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21. Bioinformatics: Tools and Applications | |
Hardcover: 451
Pages
(2009-09-22)
list price: US$89.95 -- used & new: US$66.97 (price subject to change: see help) Asin: 0387927379 Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description Bioinformatics is a relatively new field of research. It evolved from the requirement to process, characterize, and apply the information being produced by DNA sequencing technology. The production of DNA sequence data continues to grow exponentially. At the same time, improved bioinformatics such as faster DNA sequence search methods have been combined with increasingly powerful computer systems to process this information. Methods are being developed for the ever more detailed quantification of gene expression, providing an insight into the function of the newly discovered genes, while molecular genetic tools provide a link between these genes and heritable traits. Genetic tests are now available to determine the likelihood of suffering specific ailments and can predict how plant cultivars may respond to the environment. The steps in the translation of the genetic blueprint to the observed phenotype is being increasingly understood through proteome, metabolome and phenome analysis, all underpinned by advances in bioinformatics. Bioinformatics is becoming increasingly central to the study of biology, and a day at a computer can often save a year or more in the laboratory. The volume is intended for graduate-level biology students as well as researchers who wish to gain a better understanding of applied bioinformatics and who wish to use bioinformatics technologies to assist in their research. The volume would also be of value to bioinformatics developers, particularly those from a computing background, who would like to understand the application of computational tools for biological research. Each chapter would include a comprehensive introduction giving an overview of the fundamentals, aimed at introducing graduate students and researchers from diverse backgrounds to the field and bring them up-to-date on the current state of knowledge. To accommodate the broad range of topics in applied bioinformatics, chapters have been grouped into themes: gene and genome analysis, molecular genetic analysis, gene expression analysis, protein and proteome analysis, metabolome analysis, phenome data analysis, literature mining and bioinformatics tool development. Each chapter and theme provides an introduction to the biology behind the data describes the requirements for data processing and details some of the methods applied to the data to enhance biological understanding. |
22. MicroRNA Profiling in Cancer: A Bioinformatics Perspective | |
Hardcover: 300
Pages
(2009-10-01)
list price: US$129.00 -- used & new: US$87.07 (price subject to change: see help) Asin: 9814267015 Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description |
23. Machine Learning Approaches to Bioinformatics (Science, Engineering, and Biology Informatics) by Zheng Rong Yang | |
Hardcover: 336
Pages
(2010-05-06)
list price: US$107.00 -- used & new: US$85.51 (price subject to change: see help) Asin: 981428730X Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description Unlike most of the bioinformatics books on the market, the content coverage is not limited to just one subject. A broad spectrum of relevant topics in bioinformatics including systematic data mining and computational systems biology researches are brought together in this book, thereby offering an efficient and convenient platform for teaching purposes. An essential reference for both final year undergraduates and graduate students in universities, as well as a comprehensive handbook for new researchers, this book will also serve as a practical guide for software development in relevant bioinformatics projects. |
24. Introduction to Mathematical Methods in Bioinformatics (Universitext) by Alexander Isaev | |
Paperback: 298
Pages
(2004-06-02)
list price: US$74.95 -- used & new: US$51.82 (price subject to change: see help) Asin: 3540219730 Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description This book looks at the mathematical foundations of the models which is crucial for correct interpretation of the outputs of the models. A bioinformatician should be able not only use software packages, but also know the mathematics behind these packages. From this point of view, mathematics departments throughout the world have a major role to play in bioinformatics education by teaching courses on the mathematical foundations of bioinformatics. The author wrote this book based on his lecture notes for his courses. It combines several topics in biological sequence analysis with mathematical and statistical material required for such analysis. |
25. Discovering Genomics, Proteomics and Bioinformatics (2nd Edition) by A. Malcolm Campbell, Laurie J. Heyer | |
Paperback: 464
Pages
(2006-03-12)
list price: US$115.00 -- used & new: US$66.50 (price subject to change: see help) Asin: 0805382194 Average Customer Review: Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description KEY BENEFIT: Discovering Genomics is the first genomics text that combines web activities and case studies with a problem-solving approach to teach upper-level undergraduates and first-year graduate students the fundamentals of genomic analysis. More of a workbook than a traditional text, Discovering Genomics, Second Edition allows students to work with real genomic data in solving problems and provides the user with an active learning experience. KEY TOPICS: Genomic Medicine Case Study: What’s wrong with my child? Genome Sequence Acquisition and Analysis, Comparative Genomics in Evolution and Medicine, Genome Variations, Genomic Medicine Case Study: Why Can’t I Just Take a Pill to Lose Weight? Basic Research with DNA Microarrays, Applied Research with DNA Microarrays, Proteomics, Genomic Medicine Case Study: Why Can’t We Cure More Diseases? Genomic Circuits in Single Genes, Integrated Genomic Circuits, Modeling Whole-Genome Circuits. MARKET: For all readers interested in genomics. Customer Reviews (7)
Good!
