Download or read book Networks in Cell Biology written by Mark Buchanan and published by Cambridge University Press. This book was released on 2010-05-13 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Key introductory text for graduate students and researchers in physics, biology and biochemistry.

Download or read book Algorithms on Trees and Graphs written by Gabriel Valiente and published by Springer Nature. This book was released on 2021-10-11 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph algorithms is a well-established subject in mathematics and computer science. Beyond classical application fields, such as approximation, combinatorial optimization, graphics, and operations research, graph algorithms have recently attracted increased attention from computational molecular biology and computational chemistry. Centered around the fundamental issue of graph isomorphism, this text goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. This book introduces graph algorithms on an intuitive basis followed by a detailed exposition in a literate programming style, with correctness proofs as well as worst-case analyses. Furthermore, full C++ implementations of all algorithms presented are given using the LEDA library of efficient data structures and algorithms.

Download or read book Networks of Networks in Biology written by Narsis A. Kiani and published by Cambridge University Press. This book was released on 2021-04 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces network inspired approaches for the analysis and integration of large, heterogeneous data sets in the life sciences.

Download or read book Systems Biology and In Depth Applications for Unlocking Diseases written by Babak Sokouti and published by Elsevier. This book was released on 2024-11-05 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems Biology and In-Depth Applications for Unlocking Diseases: Principles, tools and Application to Disease provides the essence of systems biology approaches in a practical manner, illustrating the basic principles essential to develop and model in real life science applications. Methodologies covered show how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatment. Sections provide an introduction and history of systems biology, discuss the tools and resources needed for structure and function of biological systems, and present evidence of systems biology in action. Examples include big data techniques, scale networks, mathematical model development, and much more. This is the perfect reference to provide the fundamental base of knowledge needed for systems biologists, professionals in systems medicine, computational biologists, and bioinformaticians. - Provides detailed and comprehensive coverage of the field of systems biology - Delivers instruction on how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatment - Makes effective steps towards personalized medicine in the treatment of disease - Explains effective disease treatment strategies at early diagnosis stages

Download or read book Encyclopedia of Bioinformatics and Computational Biology written by and published by Elsevier. This book was released on 2018-08-21 with total page 3421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set 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 Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases

Download or read book Machine Learning Methodologies To Study Molecular Interactions written by Elif Ozkirimli and published by Frontiers Media SA. This book was released on 2022-01-21 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr. Elif Ozkirimli is a full time employee of F. Hoffmann-La Roche AG, Switzerland and Dr. Artur Yakimovich is a full time employee of Roche Products Limited, UK. All other Topic Editors declare no competing interests with regards to the Research Topic.

Download or read book 10th International Conference on Practical Applications of Computational Biology Bioinformatics written by Mohd Saberi Mohamad and published by Springer. This book was released on 2016-05-31 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of Bioinformatics and Computational Biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial Intelligence. Clearly, Biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of Bioinformatics scientists. PACBB‘16 hopes to contribute to this effort promoting this fruitful interaction. PACBB'16 technical program included 21 papers spanning many different sub-fields in Bioinformatics and Computational Biology. Therefore, the conference will certainly promote the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists). The scientific content will certainly be challenging and will promote the improvement of the work being developed by each of the participants.

Download or read book Biological Network Analysis written by Pietro Hiram Guzzi and published by Elsevier. This book was released on 2020-05-11 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological Network Analysis: Trends, Approaches, Graph Theory, and Algorithms considers three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN), and Human Brain Connectomes. The book's authors discuss various graph theoretic and data analytics approaches used to analyze these networks with respect to available tools, technologies, standards, algorithms and databases for generating, representing and analyzing graphical data. As a wide variety of algorithms have been developed to analyze and compare networks, this book is a timely resource. - Presents recent advances in biological network analysis, combining Graph Theory, Graph Analysis, and various network models - Discusses three major biological networks, including Gene Regulatory Networks (GRN), Protein-Protein Interaction Networks (PPIN) and Human Brain Connectomes - Includes a discussion of various graph theoretic and data analytics approaches

Download or read book Statistical and Machine Learning Approaches for Network Analysis written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2012-06-26 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networks An introduction to complex networks—measures, statistical properties, and models Modeling for evolving biological networks The structure of an evolving random bipartite graph Density-based enumeration in structured data Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.

Download or read book Biomolecular Networks written by Luonan Chen and published by John Wiley & Sons. This book was released on 2009-06-29 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Alternative techniques and tools for analyzing biomolecular networks With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's form and function. This book addresses the important need for a new set of computational tools to reveal essential biological mechanisms from a systems biology approach. Readers will get comprehensive coverage of analyzing biomolecular networks in cellular systems based on available experimental data with an emphasis on the aspects of network, system, integration, and engineering. Each topic is treated in depth with specific biological problems and novel computational methods: GENE NETWORKS—Transcriptional regulation; reconstruction of gene regulatory networks; and inference of transcriptional regulatory networks PROTEIN INTERACTION NETWORKS—Prediction of protein-protein interactions; topological structure of biomolecular networks; alignment of biomolecular networks; and network-based prediction of protein function METABOLIC NETWORKS AND SIGNALING NETWORKS—Analysis, reconstruction, and applications of metabolic networks; modeling and inference of signaling networks; and other topics and new trends In addition to theoretical results and methods, many computational software tools are referenced and available from the authors' Web sites. Biomolecular Networks is an indispensable reference for researchers and graduate students in bioinformatics, computational biology, systems biology, computer science, and applied mathematics.

