Elements of Computational Systems... | Buy

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.

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.

Supplemental Materials

What is included with this book?

The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.