and biochemical resources receive "a just and equitable" share of the profits that accrue from the comemrcialization of their resources.
To be absolutely fair and follow the law to the limit, how much do you owe to whom? What should the collector of the variety get? The owner of the property on which it is found? The country in which it is found? And oh yes, the United States is not a signatory nation to the convention.
This fascinating book opens a wide variety of questions, and in doing so explains a lot about biodiversity that I never knew.
Average customer rating:
- decent intro, but not comprehensive or very usable
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Bioinformatics in the Post-Genomic Era: Genome, Transcriptome, Proteome, and Information-Based Medicine
Jeff Augen
Manufacturer: Addison-Wesley Professional
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Your UNIX: The Ultimate Guide
ASIN: 0321173864 |
Customer Reviews:
decent intro, but not comprehensive or very usable .......2005-04-06
Bioinformatics is the science of biological information, namely sequences and metadata about organisms and sequences. What's interesting about this field to many people, both in the sciences and outside of it, is the large volume of data that gets analyzed and the results that emerge on a daily basis. Obviously interesting for the medical advances and the rapidly growing business in the life sciences, there's a complex field that has developed in the past ten years or so. And following the sequencing of the human genome, new challenges have arisen for everyone involved. Augen's Bioinformatics provides a good introduction to this new field of research for students in the sciences, and anyone with a decent undergraduate education in modern biology. I think that this accessibility of the material is one of the book's biggest winning points.
After an introduction to the book and the subject area of bioinformatics (chapters 1 and 2), Augen begins at the level of the structure of a gene (chapter 3). Here, anyone with an undergraduate level understanding of genetics or molecular biology can begin using the book and bridging the gap to the new areas of modern bioinformatics. Augen then describes how basic sequence analysis is performed at the DNA sequence level (in chapter 4). The material in Bioinformatics covers some of the higher-level methods for sequence analysis, including hidden Markov models, neural networks, and pattern discovery, and introduces some of the common algorithms found to do this analysis.
Chapter 5 then covers transcription, the process of going from DNA to mRNA. Beginning with the biology behind this activity (the ribosome and the larger "transcriptome"), Bioinformatics then describes how you would perform transcriptional analysis. Here, Augen shows how you go from a wet lab to a computational lab and describes what classes of experiments you perform to gather data and then what kinds of analysis you perform on it. This chapter introduces some of the more common clustering techniques for data aggregation and understanding.
The next step in the DNA -> RNA -> protein chain is found in chapter 6, which covers the translation process. Coupled to chapter 7, which describes protein structure prediction and searching, these two chapters bridge the next gap between laboratory data and computational analysis. Protein folding and structure analysis was one of my pet areas of study as a graduate student, and Augen's text does a decent summarization of the field to date. The resources listed and techniques described are definitely on par with the common practices in the field.
Finally, Bioinformatics gets into the next major area of bioinformatics, medical databases. Augen's bridge from genetics to medical science is complete, and he discusses how medical professionals utilize databases and can begin to predict disease, for example, based on data mining. The final chapter, "New Themes in Bioinformatics," covers exactly that, but also what Augen refers to as "workflow computing," or basically going about being a bioinformatics scientist. One of my favorite emerging areas in bioinformatics, metabolic pathway elucidation, is also covered briefly.
I've shared this book with a few friends who are all studying computer science or practicing computer scientists. I did so because Augen's material does a good job of explaining my background and introducing them to some of the analysis forms I introduce into my own work. It does a good job of that, and gets them quite excited. Bioinformatics really bridges a number of fascinating areas of computer sciences, including data mining and high performance algorithms. Augen's Bioinformatics is a good introduction to the field for them, and really anyone who has studied a couple of biology courses in college.
Where the book falls short, however, can be grouped into two main areas. The first is the failure of Augen's presentation of the algorithms. While the methods used to describe computational algorithms in Bioinformatics is common for non-computer scientists, it's completely unusable for computer scientists who are used to a specific algorithm presentation style that looks more like pseudocode than rambling text. The ambiguities this presents for a technical reader are unfortunate, especially if anyone studying bioinformatics is supposed to be computer science literate. The book itself assumes a life science literacy, so this isn't an unreasonable expectation of the reader.
