Python for Biologists | Learning Perl | Programming Perl | Bioinformatics Data Skills | Advanced Python for Biologists | Beginning Perl for Bioinformatics | Building Bioinformatics Solutions | Developing Bioinformatics Computer Skills | Bioinformatics Programming Using Python
Historically, programming hasn't been considered a critical skill for biologists. But now, with access to vast amounts of biological data contained in public databases, programming skills are increasingly in strong demand in biology research and development. Perl, with its highly developed capacities in string handling, text processing, networking, and rapid prototyping, has emerged as the programming language of choice for biological data analysis.Mastering Perl for Bioinformatics covers the core Perl language and many of its module extensions, presenting them in the context of biological data and problems of pressing interest to the biological community. This book, along with Beginning Perl for Bioinformatics, forms a basic course in Perl programming. This second volume finishes the basic Perl tutorial material (references, complex data structures, object-oriented programming, use of modules--all presented in a biological context) and presents some advanced topics of considerable interest in bioinformatics.The range of topics covered in Mastering Perl for Bioinformatics prepares the reader for enduring and emerging developments in critical areas of bioinformatics programming such as:
- Gene finding
- String alignment
- Methods of data storage and retrieval (SML and databases)
- Modeling of networks (graphs and Petri nets)
- Graphics (Tk)
- Interfacing with other programming languages
- Statistics (PDL)
- Protein structure determination
- Biological models of computation (DNA Computers)
About: A companion volume to Beginning Perl for Bioinformatics discusses the ties between biology and computer science and covers core PERL programming concepts, module extensions, and more advanced Perl techniques, data structures, object-oriented programming, and more in relation to biological data and other specific biological applications.
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