Computational Biology

PUBLISHED


Viewing: 1 - 10 of 62
Published:
March 18, 2014
Author(s):
Allegra Via, Kristian Rother, Anna Tramontano
Take Control of Your Data and Use Python with Confidence Requiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to 
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$69.95
Paperback
Published:
March 06, 2014
Editor(s):
Luis Rueda
Microarray Image and Data Analysis: Theory and Practice is a compilation of the latest and greatest microarray image and data analysis methods from the multidisciplinary international research community. Delivering a detailed discussion of the biological aspects and applications of microarrays, the 
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$99.95
Hardback
Published:
January 27, 2014
Editor(s):
James Devillers
Bees are critically important for ecosystem function and biodiversity maintenance through their pollinating activity. Unfortunately, bee populations are faced with many threats, and evidence of a massive global pollination crisis is steadily growing. As a result, there is a need to understand and, 
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$119.95
Hardback
Published:
December 18, 2013
Author(s):
Guanyu Wang, PhD
A complex disease involves many etiological and risk factors operating at multiple levels—molecular, cellular, organismal, and environmental. The incidence of such diseases as cancer, obesity, and diabetes are increasing in occurrence, urging us to think fundamentally and use a broader perspective 
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$129.95
Hardback
Published:
December 17, 2013
Author(s):
Ken A. Aho
Full of biological applications, exercises, and interactive graphical examples, Foundational and Applied Statistics for Biologists Using R presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment 
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$69.95
Hardback
Published:
November 06, 2013
Editor(s):
Arvin Agah
Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to 
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$149.95
Hardback
Published:
November 01, 2013
Author(s):
Zehua Chen
While numerous advanced statistical approaches have recently been developed for quantitative trait loci (QTL) mapping, the methods are scattered throughout the literature. Statistical Methods for QTL Mapping brings together many recent statistical techniques that address the data complexity of QTL 
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$89.95
Hardback
Published:
April 24, 2013
Author(s):
Alpan Raval, Animesh Ray
The new research area of genomics-inspired network biology lacks an introductory book that enables both physical/computational scientists and biologists to obtain a general yet sufficiently rigorous perspective of current thinking. Filling this gap, Introduction to Biological Networks provides a 
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$79.95
Hardback
Published:
January 23, 2013
Author(s):
Diana Ivanova Stephanova, Bozhidar Dimitrov Kolev
This book covers the computer simulation of demyelinating neuropathies and neuronopathies and compares models with clinical findings. Through the approximation of nerve excitation and conduction, the authors show how the versatile structure of nerve fibers relates to different modes of focal 
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$69.95
Hardback
Published:
August 30, 2012
Author(s):
Jung Soh, Paul M.K. Gordon, Christoph W. Sensen
The success of individualized medicine, advanced crops, and new and sustainable energy sources requires thoroughly annotated genomic information and the integration of this information into a coherent model. A thorough overview of this field, Genome Annotation explores automated genome analysis and 
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$93.95
Hardback

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Data Mining "Nobel Prize" Awarded to Series Editor Vipin Kumar

The ACM SIGKDD 2012 Innovation Award, the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD), has been awarded to Prof. Vipin Kumar for his technical contributions to foundational research in data mining and its applications to mining scientific and climate data. Prof. Kumar is the editor of the Chapman & Hall/CRC Data Mining and Knowledge Discovery Series. He has pioneered research in the areas of high performance and parallel data mining. His research group has also been at the forefront in the development of data-driven discovery methods for analyzing global climate and ecosystem data.

 

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