The second area that consistently falls short in the book is in the utility of the information given. While I am significantly happier with the quality and depth of material presented in Augen's book than in the O'Reilly bioinformatics series, where the book fails to deliver is in showing the reader how to actually use the data they gather. After all, the book shows various sequence analysis algorithms and discusses tools available to do this work, but it only devotes a few pages (out of over 370 in total) to a workflow that can be used. Also, the book fails to point the reader at very worthwhile web resources sometimes, including meta sites like the SDSC Biology Workbench site, and just says "some Perl scripts" for local data analysis. As such, you'll have to go a few extra miles on your own to make use of the data sources.
I guess a third complaint of the book for me is that Augen has ignored or omitted significant bodies of research that fit squarely into the scope of the book. For example, Ken Dill's research into protein folding models, as well as Martin Karplus' work on the subject, receives no mention, nor does the topic of Bayesian network analysis when Augen discusses time series data analysis. These aren't new, they've been around for many years and influenced most of the field, and their absence is noted. The book's spotty coverage in some places, like these, is noticeable.
Bioinformatics does a few things well, but overall reads too much like a biology textbook to be useful to the average computer scientist. More emphasis on the practice of bioinformatics and data analysis would have made this book stronger and complemented the substantive background material well. Finally, using an approach more similar to the computer science approach would have been a tremendous benefit, since the material really is computer science in part. That said, I think this is probably the best introduction to this exciting area of science that I have yet seen.
Book Description
In the age of global biotechnology, DNA can exist as biological material in a test tube, as a sequence in a computer database, and as economically valuable information in a patent. In The Global Genome, Eugene Thacker asks us to consider the relationship of these three entities and argues that -- by their existence and their interrelationships -- they are fundamentally redefining the notion of biological "life itself."
Biological science and the biotech industry are increasingly organized at a global level, in large part because of the use of the Internet in exchanging biological data. International genome sequencing efforts, genomic databases, the development of World Intellectual Property policies, and the "borderless" business of biotech are all evidence of the global intersections of biology and informatics -- of genetic codes and computer codes. Thacker points out the internal tension in the very concept of biotechnology: the products are more "tech" than "bio," but the technology itself is fully biological, composed of the biomaterial labor of genes, proteins, cells, and tissues. Is biotechnology a technology at all, he asks, or is it a notion of "life itself" that is inseparable from its use in the biotech industry?
The three sections of the book cover the three primary activities of biotechnology today: the encoding of biological materials into digital form -- as in bioinformatics and genomics; its recoding in various ways -- including the "biocolonialism" of mapping genetically isolated ethnic populations and the newly pervasive concern over "biological security"; and its decoding back into biological materiality -- as in tissue engineering and regenerative medicine. Thacker moves easily from science to philosophy to political economics, enlivening his account with ideas from such thinkers as Georges Bataille, Georges Canguilhem, Michel Foucault, Antonio Negri, and Paul Virilio. The "global genome," says Thacker, makes it impossible to consider biotechnology without the context of globalism.
Customer Reviews:
DNA=channel .......2006-02-05
"Eugene Thacker send back out the DNA=channel that turned on the industrial ill-treatment of a chemical=anthropoid era respiration-byte." - Kenji Siratori, author of Blood Electric
Average customer rating:
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Bioinformatics of Genome Regulation and Structure II
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ASIN: 0387294503 |
Book Description
This work is a follow-up of the International Conference on Bioinformatics of Genome Regulation and Structure (BGRS-2004), held in Novosibirsk, Russia, in July 2004. It comprises the newest results obtained while researching into the structure and function of molecular genetic systems belonging to different complexity level of their organization. The material covers the following: (i) regulatory genomic sequences; (ii) large-scale genome analysis and functional annotation; (iii) gene structure detection and prediction; (iv) comparative and evolutionary genomics; (v) computer analysis of genome polymorphism and evolution; computer analysis and modeling of transcription, splicing, and translation; structural computational biology; (vi) gene networks, signal transduction pathways, and genetically controlled metabolic pathways; (vii) data warehousing, knowledge discovery and data mining; and (viii) analysis of basic patterns of genome operation, organization, and evolution.
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- Biology (Cliffs AP) 2nd Edition
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- Biology: Concepts & Connections with Student CD-ROM (5th Edition)
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- Biology, Sixth Edition
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