Featured Categories : Study Books : Undergraduate & Postgraduate : Sciences : Biology : Computational Biology

• Home
• US Store
• Electronics
• Computers
• Sitemap

Featured Categories : Study Books : Undergraduate & Postgraduate : Sciences : Biology : Computational Biology

• Bioinformatics for Dummies (For Dummies)

  Claverie, JeanMichel Ph. D., Notredame, Cedric Ph.D.

  
  
   

• Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems

  P Dayan

  
  
   

• An Introduction to Systems Biology: Design Principles of Biological Circuits (Mathematical & Computational Biology)

  Uri Alon

  
  
   

• A New Kind of Science

  Stephen Wolfram

  
  Physics and computer science genius Stephen Wolfram, sets his sights on a daunting goal: understanding the universe. A New Kind of Science is a gorgeous, 1,280-page tome more than a decade in the making. With patience, insight, and self-confidence to spare, Wolfram outlines a fundamental new way of modelling complex systems.

  On the frontier of complexity science since he was a boy, Wolfram is a champion of cellular automata--256 "programs" governed by simple non-mathematical rules. He points out that even the most complex equations fail to accurately model biological systems, but the simplest cellular automata can produce results straight out of nature--tree branches, stream eddies, and leopard spots, for instance. The graphics in A New Kind of Science show striking resemblance to the patterns we see in nature every day.

  Wolfram wrote the book in a distinct style meant to make it easy to read, even for non-techies; a basic familiarity with logic is helpful but not essential. Readers will find themselves swept away by the elegant simplicity of Wolfram's ideas and the accidental artistry of the cellular automaton models. Whether or not Wolfram's revolution ultimately gives us the keys to the universe, his new science is absolutely awe-inspiring. --Therese Littleton

  
   

• Introduction to Computational Genomics: A Case Studies Approach

  Nello Cristianini, Matthew W. Hahn

  
  
   

• Bioconductor Case Studies (Use R)

  Florian Hahne, Wolfgang Huber, Robert Gentleman, Seth Falcon

  
  
   

• Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology

  Dan Gusfield

  
  
   

• Understanding Bioinformatics

  Marketa Zvelebil, Jeremy O. Baum

  
  
   

• Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health) (Statistics for Biology and Health) (Statistics for Biology and Health)

  Robert Gentleman

  
  
   

• Bioinformatics and Molecular Evolution

  Paul G. Higgs, Teresa K. Attwood

  
  
   

• Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation (Wiley Series in Mathematical & Computational Biology)

  O. Diekmann, J. A. P. Heesterbeek

  
  
   

• Stochastic Modelling for Systems Biology (Mathematical and Computational Biology)

  Darren James Wilkinson

  
  
   

• Fundamentals of Computational Neuroscience

  Thomas P. Trappenberg

  
  
   

• Individual-based Modeling and Ecology (Princeton Series in Theoretical and Computational Biology)

  Volker Grimm, Steven F. Railsback

  
  
   

• Handbook of Hidden Markov Models in Bioinformatics (Mathematical and Computational Biology) (Chapman & Hall/CRC Mathematical & Computational Biology)

  Martin Gollery

  
  
   

• An Introduction to Bioinformatics Algorithms (Computational Molecular Biology)

  NC Jones

  
  
   

• Computational Molecular Biology: An Introduction (Wiley Series in Mathematical & Computational Biology)

  Peter Clote, Rolf Backofen

  
  
   

• Optimal Control Applied to Biological Models (Chapman & Hall / Crc Mathematical and Computational Biology) (Chapman & Hall/CRC Mathematical & Computational Biology)

  Suzanne Lenhart, John T. Workman

  
  
   

• Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting (Computational Neuroscience)

  EM Izhikevich

  
  
   

• Grid Computing for Bioinformatics and Computational Biology (Wiley Series in Bioinformatics)