Genomics, Proteomics, and Bioinformatics textbook
Convoluted layout, authors stray off topic, web links and problem sets are outdated
Textbook + website =great new textbook
Great New Format to get students out of a dull book |
26. Instant Notes in Bioinformatics by Charlie Hodgman, Andrew French, David Westhead | |
Paperback: 300
Pages
(2009-09-24)
list price: US$40.00 -- used & new: US$29.07 (price subject to change: see help) Asin: 0415394945 Average Customer Review: Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description The second edition of Instant Notes in Bioinformatics introduced the readers to the themes and terminology of bioinformatics. It is divided into three parts: the first being an introduction to bioinformatics in biology; the second covering the physical, mathematical, statistical and computational basis of bioinformatics, using biological examples wherever possible; the third describing applications, giving specific detail and including data standards. The applications covered are sequence analysis and annotation, transcriptomics, proteomics, metabolite study, supramolecular organization, systems biology and the integration of-omic data, physiology, image analysis, and text analysis. Customer Reviews (1)
Concise primer. Not bad. Compared to other primers such as "Developing Bioinformatics Computer Skills", this book contains less unnecessasary figures (e.g., central dogma, etc.), covers wider range of topics, tries to be less verbose. A drawback is that there is little description at an algorithmic level (e.g., dynamic programming). However, the book does a pretty good job in conveying the main ideas about what such algorithms do and why they are needed. I like this book's concise and accurate presentation style much better than lengthy and confusing style found in many other books (e.g., Bioinformatics - David Mount). Another drawback is that font is small. Overall, this book is not bad. I think this book's preface tells you what you can expect from this book, so below I excerpted a paragraph. "We will tell you how to do things, but this is not a software manual for commonly used packages. They have their own manuals that are (mostly) much better than anything we could provide. Many of the methods we describe rely on quite complex mathematical, statistical or computational techniques. Often we choose not to describe these at all, but where we do we have aimed for a simple conceptual understanding." ... Read more |
27. Probabilistic Methods for Bioinformatics: with an Introduction to Bayesian Networks by Richard E. Neapolitan | |
Hardcover: 424
Pages
(2009-04-17)
list price: US$69.95 -- used & new: US$51.95 (price subject to change: see help) Asin: 0123704766 Average Customer Review: Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis. Customer Reviews (1)
Lots of examples |
28. Exploring Genomes: Web Based Bioinformatics Tutorials by William M. Gelbart, Richard C. Lewontin, Jeffrey H. Miller, Paul Young | |
Paperback: 51
Pages
(2007-03-23)
-- used & new: US$19.20 (price subject to change: see help) Asin: 1429201789 Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description |
29. Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health) by Warren J. Ewens, Gregory R. Grant | |
Paperback: 588
Pages
(2010-11-02)
list price: US$115.00 -- used & new: US$91.73 (price subject to change: see help) Asin: 1441923020 Average Customer Review: Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science. Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999. Comments on the first edition: "This book would be an ideal text for a postgraduate course…[and] is equally well suited to individual study…. I would recommend the book highly." (Biometrics) "Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces." (Naturwissenschaften) "The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details." (Journal American Statistical Association) "The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book." (Metrika) Customer Reviews (7)
modern bioinformatics
Misleading title!
