Gene Prediction

Author : Martin Kollmar
Publisher : Humana Press
ISBN 13 : 9781493991723
Total Pages : 284 pages
Book Rating : 4.28/5 ( download)

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Download or read book Gene Prediction written by Martin Kollmar and published by Humana Press. This book was released on 2019-05-19 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume introduces software used for gene prediction with focus on eukaryotic genomes. The chapters in this book describe software and web server usage as applied in common use-cases, and explain ways to simplify re-annotation of long available genome assemblies. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary computational requirements, step-by-step, readily reproducible computational protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Gene Prediction: Methods and Protocols is a valuable resource for researchers and research groups working on the assembly and annotation of single species or small groups of species. Chapter 3 is available open access under a CC BY 4.0 license via link.springer.com.

Author : William H. Majoros
Publisher :
ISBN 13 :
Total Pages : 456 pages
Book Rating : 4.28/5 ( download)

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Download or read book Methods for Computational Gene Prediction written by William H. Majoros and published by . This book was released on 2007-08-16 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: A self-contained, rigorous text describing models used to identify genes in genomic DNA sequences.

Author : Jin Xiong
Publisher : Cambridge University Press
ISBN 13 : 113945062X
Total Pages : 360 pages
Book Rating : 4.21/5 ( download)

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Download or read book Essential Bioinformatics written by Jin Xiong and published by Cambridge University Press. This book was released on 2006-03-13 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essential Bioinformatics is a concise yet comprehensive textbook of bioinformatics, which provides a broad introduction to the entire field. Written specifically for a life science audience, the basics of bioinformatics are explained, followed by discussions of the state-of-the-art computational tools available to solve biological research problems. All key areas of bioinformatics are covered including biological databases, sequence alignment, genes and promoter prediction, molecular phylogenetics, structural bioinformatics, genomics and proteomics. The book emphasizes how computational methods work and compares the strengths and weaknesses of different methods. This balanced yet easily accessible text will be invaluable to students who do not have sophisticated computational backgrounds. Technical details of computational algorithms are explained with a minimum use of mathematical formulae; graphical illustrations are used in their place to aid understanding. The effective synthesis of existing literature as well as in-depth and up-to-date coverage of all key topics in bioinformatics make this an ideal textbook for all bioinformatics courses taken by life science students and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research.

Author : Mukhdeep Singh Manshahia
Publisher : John Wiley & Sons
ISBN 13 : 1119792622
Total Pages : 944 pages
Book Rating : 4.28/5 ( download)

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Download or read book Handbook of Intelligent Computing and Optimization for Sustainable Development written by Mukhdeep Singh Manshahia and published by John Wiley & Sons. This book was released on 2022-02-11 with total page 944 pages. Available in PDF, EPUB and Kindle. Book excerpt: HANDBOOK OF INTELLIGENT COMPUTING AND OPTIMIZATION FOR SUSTAINABLE DEVELOPMENT This book provides a comprehensive overview of the latest breakthroughs and recent progress in sustainable intelligent computing technologies, applications, and optimization techniques across various industries. Optimization has received enormous attention along with the rapidly increasing use of communication technology and the development of user-friendly software and artificial intelligence. In almost all human activities, there is a desire to deliver the highest possible results with the least amount of effort. Moreover, optimization is a very well-known area with a vast number of applications, from route finding problems to medical treatment, construction, finance, accounting, engineering, and maintenance schedules in plants. As far as optimization of real-world problems is concerned, understanding the nature of the problem and grouping it in a proper class may help the designer employ proper techniques which can solve the problem efficiently. Many intelligent optimization techniques can find optimal solutions without the use of objective function and are less prone to local conditions. The 41 chapters comprising the Handbook of Intelligent Computing and Optimization for Sustainable Development by subject specialists, represent diverse disciplines such as mathematics and computer science, electrical and electronics engineering, neuroscience and cognitive sciences, medicine, and social sciences, and provide the reader with an integrated understanding of the importance that intelligent computing has in the sustainable development of current societies. It discusses the emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative intelligent techniques in a variety of sectors, including IoT, manufacturing, optimization, and healthcare. Audience It is a pivotal reference source for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in the field of artificial intelligence in the areas of Internet of Things, renewable energy, optimization, and smart cities.

