Learn IT - Books tags bioinformatics

Python Algorithms: Mastering Basic Algorithms in the Python Language

Apress, 2010

Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving...

Data Mining for Bioinformatics

CRC Press, 2012

Covering theory, algorithms, and methodologies, as well as data mining technologies, Data Mining for Bioinformatics provides a comprehensive discussion of data-intensive computations used in data mining with applications in bioinformatics. It supplies a broad, yet in-depth, overview of the application domains of data mining...

Pharmaceutical Data Mining: Approaches and Applications for Drug Discovery

John Wiley & Sons, 2009

Leading experts illustrate how sophisticated computational data mining techniques can impact contemporary drug discovery and development

In the era of post-genomic drug development, extracting and applying knowledge from chemical, biological, and clinical data is one of the greatest challenges facing the pharmaceutical industry....

Systems Bioinformatics: An Engineering Case-Based Approach

Artech House Publishers, 2007

The high-throughput nature of bioinformatics and system biology has made traditional biological methods, which tend to focus one or two molecules at a time, obsolete. It has made engineering and problem solving skills essential to attack the resulting complex, multiscale problems. Certain technologies, such as robotics automation, microfabrication,...

Bioinformatics: High Performance Parallel Computer Architectures (Embedded Multi-Core Systems)

CRC Press, 2010

New sequencing technologies have broken many experimental barriers to genome scale sequencing, leading to the extraction of huge quantities of sequence data. This expansion of biological databases established the need for new ways to harness and apply the astounding amount of available genomic information and convert it into substantive...

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

Springer, 2005

Full four-color book.

Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R.

All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies.

Code underlying all of the computations that are...

Genetic Programming Theory and Practice V (Genetic and Evolutionary Computation)

Springer, 2008

Genetic Programming Theory and Practice V was developed from the fifth workshop at the University of Michigans Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). Contributions from the foremost international researchers and practitioners in...

Pro Perl Debugging

Apress, 2005

Combining the best features of C, UNIX utilities, and regular expressions, Perl has grown as one of the most powerful and popular scripting languages. The valuable Perl is often used for system administration, text processing and Web programming. It is even being used for more exotic areas, like bioinformatics. Perl is supported by all of the...

Linear Genetic Programming (Genetic and Evolutionary Computation)

Springer, 2006

Linear Genetic Programming presents a variant of genetic programming (GP) that evolves imperative computer programs as linear sequences of instructions, in contrast to the more traditional functional expressions or syntax trees. Primary characteristics of linear program structure are exploited to achieve acceleration of both execution time and...

Fuzzy Systems in Bioinformatics and Computational Biology (Studies in Fuzziness and Soft Computing)

Springer, 2009

Biological systems are inherently stochastic and uncertain. Thus, research in bioinformatics, biomedical engineering and computational biology has to deal with a large amount of uncertainties.

Fuzzy logic has shown to be a powerful tool in capturing different uncertainties in engineering systems. In recent years, fuzzy logic based modeling and...

Data Engineering: Fuzzy Mathematics in Systems Theory and Data Analysis

John Wiley & Sons, 2001

Although data engineering is a multi-disciplinary field with applications in control, decision theory, and the emerging hot area of bioinformatics, there are no books on the market that make the subject accessible to non-experts. This book fills the gap in the field, offering a clear, user-friendly introduction to the main theoretical and...

Data Algorithms: Recipes for Scaling Up with Hadoop and Spark

O'Reilly, 2015

If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as...

Result Page: 20 19 18 17 16 15 14 13 12 11