Great all-around review of probability
Disappointing overview A topic such as the two-sample t-statistic is scattered throughout the book, with the main part not even cited in the index! Unfortunately there are not a lot of books in the field of Statistics in Bioinformatics. However, I would recommend "The Elements of Statistical Learning" (Hastie et al.) for classifiers etc (Duda and Hart's classic is also good). I would recommend "Biostatistical Analysis" by Zar for a general coverage, and Terry Speed's "stat Labs: Mathematical Statistics ..." which is not comprehensive but has good lab examples with associated statistical analysis.
Pretty good overview Chapter one begins, appropriately, with an introduction to probability theory, with a consideration of discrete probability distributions of one variable beginning the chapter. The Bernoulli, binomial, uniform, geometric, generalized geometric, and Poisson distributions are discussed. The authors point out the use of geometric-like distributions in the BLAST application. The also caution the reader as to the difference between the mean and the average of a random variable. They then move on to consider continuous distributions, discussing briefly the uniform, Normal, exponential, gamma, and beta distributions. Moment-generating functions are also introduced, and they prove a "convexity" theorem for these functions that is important in the BLAST application. The authors also introduce the relative entropy and generalized support statistics, the later also being used in BLAST. The next chapter is an overview of probability theory in many random variables. The results in chapter one are discussed in this context, and the authors give an interesting application to the sequencing of EST libraries. The authors also point out that the variance of the maximum of a collection random variables is finite as the number of variables increases, a fact that is used quite often in bioinformatics. Transformations of random variables are also discussed, with the goal of showing how these can be used to find the density function of a single random variable, this also being important in BLAST. The most important subject of the book begins in chapter 3, wherein the authors introduce statistical inference. They begin with a very brief discussion of the differences between the frequentist and Bayesian approaches to statistical inference and then move on to classical hypothesis testing and nonparametric tests. This chapter is of great value to those readers, for example biologists/would-be bioinformaticists who are approaching statistics for the first time. Chapter 4 introduces concepts that are of upmost importance in probabilistic computational biology, namely Markov chains. The discussion in this chapter sets up the strategies used in the next chapter on analyzing a single DNA sequence and a latter chapter on hidden Markov models. Shotgun sequencing is discussed as a tool to determine the an actual DNA sequence, and the authors discuss the probabilistic issues that arise in the reconstruction of long DNA sequences from shorter sequences. Missing in this chapter is a mathematical analysis of the advantages/disadvantages between shotgun and whole genome sequencing strategies. Chapter 6 then generalizes the analysis of chapter 5 to multiple DNA and protein sequences. It is here that one begins to talk about alignments between sequences, which bring about some very subtle mathematical problems in computational biology. The computational complexity of the (global) alignment problem entails the use of softer techniques, such as dynamic programming, which is discussed in this chapter. The (local) alignment problem is also discussed in some detail, using the linear gap model. The alignment problem and the issues with scoring for protein sequences are also discussed in detail. The reader first encounters the famous PAM and BLOSUM matrices in this chapter. The authors do not discuss any connections with the protein folding problem, unfortunately. The next chapter introduces the basic probability theory behind the BLAST algorithm, namely random walks. They do so with emphasis on moment generating functions, which might be a little abstract for the biologist reader. The authors return to tatistical estimation and hypothesis testing in chapter 8, with maximum liklihood and fixed sample size tests discussed in some detail. Again connecting with the BLAST algorithm, the sequential probability ratio test is treated. The authors finally get down to the BLAST algorithm in chapter 9, using an older version of the software (1.4). The connection of the algorithm with random walks and how to assign scores is immediately apparent, as is the ability of BLAST to do database queries against a