Download or read book Kernel Methods in Bioengineering Signal and Image Processing written by Gustavo Camps-Valls and published by IGI Global. This book was released on 2007-01-01 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book presents an extensive introduction to the field of kernel methods and real world applications. The book is organized in four parts: the first is an introductory chapter providing a framework of kernel methods; the others address Bioegineering, Signal Processing and Communications and Image Processing"--Provided by publisher.

Download or read book Systems Biology for Signaling Networks written by Sangdun Choi and published by Springer Science & Business Media. This book was released on 2010-08-09 with total page 900 pages. Available in PDF, EPUB and Kindle. Book excerpt: System Biology encompasses the knowledge from diverse fields such as Molecular Biology, Immunology, Genetics, Computational Biology, Mathematical Biology, etc. not only to address key questions that are not answerable by individual fields alone, but also to help in our understanding of the complexities of biological systems. Whole genome expression studies have provided us the means of studying the expression of thousands of genes under a particular condition and this technique had been widely used to find out the role of key macromolecules that are involved in biological signaling pathways. However, making sense of the underlying complexity is only possible if we interconnect various signaling pathways into human and computer readable network maps. These maps can then be used to classify and study individual components involved in a particular phenomenon. Apart from transcriptomics, several individual gene studies have resulted in adding to our knowledge of key components that are involved in a signaling pathway. It therefore becomes imperative to take into account of these studies also, while constructing our network maps to highlight the interconnectedness of the entire signaling pathways and the role of that particular individual protein in the pathway. This collection of articles will contain a collection of pioneering work done by scientists working in regulatory signaling networks and the use of large scale gene expression and omics data. The distinctive features of this book would be: Act a single source of information to understand the various components of different signaling network (roadmap of biochemical pathways, the nature of a molecule of interest in a particular pathway, etc.), Serve as a platform to highlight the key findings in this highly volatile and evolving field, and Provide answers to various techniques both related to microarray and cell signaling to the readers.

Download or read book Data Mining Foundations and Intelligent Paradigms written by Dawn E. Holmes and published by Springer Science & Business Media. This book was released on 2012-01-12 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 3: Medical, Health, Social, Biological and other Applications” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.

Download or read book Computational Methods for Understanding Complexity The Use of Formal Methods in Biology written by David A. Rosenblueth, and published by Frontiers Media SA. This book was released on 2016-11-21 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: The complexity of living organisms surpasses our unaided habilities of analysis. Hence, computational and mathematical methods are necessary for increasing our understanding of biological systems. At the same time, there has been a phenomenal recent progress allowing the application of novel formal methods to new domains. This progress has spurred a conspicuous optimism in computational biology. This optimism, in turn, has promoted a rapid increase in collaboration between specialists of biology with specialists of computer science. Through sheer complexity, however, many important biological problems are at present intractable, and it is not clear whether we will ever be able to solve such problems. We are in the process of learning what kind of model and what kind of analysis and synthesis techniques to use for a particular problem. Some existing formalisms have been readily used in biological problems, others have been adapted to biological needs, and still others have been especially developed for biological systems. This Research Topic has examples of cases (1) employing existing methods, (2) adapting methods to biology, and (3) developing new methods. We can also see discrete and Boolean models, and the use of both simulators and model checkers. Synthesis is exemplified by manual and by machine-learning methods. We hope that the articles collected in this Research Topic will stimulate new research.

Download or read book Biocomputing 2023 Proceedings Of The Pacific Symposium written by Russ B Altman and published by World Scientific. This book was released on 2022-11-24 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Pacific Symposium on Biocomputing (PSB) 2023 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2023 will be held on January 3-7, 2023 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2023 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.

Download or read book Springer Handbook of Bio Neuro Informatics written by Nikola Kasabov and published by Springer Science & Business Media. This book was released on 2013-11-30 with total page 1239 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Springer Handbook of Bio-/Neuro-Informatics is the first published book in one volume that explains together the basics and the state-of-the-art of two major science disciplines in their interaction and mutual relationship, namely: information sciences, bioinformatics and neuroinformatics. Bioinformatics is the area of science which is concerned with the information processes in biology and the development and applications of methods, tools and systems for storing and processing of biological information thus facilitating new knowledge discovery. Neuroinformatics is the area of science which is concerned with the information processes in biology and the development and applications of methods, tools and systems for storing and processing of biological information thus facilitating new knowledge discovery. The text contains 62 chapters organized in 12 parts, 6 of them covering topics from information science and bioinformatics, and 6 cover topics from information science and neuroinformatics. Each chapter consists of three main sections: introduction to the subject area, presentation of methods and advanced and future developments. The Springer Handbook of Bio-/Neuroinformatics can be used as both a textbook and as a reference for postgraduate study and advanced research in these areas. The target audience includes students, scientists, and practitioners from the areas of information, biological and neurosciences. With Forewords by Shun-ichi Amari of the Brain Science Institute, RIKEN, Saitama and Karlheinz Meier of the University of Heidelberg, Kirchhoff-Institute of Physics and Co-Director of the Human Brain Project.

Download or read book Pattern Recognition in Computational Molecular Biology written by Mourad Elloumi and published by John Wiley & Sons. This book was released on 2015-11-30 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. Surveys the development of techniques and approaches on pattern recognition in biomolecular data Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.