Elements of Computational Systems Biology

by Huma M. Lodhi; Stephen H. Muggleton

• ISBN13: 9780470556740
• ISBN10: 0470556749
• Additional ISBN(s): 9780470180938, 9780470556757
• Format: eBook
• Copyright: 2010-03-01
• Publisher: Wiley
• More Book Details
• Purchase Benefits

Summary

Groundbreaking, long-ranging research in this emergent field that enables solutions to complex biological problems Computational systems biology is an emerging discipline that is evolving quickly due to recent advances in biology such as genome sequencing, high-throughput technologies, and the recent development of sophisticated computational methodologies. Elements of Computational Systems Biology is a comprehensive reference covering the computational frameworks and techniques needed to help research scientists and professionals in computer science, biology, chemistry, pharmaceutical science, and physics solve complex biological problems. Written by leading experts in the field, this practical resource gives detailed descriptions of core subjects, including biological network modeling, analysis, and inference; presents a measured introduction to foundational topics like genomics; and describes state-of-the-art software tools for systems biology. Offers a coordinated integrated systems view of defining and applying computational and mathematical tools and methods to solving problems in systems biology Chapters provide a multidisciplinary approach and range from analysis, modeling, prediction, reasoning, inference, and exploration of biological systems to the implications of computational systems biology on drug design and medicine Helps reduce the gap between mathematics and biology by presenting chapters on mathematical models of biological systems Establishes solutions in computer science, biology, chemistry, and physics by presenting an in-depth description of computational methodologies for systems biology Elements of Computational Systems Biology is intended for academic/industry researchers and scientists in computer science, biology, mathematics, chemistry, physics, biotechnology, and pharmaceutical science. It is also accessible to undergraduate and graduate students in machine learning, data mining, bioinformatics, computational biology, and systems biology courses.

Table of Contents

Preface

Contributors

Overview

Advances in Computational Systems Biology

Biological Network Modeling

Models in Systems Biology: The Parameter Problem and the Meanings of Robustness

In Silico Analysis of Combined Therapeutics Strategy for Hearth Failure

Rule-Based Modeling and Model Refinement

A (Natural) Computing Perspective on Cellular Processes

Simulating Filament Dynamics in Cellular Systems

Biological Network Inference

Reconstruction of Biological Networks by Supervised Machine Learning Approaches

Supervised Inference of Metabolic Networks from the Integration of Genomic Data and Chemical Information

Integrating Abduction and Induction in Biological Inference Using CF-Induciton

Analysis and Control of Deterministic and Probabilistic Boolean Networks

Probabilistic Methods and Rate Heterogeneity

Genomics And Computational Systems Biology

From DNA Motifs to Gene Networks: A Review of Physical Interaction Models

The Impact of Whole Genome In Silico Screening for Nuclear Receptor-Binding Sites in Systems Biology

Environmental and Physiological Insights from Microbial Genome Sequences

Software Tools For Systems Biology

Ali Baba: A Text Mining Tool for Systems Biology

Validation Issues in Regulatory Module Discovery

Computational Imaging and Modeling for Systems Biology

Index

Series Information

Table of Contents provided by Publisher. All Rights Reserved.