chosen sequence. The algorithm is compared with the sequential analysis discussed in the last chapter. The authors return to Markov chains in chapter 10, and give some numerical examples. In addition, they treat the important topic of Markov chain Monte Carlo via the Hastings-Metropolis algorithm, Gibbs sampling, and simulated annealing. An application of simulated annealing to the double digest problem is described. The authors also spend a litte time discussing continuous-time Markov chains. Hidden Markov models are finally discussed in chapter 11. These have been the most effective tools in sequence analysis and the authors give a nice overview of their construction and properties in this chapter. The Pfam package is discussed as a software implementation of HMMs for determining protein domains. Unfortunately, they do not discuss the excellent package HMMER for implementing HMMs in sequence analysis. Chapter 12 discusses computationally intensive methods in classical inference. One of these methods, the bootstrap procedure, which is used for large sample sizes, is described. Used to estimate confidence intervals in situations where there is not enough information to employ classical methods, the authors detail a method using quantiles to estimate the confidence interval for the standard deviation of the expression intensity of a gene. This is followed by a return to the multiple testing problem of chapter 3 in the context of the data analysis of expression arrays. I did not read the last two chapters on evolutionary models and phylogenetic tree estimation so I will omit their review. ... Read more |
30. Introduction to Bioinformatics: A Theoretical and Practical Approach | |
Paperback: 760
Pages
(2003-04-01)
list price: US$104.00 -- used & new: US$7.66 (price subject to change: see help) Asin: 158829241X Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description |
31. Python for Bioinformatics (Chapman & Hall/CRC Mathematical & Computational Biology) by Sebastian Bassi | |
Paperback: 587
Pages
(2009-09-30)
list price: US$69.95 -- used & new: US$57.94 (price subject to change: see help) Asin: 1584889292 Average Customer Review: Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description Programming knowledge is often necessary for finding a solution to a biological problem. Based on the author’s experience working for an agricultural biotechnology company, Python for Bioinformatics helps scientists solve their biological problems by helping them understand the basics of programming. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language. The book begins with a very basic introduction that teaches the principles of programming. It then introduces the Biopython package, which can be useful in solving life science problems. The next section covers sophisticated tools for bioinformatics, including relational database management systems and XML. The last part illustrates applications with source code, such as sequence manipulation, filtering vector contamination, calculating DNA melting temperature, parsing a genbank file, inferring splicing sites, and more. The appendices provide a wealth of supplementary information, including instructions for installing Python and Biopython and a Python language and style guide. By incorporating examples in biology as well as code fragments throughout, the author places a special emphasis on practice, encouraging readers to experiment with the code. He shows how to use Python and the Biopython package for building web applications, genomic annotation, data manipulation, and countless other applications. Customer Reviews (1)
Valuable resource |
32. Bioinformatics: An Introduction (Computational Biology) by Jeremy Ramsden | |
Hardcover: 272
Pages
(2009-04-14)
list price: US$69.95 -- used & new: US$39.49 (price subject to change: see help) Asin: 1848002564 Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description Bioinformatics is interpreted as the application of information science to biology, in which it plays a fundamental and all-pervasive role. The field continues to develop intensively in both academia and commercially, and is highly interdisciplinary. This broad-ranging and thoroughly updated second edition covers new findings while retaining the successful formula of the original text. Bioinformatics: An Introduction is structured into three parts devoted to Information, Biology, and Applications. Every section of the book has been completely revised for currency, and expanded where relevant, to take account of significant new discoveries and realizations of the importance of key concepts. Furthermore, two new chapters provide instruction about algorithms and knowledge representation. Emphases are placed on the underlying fundamentals and