Bioinformatics

From the reviews: "In general, this book describes some of the most useful and widely used techniques in the field of bioinformatics. ... it covers a wide variety of topics to satisfy the large audience involved in using and developing bioinformatics. ... These will be of extreme importance to those involved in utilization and development of bioinformatics methods. The book is written for students and beginning level bioinformatics researchers. ... This is a good reference in the field of bioinformatics, particularly for those who are just starting out." (Basabi Rana, Doody's Review Service, September, 2008) "Bioinformatics is presented ... with a total of 51 chapters. ... successfully cover the wide field of bioinformatics, providing many useful methods, the majority of which are accessible to the non-specialist. ... will serve as a valuable reference and therefore may be most appropriate as an institutional purchase." (Conrad Nieduszynski, Microbiology Today, February, 2009) "Volume II contains 25 chapters that cover computational approaches and theory in analyzing function and structure of protein and nucleic acid sequences. ... give relatively in-depth coverage of many concepts that are applied by bioinformatics specialists. ... Many of the chapters are example driven, with basic forays into bioinformatics analyses that will educate readers in both the theory and practical matter of running the analyses." (Jason E. Stajich, The Quarterly Review of Biology, Vol. 84, September, 2009) "This volume emphasizes protein analysis and function recognition. ... In summary, this book presents a number of bioinformatics tools and methods, ranging from protein structure prediction, to gene function inference, to microarray data profiling. ... The book is very suitable for entry-level bioinformaticians and clinical researchers." (Hsun-Hsien Chang, ACM Computing Reviews, August, 2009)

• Structures.- UNAFold.- Protein Structure Prediction.- An Introduction to Protein Contact Prediction.- Analysis of Mass Spectrometry Data in Proteomics.- The Classification of Protein Domains.- Inferring Function.- Inferring Function from Homology.- The Rosetta Stone Method.- Inferring Functional Relationships from Conservation of Gene Order.- Phylogenetic Profiling.- Phylogenetic Shadowing.- Prediction of Regulatory Elements.- Expression and Microarrays.- Identifying Components of Complexes.- Integrating Functional Genomics Data.- Applications and Disease.- Computational Diagnostics with Gene Expression Profiles.- Analysis of Quantitative Trait Loci.- Molecular Similarity Concepts and Search Calculations.- Optimization of the MAD Algorithm for Virtual Screening.- Combinatorial Optimization Models for Finding Genetic Signatures from Gene Expression Datasets.- Genetic Signatures for a Rodent Model of Parkinson's Disease Using Combinatorial Optimization Methods.- Analytical and Computational Methods.- Developing Fixed-Parameter Algorithms to Solve Combinatorially Explosive Biological Problems.- Clustering.- Visualization.- Constructing Computational Pipelines.- Text Mining.