Systems biology and bioinformatics: a computational approach
CRC Press, 2009/04/08 - 166 ページ
The availability of molecular imaging and measurement systems enables today's biologists to swiftly monitor thousands of genes involved in a host of diseases, a critical factor in specialized drug development. Systems Biology and Bioinformatics: A Computational Approach provides students with a comprehensive collection of the computational methods used in what is being coined the digital eraof biology. Written by field experts with proven track records, this authoritative textbook first provides an introduction to systems biology and its impact on biology and medicine. The book then reviews the basic principles of molecular and cell biology using a system-oriented approach, with a brief description of the high-throughput biological experiments that produce databases. The text includes techniques to discover genes, perform nucleotide and amino acid sequence matching, and estimate static gene dynamic pathways. The book also explains how to use system-oriented models to predict the behavior of biological systems for important applications such as rational drug design. The numerous examples and problem sets allow students to confidently explore practical systems biology applications using real examples with real biological data, making Systems Biology and Bioinformatics: A Computational Approachan ideal text for senior undergraduate and first-year graduate students.
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algorithm allows amino acids analysis analyzed applications approach ARX model Bayesian networks bind bioinformatics biological systems biomedical BLOSUM calculated cell cycle chapter chromosomes clustering codons coefficients computing correlation data set described distribution DNA microarray DNA sequence drug dynamic programming effect encoding Equation estimate expression level factors FASTA function Gal3 Gal4 Gal6 galactose galactose pathway Gaussian gene expression gene networks gene regulatory network gene silencing gene-protein genetic genome identify knockout experiments large number linear markers Mason's rule matches matrix membrane methods microarray data molecular molecules mRNA nonlinear nucleotide nucleotide sequence observations Ontology optimal output pair parameters perturbation phenotypes predict problem produce protein folding protein sequence protein structure proteomics query sequence random regions regulatee residues ribosome Rosetta@Home sample score secondary structures sequence alignment signal similarity simulation specific statistical step stochastic process strand systems biology target theory tion UniProt variables