on acquisition of a broad and comprehensive grasp of the field as a whole. Features: • Provides a solid foundation in, and self-contained introduction to, the field of bioinformatics and its state-of-the-art as it relates to computational biology research • Imparts a thorough grounding of core concepts, enabling the reader to understand contemporary work within an optimal context • Includes examples, definitions, problems and a comprehensive and useful bibliography • Offers additional chapters on algorithms and knowledge representation, including text mining [NEW] • Presents new experimental methods, and serves as a springboard for new research [NEW] • Contains a greatly expanded chapter on interactions and regulatory networks [NEW] • Incorporates discussion of the method of drawing inferences from abstract sequence analysis based on frequency dictionaries • Contains an extensively revised chapter on medical applications [NEW] • Emphasizes the underlying fundamentals and acquisition of a broad and comprehensive grasp of the field as a whole This significantly improved second edition of a successful textbook is intended to be a complete study companion for the advanced undergraduate or graduate student. It is self-contained, bringing together the multiple disciplines necessary for a profound grasp of the field into a coherent whole, thereby allowing the reader to gain much insight into the state-of-the-art of bioinformatics. |
33. Essential Bioinformatics by Jin Xiong | |
Paperback: 352
Pages
(2006-03-13)
list price: US$70.00 -- used & new: US$46.34 (price subject to change: see help) Asin: 0521600820 Average Customer Review: Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description Customer Reviews (5)
amazone great!
Very simple
Good bookfor beginners
Essential Bioinformatics for Life Scientists.
Good Introductory Book for the Student or Researcher |
34. Digital Code of Life: How Bioinformatics is Revolutionizing Science, Medicine, and Business by Glyn Moody | |
Hardcover: 400
Pages
(2004-02-03)
list price: US$52.50 -- used & new: US$2.90 (price subject to change: see help) Asin: 0471327883 Average Customer Review: Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description "The man who wrote the best history yet of the open-source movement in Rebel Code gives us an equally lucid and penetrating look at bioinformatics. Well done!" "This book provides a riveting account of the history of bioinformatics and of the manner in which bioinformatics has contributed to advancing our knowledge of the human genome. Glyn Moody has chronicled through reviews of key scientific papers and through interviews with leading scientists, the major developments in the field of genomics in the past half century, from the discovery of the double helix to the emergence of proteomics, pointing to their relevance to science, medicine, and industry and to the critical contributions of bioinformatics." Customer Reviews (3)
Worth Reading
A delightful reading
Excellent Laymen's overview |
35. Introduction to Machine Learning and Bioinformatics (Chapman & Hall/CRC Computer Science & Data Analysis) by Sushmita Mitra, Sujay Datta, Theodore Perkins, George Michailidis | |
Hardcover: 384
Pages
(2008-06-05)
list price: US$81.95 -- used & new: US$50.00 (price subject to change: see help) Asin: 158488682X Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other. Examines Connections between Machine Learning & Bioinformatics The book begins with a brief historical overview of the technological developments in biology. It then describes the main problems in bioinformatics and the fundamental concepts and algorithms of machine learning. After forming this foundation, the authors explore how machine learning techniques apply to bioinformatics problems, such as electron density map interpretation, biclustering, DNA sequence analysis, and tumor classification. They also include exercises at the end of some chapters and offer supplementary materials on their website. Explores How Machine Learning Techniques Can Help Solve Bioinformatics Problems Shedding light on aspects of both machine learning and bioinformatics, this text shows how the innovative tools and techniques of machine learning help extract knowledge from the deluge of information produced by today’s biological experiments. |
36. Machine Learning in Bioinformatics (Wiley Series in Bioinformatics) by Yanqing Zhang, Jagath C. Rajapakse | |
Hardcover: 456
Pages
(2008-12-03)
