Emphasizing the search for patterns within and between biological sequences, trees, and graphs, Combinatorial Pattern Matching Algorithms in Computational Biology Using Perl and R shows how combinatorial pattern matching algorithms can solve computational biology problems that arise in the analysis of genomic, transcriptomic, proteomic, metabolomic, and interactomic data. It implements the algorithms in Perl and R, two widely used scripting languages in computational biology.
The book provides a well-rounded explanation of traditional issues as well as an...
Emphasizing the search for patterns within and between biological sequences, trees, and graphs, Combinatorial Pattern Matching Algorithms i...
The unprecedented amount of data produced with high-throughput experimentation forces biologists to employ mathematical representation and computation methods to glean meaningful information in systems-level biology. Applying this approach to the underlying molecular mechanisms of tumorigenesis, cancer researchers can uncover a series of new discoveries and biological insights.
The First Cancer Systems Biology Book Designed for Computational and Experimental Biologists Unusual in its dualistic approach, Cancer Systems Biology...
The unprecedented amount of data produced with high-throughput experimentation forces biologists to employ mathematical representation and computat...
An Introduction to Systems BioengineeringTakes a Clear and Systematic Engineering Approach to Systems Biology Focusing on genetic regulatory networks, Engineering Genetic Circuits presents the modeling, analysis, and design methods for systems biology. It discusses how to examine experimental data to learn about mathematical models, develop efficient abstraction and simulation methods to analyze these models, and use analytical methods to guide the design of new circuits.
After reviewing the basic molecular biology and biochemistry principles needed to understand genetic circuits, the book...
An Introduction to Systems BioengineeringTakes a Clear and Systematic Engineering Approach to Systems Biology Focusing on genetic regulatory netwo...
Too often, healthcare workers are led to believe that medical informatics is a complex field that can only be mastered by teams of professional programmers. This is simply not the case. With just a few dozen simple algorithms, easily implemented with open source programming languages, you can fully utilize the medical information contained in clinical and research datasets. The common computational tasks of medical informatics are accessible to anyone willing to learn the basics.
Methods in Medical Informatics: Fundamentals of Healthcare Programming in Perl, Python, and Ruby demonstrates...
Too often, healthcare workers are led to believe that medical informatics is a complex field that can only be mastered by teams of professional progra...
