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Author: Byung-Jun Yoon
Publisher: Springer Nature
ISBN: 3030571734
Category : Medical
Languages : en
Pages : 220
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Book Description
This book reviews recent advances in the emerging field of computational network biology with special emphasis on comparative network analysis and network module detection. The chapters in this volume are contributed by leading international researchers in computational network biology and offer in-depth insight on the latest techniques in network alignment, network clustering, and network module detection. Chapters discuss the advantages of the respective techniques and present the current challenges and open problems in the field. Recent Advances in Biological Network Analysis: Comparative Network Analysis and Network Module Detection will serve as a great resource for graduate students, academics, and researchers who are currently working in areas relevant to computational network biology or wish to learn more about the field. Data scientists whose work involves the analysis of graphs, networks, and other types of data with topological structure or relations can also benefit from the book's insights.
Author: Byung-Jun Yoon
Publisher: Springer Nature
ISBN: 3030571734
Category : Medical
Languages : en
Pages : 220
Get Book Here
Book Description
This book reviews recent advances in the emerging field of computational network biology with special emphasis on comparative network analysis and network module detection. The chapters in this volume are contributed by leading international researchers in computational network biology and offer in-depth insight on the latest techniques in network alignment, network clustering, and network module detection. Chapters discuss the advantages of the respective techniques and present the current challenges and open problems in the field. Recent Advances in Biological Network Analysis: Comparative Network Analysis and Network Module Detection will serve as a great resource for graduate students, academics, and researchers who are currently working in areas relevant to computational network biology or wish to learn more about the field. Data scientists whose work involves the analysis of graphs, networks, and other types of data with topological structure or relations can also benefit from the book's insights.
Author: Pietro Hiram Guzzi
Publisher: Elsevier
ISBN: 0128193514
Category : Science
Languages : en
Pages : 212
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Book Description
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
Author: Henry Han
Publisher: Springer Nature
ISBN: 9811587604
Category : Computers
Languages : en
Pages : 295
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Book Description
This book constitutes selected papers of the Third International Conference on Data Science, Medicine and Bioinformatics, IDMB 2019, held in Nanning, China, in June 2019. The 19 full papers and 1 short paper were carefully reviewed and selected from 93 submissions. The papers are organized according to the following topical sections: business data science: fintech, management, and analytics.- health and biological data science.- novel data science theory and applications.
Author: Mark Buchanan
Publisher: Cambridge University Press
ISBN: 0521882737
Category : Science
Languages : en
Pages : 282
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Book Description
Key introductory text for graduate students and researchers in physics, biology and biochemistry.
Author: Uri Alon
Publisher: CRC Press
ISBN: 1000001326
Category : Mathematics
Languages : en
Pages : 343
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Book Description
Praise for the first edition: ... superb, beautifully written and organized work that takes an engineering approach to systems biology. Alon provides nicely written appendices to explain the basic mathematical and biological concepts clearly and succinctly without interfering with the main text. He starts with a mathematical description of transcriptional activation and then describes some basic transcription-network motifs (patterns) that can be combined to form larger networks. – Nature [This text deserves] serious attention from any quantitative scientist who hopes to learn about modern biology ... It assumes no prior knowledge of or even interest in biology ... One final aspect that must be mentioned is the wonderful set of exercises that accompany each chapter. ... Alon’s book should become a standard part of the training of graduate students. – Physics Today Written for students and researchers, the second edition of this best-selling textbook continues to offer a clear presentation of design principles that govern the structure and behavior of biological systems. It highlights simple, recurring circuit elements that make up the regulation of cells and tissues. Rigorously classroom-tested, this edition includes new chapters on exciting advances made in the last decade. Features: Includes seven new chapters The new edition has 189 exercises, the previous edition had 66 Offers new examples relevant to human physiology and disease The book website including course videos can be found here: https://www.weizmann.ac.il/mcb/UriAlon/introduction-systems-biology-design-principles-biological-circuits.
Author: Sang Yup Lee
Publisher: Springer Science & Business Media
ISBN: 1402093942
Category : Science
Languages : en
Pages : 471
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Book Description
Systems biology is changing the way biological systems are studied by allowing us to examine the cell and organism as a whole. Systems biotechnology allows optimal design and development of upstream to downstream bioprocesses by taking a systems-approach. E. coli has been a model organism for almost all biological and biotechnological studies. This book brings together for the first time the state-of-the-art reviews by the world-leading experts on systems biology and biotechnological applications of E. coli. The topics covered include genomics and functional genomics, resources for systems biology, network analysis, genome-scale metabolic reconstruction, modelling and simulation, dynamic modelling and simulation, systems-level analysis of evolution, plasmids and expression systems, protein synthesis, production and export, engineering the central metabolism, synthetic biology, and systems metabolic engineering of E. coli. This book provides readers with guidance on how a complex biological system can be studied using E. coli as a model organism. It also presents how to perform synthetic biology and systems metabolic engineering studies on E. coli with successful examples, the approaches of which can be extended to other organisms. This book will be a complete resource for anyone interested in systems biology and biotechnology.
