Download or read book Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics written by Yi Pan and published by John Wiley & Sons. This book was released on 2013-11-12 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems. Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization Includes many tables and illustrations demonstrating concepts and performance figures Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics.
Download or read book Advanced AI Techniques and Applications in Bioinformatics written by Loveleen Gaur and published by CRC Press. This book was released on 2021-10-17 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists. Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers
Download or read book Artificial Intelligence and Heuristic Methods in Bioinformatics written by Paolo Frasconi and published by . This book was released on 2003 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 14 papers consider how various methods in artificial intelligence are applied to problems in bioinformatics. Among the topics are statistical learning and kernel methods in bioinformatics, new machine learning methods for predicting protein topologies, multiple sequence alignments information in structure and function prediction, pattern discovery and the algorithms of surprise, the computational identification of regulatory sites in DNA sequences, computer system gene discovery for promoter structure analysis, and data acquisition and analysis in near-genome-wide expressions screening of tumor suppressor pathways using model cell lines with inducible transcription factors. There is no subject index. Annotation : 2004 Book News, Inc., Portland, OR (booknews.com).
Download or read book Machine Learning In Bioinformatics Of Protein Sequences Algorithms Databases And Resources For Modern Protein Bioinformatics written by Lukasz Kurgan and published by World Scientific. This book was released on 2022-12-06 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Bioinformatics of Protein Sequences guides readers around the rapidly advancing world of cutting-edge machine learning applications in the protein bioinformatics field. Edited by bioinformatics expert, Dr Lukasz Kurgan, and with contributions by a dozen of accomplished researchers, this book provides a holistic view of the structural bioinformatics by covering a broad spectrum of algorithms, databases and software resources for the efficient and accurate prediction and characterization of functional and structural aspects of proteins. It spotlights key advances which include deep neural networks, natural language processing-based sequence embedding and covers a wide range of predictions which comprise of tertiary structure, secondary structure, residue contacts, intrinsic disorder, protein, peptide and nucleic acids-binding sites, hotspots, post-translational modification sites, and protein function. This volume is loaded with practical information that identifies and describes leading predictive tools, useful databases, webservers, and modern software platforms for the development of novel predictive tools.
Download or read book Artificial Intelligence Technologies for Computational Biology written by Ranjeet Kumar Rout and published by CRC Press. This book was released on 2022-11-10 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing. It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems. The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology. This book: • Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis. • Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems. • Presents the application of evolutionary computations for fractal visualization of sequence data. • Explores the use of genetic algorithms for pair-wise and multiple sequence alignments. • Examines the roles of efficient computational techniques in biology.
Download or read book Molecular Bioinformatics written by Steffen Schulze-Kremer and published by Walter de Gruyter. This book was released on 2011-07-20 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advanced AI Techniques and Applications in Bioinformatics written by and published by . This book was released on 2021-10 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists. Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers"--
Download or read book Machine Learning Approaches to Bioinformatics written by Zheng Rong Yang and published by World Scientific. This book was released on 2010 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers a wide range of subjects in applying machine learning approaches for bioinformatics projects. The book succeeds on two key unique features. First, it introduces the most widely used machine learning approaches in bioinformatics and discusses, with evaluations from real case studies, how they are used in individual bioinformatics projects. Second, it introduces state-of-the-art bioinformatics research methods. Furthermore, the book includes R codes and example data sets to help readers develop their own bioinformatics research skills. The theoretical parts and the practical parts are well integrated for readers to follow the existing procedures in individual research. Unlike most of the bioinformatics textbooks on the market, the content coverage is not limited to just one subject. A broad spectrum of relevant topics in bioinformatics including systematic data mining and computational systems biology researches are brought together in this book, thereby offering an efficient and convenient platform for undergraduate/graduate teaching. An essential textbook for both final year undergraduates and graduate students in universities, as well as a comprehensive handbook for new researchers, this book will also serve as a practical guide for software development in relevant bioinformatics projects.
Download or read book Bioinformatics and Medical Applications written by A. Suresh and published by John Wiley & Sons. This book was released on 2022-04-12 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: BIOINFORMATICS AND MEDICAL APPLICATIONS The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms analyses massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. The book delivers various bioinformatics computational methods used to identify diseases at an early stage by assembling cutting-edge resources into a single collection designed to enlighten the reader on topics focusing on computer science, mathematics, and biology. In modern biology and medicine, bioinformatics is critical for data management. This book explains the bioinformatician’s important tools and examines how they are used to evaluate biological data and advance disease knowledge. The editors have curated a distinguished group of perceptive and concise chapters that presents the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to healthcare. Applying deep learning techniques for data-driven solutions in health information allows automated analysis whose method can be more advantageous in supporting the problems arising from medical and health-related information. Audience The primary audience for the book includes specialists, researchers, postgraduates, designers, experts, and engineers, who are occupied with biometric research and security-related issues.
Download or read book Data Analytics in Bioinformatics written by Rabinarayan Satpathy and published by John Wiley & Sons. This book was released on 2021-01-20 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.