list price: US$112.00 -- used & new: US$56.69 (price subject to change: see help) Asin: 0470116625 Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. From an internationally recognized panel of prominent researchers in the field, Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics. Coverage includes: feature selection for genomic and proteomic data mining; comparing variable selection methods in gene selection and classification of microarray data; fuzzy gene mining; sequence-based prediction of residue-level properties in proteins; probabilistic methods for long-range features in biosequences; and much more. Machine Learning in Bioinformatics is an indispensable resource for computer scientists, engineers, biologists, mathematicians, researchers, clinicians, physicians, and medical informaticists. It is also a valuable reference text for computer science, engineering, and biology courses at the upper undergraduate and graduate levels. |
37. Applied Bioinformatics: An Introduction by Paul Maria Selzer, Richard Marhöfer, Andreas Rohwer | |
Paperback: 288
Pages
(2008-02-06)
list price: US$49.95 -- used & new: US$22.02 (price subject to change: see help) Asin: 354072799X Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description Confused by cryptic computer programs, algorithms and formulae? In this book, anyone who can operate a PC, standard software and the Internet will learn to understand the biological basis of bioinformatics of the existence as well as the source and availability of bioinformatics software how to apply these tools and interpret results with confidence. This is aided by introductory chapters to important aspects of bioinformatics, detailed bioinformatics exercises, including solutions and a glossary of definitions and terminology relating to bioinformatics. Quickly learn to manage bioinformatics! |
38. Computational Intelligence and Pattern Analysis in Biology Informatics (Wiley Series in Bioinformatics) by Ujjwal Maulik, Sanghamitra Bandyopadhyay, Jason T. Wang | |
Hardcover: 400
Pages
(2010-11-16)
list price: US$110.00 -- used & new: US$97.14 (price subject to change: see help) Asin: 047058159X Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques, either individually or in a hybridized manner. The purpose is to analyze biological data and enable extraction of more meaningful information and insight from it. Biological data for analysis include sequence data, secondary and tertiary structure data, and microarray data. These data types are complex and advanced methods are required, including the use of domain-specific knowledge for reducing search space, dealing with uncertainty, partial truth and imprecision, efficient linear and/or sub-linear scalability, incremental approaches to knowledge discovery, and increased level and intelligence of interactivity with human experts and decision makers |
39. Exploring Bioinformatics: A Project-Based Approach by Caroline St. Clair, Jonathan E Visick | |
Paperback: 376
Pages
(2009-02-16)
list price: US$102.95 -- used & new: US$49.10 (price subject to change: see help) Asin: 0763758299 Average Customer Review: Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description Customer Reviews (1)
Not worth the price |
40. Biomolecular Networks: Methods and Applications in Systems Biology (Wiley Series in Bioinformatics) by Luonan Chen, Rui-Sheng Wang, Xiang-Sun Zhang | |
Hardcover: 391
Pages
(2009-07-20)
list price: US$105.00 -- used & new: US$81.00 (price subject to change: see help) Asin: 0470243732 Canada | United Kingdom | Germany | France | Japan | |
Editorial Review Product Description With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's form and function. This book addresses the important need for a new set of computational tools to reveal essential biological mechanisms from a systems biology approach. Readers will get comprehensive coverage of analyzing biomolecular networks in cellular systems based on available experimental data with an emphasis on the aspects of network, system, integration, and engineering. Each topic is treated in depth with specific biological problems and novel computational methods: GENE NETWORKS—Transcriptional regulation; reconstruction of gene regulatory networks; and inference of transcriptional regulatory networks PROTEIN INTERACTION NETWORKS—Prediction of protein-protein interactions; topological structure of biomolecular networks; alignment of biomolecular networks; and network-based prediction of protein function METABOLIC NETWORKS AND SIGNALING NETWORKS—Analysis, reconstruction, and applications of metabolic networks; modeling and inference of signaling networks; and other topics and new trends In addition to theoretical results and methods, many computational software tools are referenced and available from the authors' Web sites. Biomolecular Networks is an indispensable reference for researchers and graduate students in bioinformatics, computational biology, systems biology, computer science, and applied mathematics. |
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