Author : Md. Zia Ur Rahman
Publisher : CRC Press
ISBN 13 : 1000375153
Total Pages : 202 pages
Book Rating : 4.52/5 ( download)

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Download or read book Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms written by Md. Zia Ur Rahman and published by CRC Press. This book was released on 2021-06-30 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the issue of improving the accuracy in exon prediction in DNA sequences using various adaptive techniques based on different performance measures that are crucial in disease diagnosis and therapy. First, the authors present an overview of genomics engineering, structure of DNA sequence and its building blocks, genetic information flow in a cell, gene prediction along with its significance, and various types of gene prediction methods, followed by a review of literature starting with the biological background of genomic sequence analysis. Next, they cover various theoretical considerations of adaptive filtering techniques used for DNA analysis, with an introduction to adaptive filtering, properties of adaptive algorithms, and the need for development of adaptive exon predictors (AEPs) and structure of AEP used for DNA analysis. Then, they extend the approach of least mean squares (LMS) algorithm and its sign-based realizations with normalization factor for DNA analysis. They also present the normalized logarithmic-based realizations of least mean logarithmic squares (LMLS) and least logarithmic absolute difference (LLAD) adaptive algorithms that include normalized LMLS (NLMLS) algorithm, normalized LLAD (NLLAD) algorithm, and their signed variants. This book ends with an overview of the goals achieved and highlights the primary achievements using all proposed techniques. This book is intended to provide rigorous use of adaptive signal processing algorithms for genetic engineering, biomedical engineering, and bioinformatics and is useful for undergraduate and postgraduate students. This will also serve as a practical guide for Ph.D. students and researchers and will provide a number of research directions for further work. Features Presents an overview of genomics engineering, structure of DNA sequence and its building blocks, genetic information flow in a cell, gene prediction along with its significance, and various types of gene prediction methods Covers various theoretical considerations of adaptive filtering techniques used for DNA analysis, introduction to adaptive filtering, properties of adaptive algorithms, need for development of adaptive exon predictors (AEPs), and structure of AEP used for DNA analysis Extends the approach of LMS algorithm and its sign-based realizations with normalization factor for DNA analysis Presents the normalized logarithmic-based realizations of LMLS and LLAD adaptive algorithms that include normalized LMLS (NLMLS) algorithm, normalized LLAD (NLLAD) algorithm, and their signed variants Provides an overview of the goals achieved and highlights the primary achievements using all proposed techniques Dr. Md. Zia Ur Rahman is a professor in the Department of Electronics and Communication Engineering at Koneru Lakshmaiah Educational Foundation (K. L. University), Guntur, India. His current research interests include adaptive signal processing, biomedical signal processing, genetic engineering, medical imaging, array signal processing, medical telemetry, and nanophotonics. Dr. Srinivasareddy Putluri is currently a Software Engineer at Tata Consultancy Services Ltd., Hyderabad. He received his Ph.D. degree (Genomic Signal Processing using Adaptive Signal Processing algorithms) from the Department of Electronics and Communication Engineering at Koneru Lakshmaiah Educational Foundation (K. L. University), Guntur, India. His research interests include genomic signal processing and adaptive signal processing. He has published 15 research papers in various journals and proceedings. He is currently a reviewer of publishers like the IEEE Access and IGI.

Author : Bruce Alberts
Publisher :
ISBN 13 : 9780815332183
Total Pages : 0 pages
Book Rating : 4.81/5 ( download)

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Download or read book Molecular Biology of The Cell written by Bruce Alberts and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Eugene V. Koonin
Publisher : Springer Science & Business Media
ISBN 13 : 1475737831
Total Pages : 482 pages
Book Rating : 4.37/5 ( download)

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Download or read book Sequence — Evolution — Function written by Eugene V. Koonin and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.

Author : Nils Stein
Publisher : Springer
ISBN 13 : 3319925288
Total Pages : 394 pages
Book Rating : 4.88/5 ( download)

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Download or read book The Barley Genome written by Nils Stein and published by Springer. This book was released on 2018-08-18 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview of the state-of-the-art in barley genome analysis, covering all aspects of sequencing the genome and translating this important information into new knowledge in basic and applied crop plant biology and new tools for research and crop improvement. Unlimited access to a high-quality reference sequence is removing one of the major constraints in basic and applied research. This book summarizes the advanced knowledge of the composition of the barley genome, its genes and the much larger non-coding part of the genome, and how this information facilitates studying the specific characteristics of barley. One of the oldest domesticated crops, barley is the small grain cereal species that is best adapted to the highest altitudes and latitudes, and it exhibits the greatest tolerance to most abiotic stresses. With comprehensive access to the genome sequence, barley’s importance as a genetic model in comparative studies on crop species like wheat, rye, oats and even rice is likely to increase.

