<p><P>This book provides simultaneously a design blueprint, user guide, research agenda, and communication platform for current and future developments in artificial intelligence (AI) approaches to systems biology. It places an emphasis on the molecular dimension of life phenomena and in one chapter
Artificial Intelligence Methods and Tools for Systems Biology
โ Scribed by W. Dubitzky
- Publisher
- Springer
- Year
- 2005
- Tongue
- English
- Leaves
- 231
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
This book provides simultaneously a design blueprint, user guide, research agenda, and communication platform for current and future developments in artificial intelligence (AI) approaches to systems biology. It places an emphasis on the molecular dimension of life phenomena and in one chapter on anatomical and functional modeling of the brain.
As design blueprint, the book is intended for scientists and other professionals tasked with developing and using AI technologies in the context of life sciences research. As a user guide, this volume addresses the requirements of researchers to gain a basic understanding of key AI methodologies for life sciences research. Its emphasis is not on an intricate mathematical treatment of the presented AI methodologies. Instead, it aims at providing the users with a clear understanding and practical know-how of the methods. As a research agenda, the book is intended for computer and life science students, teachers, researchers, and managers who want to understand the state of the art of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. Our aim was to maintain the readability and accessibility of a textbook throughout the chapters, rather than compiling a mere reference manual. The book is also intended as a communication platform seeking to bride the cultural and technological gap among key systems biology disciplines. To support this function, contributors have adopted a terminology and approach that appeal to audiences from different backgrounds.
โฆ Table of Contents
Contents......Page 7
Preface......Page 9
Lazy Learning for Predictive Toxicology based on a Chemical Ontology......Page 18
QSAR Modeling of Mutagenicity on Non-Congeneric Sets of Organic Compounds......Page 36
Characterizing Gene Expression Time Series using a Hidden Markov Model......Page 53
Analysis of Large-Scale mRNA Expression Data Sets by Genetic Algorithms......Page 67
A Data-Driven, Flexible Machine Learning Strategy for the Classification of Biomedical Data......Page 83
Cooperative Metaheuristics for Exploring Proteomic Data......Page 102
Integrating Gene Expression Data, Protein Interaction Data, and Ontology-Based Literature Searches......Page 122
Ontologies in Bioinformatics and Systems Biology......Page 143
Natural Language Processing and Systems Biology......Page 160
Systems Level Modeling of Gene Regulatory Networks......Page 187
Computational Neuroscience for Cognitive Brain Functions......Page 208
D......Page 227
I......Page 228
P......Page 229
U......Page 230
Y......Page 231
๐ SIMILAR VOLUMES
<p><P>This book provides simultaneously a design blueprint, user guide, research agenda, and communication platform for current and future developments in artificial intelligence (AI) approaches to systems biology. It places an emphasis on the molecular dimension of life phenomena and in one chapter
<p><P>This book provides simultaneously a design blueprint, user guide, research agenda, and communication platform for current and future developments in artificial intelligence (AI) approaches to systems biology. It places an emphasis on the molecular dimension of life phenomena and in one chapter
This introduction to computational geometry is designed for beginners. It emphasizes simple randomized methods, developing basic principles with the help of planar applications, beginning with deterministic algorithms and shifting to randomized algorithms as the problems become more complex. It also
This volume contains a total of thirteen papers covering a variety of AI topics ranging from computer vision and robotics to intelligent modeling, neural networks and fuzzy logic. There are two general articles on robotics and fuzzy logic. The article on robotics focuses on the application of roboti
<p><span>The aim of this book is to highlight the most promising lines of research, using new enabling technologies and methods based on AI/ML techniques to solve issues and challenges related to intelligent and computing systems. Intelligent computing easily collects data using smart technological