8 edition of Computational systems bioinformatics found in the catalog.
|Other titles||Life Sciences Society computational systems bioinformatics, CSB Conference proceedings 2006, CSB 2006 Conference proceedings.|
|Statement||editors, Peter Markstein, Ying Xu.|
|Series||Series on advances in bioinformatics and computational biology -- v. 4|
|Contributions||Markstein, Peter., Xu, Ying, 1960-, Hewlett-Packard Company., Microsoft Research., Life Sciences Society.|
|The Physical Object|
|Pagination||xvi, 400 p. :|
|Number of Pages||400|
The use of agents in computational and systems biology suggest the design of agent-based systems, tools and languages for modelling the biological processes themselves. At the dawn of the ‘omics’ age, bioinformatics was defined [ 11 ] as a computational discipline aiming at the management and analysis of biological by: Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology: Systems and Applications covers the latest trends in the field with special emphasis on their applications. The first part covers the major areas of computational biology, development and application of data-analytical and theoretical methods, mathematical .
Systemic Approaches in Bioinformatics and Computational Systems Biology: Recent Advances presents new techniques that have resulted from the application of computer science methods to the organization and interpretation of biological data. The book covers three subject areas: bioinformatics, computational biology, and computational systems biology. Part of book: Systems and Computational Biology - Bioinformatics and Computational Modeling. 8. Prediction and Analysis of Gene Regulatory Networks in Prokaryotic Genomes. By Richard Münch, Johannes Klein and Dieter Jahn. Part of book: Systems and Computational Biology - Molecular and Cellular Experimental Systems. 9.
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This book is the first of its kind to focus on the newly emerging field of systems biology with an emphasis on computational approaches.
The work covers new concepts, methods for information storage, mining and knowledge extraction, reverse engineering of gene and metabolic networks, as well as modelling and simulation of multi-cellular systems. Abstract. The best understanding of complex biological systems ultimately comes from details of the underlying atomic structures within it.
In the absence of known structures of all protein complexes and interactions in a system, structural bioinformatics or modeling fill an important niche in providing predicted mechanistic information which can guide experiments, aid the. The last part of the book, dedicated to systems biology, covers phylogenetic analysis and evolutionary tree computations, as well as gene expression analysis with microarrays.
In brief, the book offers the ideal hands-on reference guide to the field of Format: Hardcover. Systems and Computational Biology - Bioinformatics and Computational Modeling. Edited by: Ning-Sun Yang.
ISBNPDF ISBNPublished Cited by: 4. Systems Biology and Bioinformatics: A Computational Approach provides students with a comprehensive collection of the computational methods used in what is being coined the digital era of biology.
Written by field experts with proven track records, this authoritative textbook first provides an introduction to systems biology and its impact on Author: Kayvan Najarian, Siamak Najarian, Shahriar Gharibzadeh, Christopher N.
Eichelberger. This series emphasizes the algorithmic, mathematical, statistical and computational methods that are central in bioinformatics and computational biology. Although the possible set of book topics is large, the following areas are particularly suitable for our book series (but not exhaustive): Bioinformatic databases.
Book Description. Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology discusses the latest developments in all aspects of Computational systems bioinformatics book biology, bioinformatics, and systems biology and the application of data-analytics and algorithms, mathematical modeling, and simu- lation techniques.
• Discusses the development and application of data-analytical. Computational Intelligence Methods for Bioinformatics and Biostatistics Raposo, M.
(Ed), Ribeiro, P. (Ed), Sério, S. (Ed), Staiano, A. (Ed), Ciaramella, A. (Ed) () This book constitutes the thoroughly refereed post-conference proceedings of the 15th International Meeting on Computational Intelligence Methods for Bioinformatics and. Systems Biology and Bioinformatics: A Computational Approach provides students with a comprehensive collection of the computational methods used in what is being coined the digital era of biology.
Written by field experts with proven track records, this authoritative textbook first provides an introduction to systems biology and its impact on.
Computational systems biology is a new and rapidly developing field of research, concerned with understanding the structure and processes of biological systems at the molecular, cellular, tissue, and organ levels through computational modeling as well as novel information theoretic data and image analysis methods.
The discipline of bioinformatics and computational biology sits at the interface between biology, the quantitative sciences (such as mathematics, statistics, computer science) and engineering, and spans levels of investigation from single genes to systems.
Section Bioinformatics and Computational Biology aims to rapidly publish new methods, research findings, opinions, and. Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes.
The book covers Theory, Topics and Applications, with a special focus on. Systems Biology & Bioinformatics. Featured journals see all. Neuroinformatics. Bulletin of Mathematical Biology. Advances in Bioinformatics and Computational Biology.
Kowada, L. (et al.) (Eds.) () Featured book series see all. Translational Bioinformatics. Bioinformatics / ˌ b aɪ. oʊ ˌ ɪ n f ər ˈ m æ t ɪ k s / is an interdisciplinary field that develops methods and software tools for understanding biological data, in particular when the data sets are large and complex.
As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret.
Research Areas: Bioinformatics, Computational Genomics, Computational Systems Biology, Statistical and Population Genetics Research Interests: The Rau lab utilizes populations of mice to study the transcriptomic and epigenomic landscape underlying cardiovascular disorders using a combination of wet and dry-lab techniques.
Shoba's research addresses several key areas of bioinformatics to understand biological systems using computational approaches. Her group has achieved both experience and expertise in different aspects of computational biology, ranging from metabolites and small molecules to biochemical networks and pathway analysis.
Computational systems bioinformatics for RNAi screening and therapeutics is defined as complete computational workflow applicable to the hypothesis generation from large-scale data from image-based RNAi screenings as well as the improvement of RNAi-based therapeutics; the workflow includes automatic image analysis compatible to large-scale cell image data, together with.
Computational Systems Biology of Synaptic Plasticity is a valuable source of knowledge to postgraduate students and researchers in computational systems biology, and as a reference book for various techniques that are needed in modelling biological processes.
Sample Chapter(s) Chapter 1: Introduction ( KB) Contents: Introduction. Computational and theoretical approaches are revolutionizing Pharmacology and Drug Discovery. Predicting, modeling, and simulating potential therapeutic agents and their interactions with target molecules is a powerful new first step in the drug discovery process.
About this book Introduction Chapters detail advanced analysis methods, such as Genome-Wide Association Studies (GWAS), machine learning, reconstruction and analysis of gene regulatory networks and differential coexpression network analysis, and gave a practical guide for how to choose and use the right algorithm or software to handle specific.
Introduction. Computational biology, which includes many aspects of bioinformatics, is the science of using biological data to develop algorithms or models in order to understand biological systems and relationships.
Until recently, biologists did not have access to very large amounts of data.Bioinformatics Open Days is a student-led initiative first held at the Universidade do Minho, Braga in It aims to promote the exchange of knowledge between students, teachers and researchers from the Bioinformatics and Computational Biology fields.Get this from a library!
Computational systems bioinformatics: methods and biomedical applications. [Xiaobo Zhou; Stephen T C Wong] -- "This book begins by introducing the basic mathematical, statistical, and data mining principles of computational systems biology, and then presents bioinformatics technology in microarray and.