Author : Md. Zia Ur Rahman
Publisher : CRC Press
ISBN 13 : 1000375226
Total Pages : 227 pages
Book Rating : 4.20/5 ( download)

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Download or read book Genomic Sequence Analysis for Exon Prediction Using Adaptive Signal Processing Algorithms written by Md. Zia Ur Rahman and published by CRC Press. This book was released on 2021-06-30 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the issue of improving the accuracy in exon prediction in DNA sequences using various adaptive techniques based on different performance measures that are crucial in disease diagnosis and therapy. First, the authors present an overview of genomics engineering, structure of DNA sequence and its building blocks, genetic information flow in a cell, gene prediction along with its significance, and various types of gene prediction methods, followed by a review of literature starting with the biological background of genomic sequence analysis. Next, they cover various theoretical considerations of adaptive filtering techniques used for DNA analysis, with an introduction to adaptive filtering, properties of adaptive algorithms, and the need for development of adaptive exon predictors (AEPs) and structure of AEP used for DNA analysis. Then, they extend the approach of least mean squares (LMS) algorithm and its sign-based realizations with normalization factor for DNA analysis. They also present the normalized logarithmic-based realizations of least mean logarithmic squares (LMLS) and least logarithmic absolute difference (LLAD) adaptive algorithms that include normalized LMLS (NLMLS) algorithm, normalized LLAD (NLLAD) algorithm, and their signed variants. This book ends with an overview of the goals achieved and highlights the primary achievements using all proposed techniques. This book is intended to provide rigorous use of adaptive signal processing algorithms for genetic engineering, biomedical engineering, and bioinformatics and is useful for undergraduate and postgraduate students. This will also serve as a practical guide for Ph.D. students and researchers and will provide a number of research directions for further work. Features Presents an overview of genomics engineering, structure of DNA sequence and its building blocks, genetic information flow in a cell, gene prediction along with its significance, and various types of gene prediction methods Covers various theoretical considerations of adaptive filtering techniques used for DNA analysis, introduction to adaptive filtering, properties of adaptive algorithms, need for development of adaptive exon predictors (AEPs), and structure of AEP used for DNA analysis Extends the approach of LMS algorithm and its sign-based realizations with normalization factor for DNA analysis Presents the normalized logarithmic-based realizations of LMLS and LLAD adaptive algorithms that include normalized LMLS (NLMLS) algorithm, normalized LLAD (NLLAD) algorithm, and their signed variants Provides an overview of the goals achieved and highlights the primary achievements using all proposed techniques Dr. Md. Zia Ur Rahman is a professor in the Department of Electronics and Communication Engineering at Koneru Lakshmaiah Educational Foundation (K. L. University), Guntur, India. His current research interests include adaptive signal processing, biomedical signal processing, genetic engineering, medical imaging, array signal processing, medical telemetry, and nanophotonics. Dr. Srinivasareddy Putluri is currently a Software Engineer at Tata Consultancy Services Ltd., Hyderabad. He received his Ph.D. degree (Genomic Signal Processing using Adaptive Signal Processing algorithms) from the Department of Electronics and Communication Engineering at Koneru Lakshmaiah Educational Foundation (K. L. University), Guntur, India. His research interests include genomic signal processing and adaptive signal processing. He has published 15 research papers in various journals and proceedings. He is currently a reviewer of publishers like the IEEE Access and IGI.

Author : Marina Axelson-Fisk
Publisher : Springer
ISBN 13 : 1447166930
Total Pages : 396 pages
Book Rating : 4.31/5 ( download)

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Download or read book Comparative Gene Finding written by Marina Axelson-Fisk and published by Springer. This book was released on 2015-04-13 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a guide to building computational gene finders, and describes the state of the art in computational gene finding methods, with a focus on comparative approaches. Fully updated and expanded, this new edition examines next-generation sequencing (NGS) technology. The book also discusses conditional random fields, enhancing the broad coverage of topics spanning probability theory, statistics, information theory, optimization theory and numerical analysis. Features: introduces the fundamental terms and concepts in the field; discusses algorithms for single-species gene finding, and approaches to pairwise and multiple sequence alignments, then describes how the strengths in both areas can be combined to improve the accuracy of gene finding; explores the gene features most commonly captured by a computational gene model, and explains the basics of parameter training; illustrates how to implement a comparative gene finder; examines NGS techniques and how to build a genome annotation pipeline.