Evolutionary Bioinformatics

✍ Donald R. Forsdyke 📂 Library 📅 2006 🏛 Springer 🌐 English

<P>Books on bioinformatics which began appearing in the mid 80s primarily served gene-hunters, and biologists who wished to construct family trees showing tidy lines of descent. Given the great pharmaceutical industry interest in genes, this trend has continued in most subsequent texts. These deal e

📁 Evolutionary Bioinformatics

✍ Donald R. Forsdyke (auth.) 📂 Library 📅 2011 🏛 Springer-Verlag New York 🌐 English

<p>Evolutionary Bioinformatics aims to make the "new" information-based (rather than gene-based) bioinformatics intelligible both to the "bio" people and the "info" people. Books on bioinformatics have traditionally served gene-hunters, and biologists who wish to construct family trees showing tidy

Evolutionary Bioinformatics

📁 Evolutionary Bioinformatics

✍ Forsdyke, Donald R 📂 Library 📅 2016;2018 🏛 Springer International Publishing 🌐 English

Evolutionary Bioinformatics

📁 Evolutionary Bioinformatics

✍ Donald R. Forsdyke (auth.) 📂 Library 📅 2016 🏛 Springer International Publishing 🌐 English

<p><p>Now in its third edition and supplemented with more online material, this book aims to make the "new" information-based (rather than gene-based) bioinformatics intelligible both to the "bio" people and the "info" people. Books on bioinformatics have traditionally served gene-hunters, and biolo

Evolutionary Computation in Bioinformati

📁 Evolutionary Computation in Bioinformatics

✍ Gary B. Fogel, David W. Corne 📂 Library 📅 2002 🏛 Morgan Kaufmann 🌐 English

Bioinformatics has never been as popular as it is today. The genomics revolution is generating so much data in such rapid succession that it has become difficult for biologists to decipher. In particular, there are many problems in biology that are too large to solve with standard methods. Researche

Evolutionary Computation in Bioinformati

📁 Evolutionary Computation in Bioinformatics

✍ Fogel G.B., Corne D.W. 📂 Library 📅 2002 🏛 Morgan Kaufmann 🌐 English

Bioinformatics has never been as popular as it is today. The genomics revolution is generating so much data in such rapid succession that it has become difficult for biologists to decipher. In particular, there are many problems in biology that are too large to solve with standard methods. Researche

Evolutionary Bioinformatics

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