Author: Mehdi Pirooznia
Publisher: Frontiers Media SA
ISBN: 2832542964
Category : Science
Languages : en
Pages : 233
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Book Description
Lung Carcinoma is the 2nd most common cancer worldwide, with more than 2.2 million cases recorded globally in the year 2020, as well as 1.8 million deaths. It is the most common cancer in men and the 2nd most common cancer in women, with an estimated lifetime risk of developing the disease of 1 in 15 for men and 1 in 17 for women. Whilst being the most prevalent cancer, it is important to note that smoking is the single biggest risk factor for developing Lung Cancer, with over 70% of cases being estimated to have been caused by tobacco smoke, and excessive smoking potentially leading to as much as a 25x increase in the likelihood of the disease developing. Mortality rates have been steadily dropping globally due to declining smoking rates, especially in younger generations who are now more aware of the potential dangers, but also because of the increasing advancements being made in our understanding of the disease. Improved screening methods mean many more cases are now caught earlier than they would otherwise have been, and our ever-advancing ranges of treatments can begin earlier than they could have previously. Recent advances in sequencing technology, computational approaches, and our biological understanding of lung cancer have revolutionized how we diagnose, prognosticate, and treat lung carcinoma. Genetic studies into this disease have revealed a plethora of information which can be used to combat the Cancer, such as novel biomarkers and gene signatures, as well as opening the door to more of a ‘personalized medicine’ approach.
Author: Sanghamitra Bandyopadhyay
Publisher: World Scientific
ISBN: 9812708898
Category : Computers
Languages : en
Pages : 353
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Book Description
Bioinformatics, a field devoted to the interpretation and analysis of biological data using computational techniques, has evolved tremendously in recent years due to the explosive growth of biological information generated by the scientific community. Soft computing is a consortium of methodologies that work synergistically and provides, in one form or another, flexible information processing capabilities for handling real-life ambiguous situations. Several research articles dealing with the application of soft computing tools to bioinformatics have been published in the recent past; however, they are scattered in different journals, conference proceedings and technical reports, thus causing inconvenience to readers, students and researchers. This book, unique in its nature, is aimed at providing a treatise in a unified framework, with both theoretical and experimental results, describing the basic principles of soft computing and demonstrating the various ways in which they can be used for analyzing biological data in an efficient manner. Interesting research articles from eminent scientists around the world are brought together in a systematic way such that the reader will be able to understand the issues and challenges in this domain, the existing ways of tackling them, recent trends, and future directions. This book is the first of its kind to bring together two important research areas, soft computing and bioinformatics, in order to demonstrate how the tools and techniques in the former can be used for efficiently solving several problems in the latter. Sample Chapter(s). Chapter 1: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (160 KB). Contents: Overview: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (H Tang & S Kim); An Introduction to Soft Computing (A Konar & S Das); Biological Sequence and Structure Analysis: Reconstructing Phylogenies with Memetic Algorithms and Branch-and-Bound (J E Gallardo et al.); Classification of RNA Sequences with Support Vector Machines (J T L Wang & X Wu); Beyond String Algorithms: Protein Sequence Analysis Using Wavelet Transforms (A Krishnan & K-B Li); Filtering Protein Surface Motifs Using Negative Instances of Active Sites Candidates (N L Shrestha & T Ohkawa); Distill: A Machine Learning Approach to Ab Initio Protein Structure Prediction (G Pollastri et al.); In Silico Design of Ligands Using Properties of Target Active Sites (S Bandyopadhyay et al.); Gene Expression and Microarray Data Analysis: Inferring Regulations in a Genomic Network from Gene Expression Profiles (N Noman & H Iba); A Reliable Classification of Gene Clusters for Cancer Samples Using a Hybrid Multi-Objective Evolutionary Procedure (K Deb et al.); Feature Selection for Cancer Classification Using Ant Colony Optimization and Support Vector Machines (A Gupta et al.); Sophisticated Methods for Cancer Classification Using Microarray Data (S-B Cho & H-S Park); Multiobjective Evolutionary Approach to Fuzzy Clustering of Microarray Data (A Mukhopadhyay et al.). Readership: Graduate students and researchers in computer science, bioinformatics, computational and molecular biology, artificial intelligence, data mining, machine learning, electrical engineering, system science; researchers in pharmaceutical industries.
Author: Elena Marchiori
Publisher: Springer
ISBN: 3540787577
Category : Computers
Languages : en
Pages : 222
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Book Description
Coverage in this proceedings volume includes biomarker discovery, cell simulation and modeling, ecological modeling, gene networks, biotechnology, microarray analysis, protein interactions, proteomics, sequence analysis and alignment, and systems biology
Author: Vijai Singh
Publisher: Springer Nature
ISBN: 9819984017
Category :
Languages : en
Pages : 365
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Book Description
