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Introduction to Computational Biology
An Evolutionary Approach
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This Introduction to Bioinformatics is motivated by the biology of genomics. Starting from a description of the Drosophila genome project, the authors explain the computational and conceptional background to the analysis of large-scale sequence data. Many of the corresponding analysis methods are rooted in evolutionary thinking, which serves as a common thread throughout the book.
The focus is on methods of comparative genomics and subjects such as alignments, gene finding, phylogeny, and the analysis of single nucleotide polymorphisms (SNPs) are treated. Especially the latter topic is closely integrated with ideas from evolutionary biology, including coalescent theory.
The volume contains exercises, questions & answers to selected problems, and a CD-ROM with software to visualize some of the central algorithms covered.
The book is of interest to advanced undergraduate and graduate students as well as to researchers in the fields of bioinformatics, molecular & evolutionary biology, and biomathematics.
The focus is on methods of comparative genomics and subjects such as alignments, gene finding, phylogeny, and the analysis of single nucleotide polymorphisms (SNPs) are treated. Especially the latter topic is closely integrated with ideas from evolutionary biology, including coalescent theory.
The volume contains exercises, questions & answers to selected problems, and a CD-ROM with software to visualize some of the central algorithms covered.
The book is of interest to advanced undergraduate and graduate students as well as to researchers in the fields of bioinformatics, molecular & evolutionary biology, and biomathematics.
Analysis of molecular sequence data is the main subject of this introduction to computational biology. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space in evolutionary time. Accordingly, the first part of the book deals with classical methods of sequence analysis: pairwise alignment, exact string matching, multiple alignment, and hidden Markov models. In the second part evolutionary time takes center stage and phylogenetic reconstruction, the analysis of sequence variation, and the dynamics of genes in populations are explained in detail. In addition, the book contains a computer program with a graphical user interface that allows the reader to experiment with a number of key concepts developed by the authors.
This textbook is intended for students enrolled in courses in computational biology or bioinformatics as well as for molecular biologists, mathematicians, and computer scientists.
This textbook is intended for students enrolled in courses in computational biology or bioinformatics as well as for molecular biologists, mathematicians, and computer scientists.