Download or read book Introduction to Machine Learning and Bioinformatics written by Sushmita Mitra and published by CRC Press. This book was released on 2008-06-05 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other. Examines Connections between Machine Learning & Bioinformatics The book begins with a brief historical overview of the technological developments in biology. It then describes the main problems in bioinformatics and the fundamental concepts and algorithms of machine learning. After forming this foundation, the authors explore how machine learning techniques apply to bioinformatics problems, such as electron density map interpretation, biclustering, DNA sequence analysis, and tumor classification. They also include exercises at the end of some chapters and offer supplementary materials on their website. Explores How Machine Learning Techniques Can Help Solve Bioinformatics Problems Shedding light on aspects of both machine learning and bioinformatics, this text shows how the innovative tools and techniques of machine learning help extract knowledge from the deluge of information produced by today’s biological experiments.
Download or read book Artificial Intelligence Methods and Tools for Systems Biology written by W. Dubitzky and published by Springer Science & Business Media. This book was released on 2007-09-29 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Algorithms in Bioinformatics written by Ben Raphael and published by Springer. This book was released on 2012-09-07 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th International Workshop on Algorithms in Bioinformatics, WABI 2012, held in Ljubljana, Slovenia, in September 2012. WABI 2012 is one of six workshops which, along with the European Symposium on Algorithms (ESA), constitute the ALGO annual meeting and focuses on algorithmic advances in bioinformatics, computational biology, and systems biology with a particular emphasis on discrete algorithms and machine-learning methods that address important problems in molecular biology. The 35 full papers presented were carefully reviewed and selected from 92 submissions. The papers include algorithms for a variety of biological problems including phylogeny, DNA and RNA sequencing and analysis, protein structure, and others.
Download or read book Computational Intelligence Methods for Bioinformatics and Biostatistics written by Francesco Masulli and published by Springer. This book was released on 2010-07-30 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation. This book constitutes the thoroughly refereed post-conference proceedings of the Sixth International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2009, held in Genova, Italy, in October 2009. The revised 23 full papers presented were carefully reviewed and selected from 57 submissions. The main goal of the CIBB meetings is to provide a forum open to researchers from different disciplines to present and discuss problems concerning computational techniques in tools for bioinformatics, gene expression analysis and new perspectives in bioinformatics together with 4 special sessions on using game-theoretical tools in bioinformatics, combining Bayesian and machine learning approaches in bioinformatics: state of the art and future perspectives, data clustering and bioinformatics (DCB 2009) and on intelligent systems for medical decisions support (ISMDS 2009).
Download or read book Introduction to Protein Structure Prediction written by Huzefa Rangwala and published by John Wiley & Sons. This book was released on 2011-03-16 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: A look at the methods and algorithms used to predict protein structure A thorough knowledge of the function and structure of proteins is critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this reference sheds light on the methods used for protein structure prediction and reveals the key applications of modeled structures. This indispensable book covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, readers will find an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction and they will acquire unique insight into the future applications of the modeled protein structures. The book begins with a thorough introduction to the protein structure prediction problem and is divided into four themes: a background on structure prediction, the prediction of structural elements, tertiary structure prediction, and functional insights. Within those four sections, the following topics are covered: Databases and resources that are commonly used for protein structure prediction The structure prediction flagship assessment (CASP) and the protein structure initiative (PSI) Definitions of recurring substructures and the computational approaches used for solving sequence problems Difficulties with contact map prediction and how sophisticated machine learning methods can solve those problems Structure prediction methods that rely on homology modeling, threading, and fragment assembly Hybrid methods that achieve high-resolution protein structures Parts of the protein structure that may be conserved and used to interact with other biomolecules How the loop prediction problem can be used for refinement of the modeled structures The computational model that detects the differences between protein structure and its modeled mutant Whether working in the field of bioinformatics or molecular biology research or taking courses in protein modeling, readers will find the content in this book invaluable.
Download or read book Computational Intelligence Methods for Bioinformatics and Biostatistics written by Elia Biganzoli and published by Springer Science & Business Media. This book was released on 2012-12-11 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the 8th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2011, held in Gargnano del Garda, Italy, in June/July 2011. The 19 papers, presented together with 2 keynote speeches, were carefully reviewed and selected from 24 submissions. The papers are organized in topical sections on statistical learning, genomics, computational intelligence for health at the edge, proteomics, intelligent clinical decision support systems (i-CDSS), bioinformatics, and data clustering.
Download or read book Computational Intelligence Methods for Bioinformatics and Biostatistics written by Riccardo Rizzo and published by Springer. This book was released on 2011-07-18 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of the 7th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2010, held in Palermo, Italy, in September 2010. The 19 papers, presented together with 2 keynote speeches and 1 tutorial, were carefully reviewed and selected from 24 submissions. The papers are organized in topical sections on sequence analysis, promoter analysis and identification of transcription factor binding sites; methods for the unsupervised analysis, validation and visualization of structures discovered in bio-molecular data -- prediction of secondary and tertiary protein structures; gene expression data analysis; bio-medical text mining and imaging -- methods for diagnosis and prognosis; mathematical modelling and simulation of biological systems; and intelligent clinical decision support systems (i-CDSS).
