Bioinformatics in the Era of Post Genomics and Big Data

Bioinformatics in the Era of Post Genomics and Big Data

Author: Ibrokhim Y. Abdurakhmonov

Publisher: BoD – Books on Demand

Published: 2018-06-20

Total Pages: 190

ISBN-13: 1789232686

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Bioinformatics has evolved significantly in the era of post genomics and big data. Huge advancements were made toward storing, handling, mining, comparing, extracting, clustering and analysis as well as visualization of big macromolecular data using novel computational approaches, machine and deep learning methods, and web-based server tools. There are extensively ongoing world-wide efforts to build the resources for regional hosting, organized and structured access and improving the pre-existing bioinformatics tools to efficiently and meaningfully analyze day-to-day increasing big data. This book intends to provide the reader with updates and progress on genomic data analysis, data modeling and network-based system tools.


Gene Quantification

Gene Quantification

Author: Francois Ferre

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 379

ISBN-13: 1461241642

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Geneticists and molecular biologists have been interested in quantifying genes and their products for many years and for various reasons (Bishop, 1974). Early molecular methods were based on molecular hybridization, and were devised shortly after Marmur and Doty (1961) first showed that denaturation of the double helix could be reversed - that the process of molecular reassociation was exquisitely sequence dependent. Gillespie and Spiegelman (1965) developed a way of using the method to titrate the number of copies of a probe within a target sequence in which the target sequence was fixed to a membrane support prior to hybridization with the probe - typically a RNA. Thus, this was a precursor to many of the methods still in use, and indeed under development, today. Early examples of the application of these methods included the measurement of the copy numbers in gene families such as the ribosomal genes and the immunoglo bulin family. Amplification of genes in tumors and in response to drug treatment was discovered by this method. In the same period, methods were invented for estimating gene num bers based on the kinetics of the reassociation process - the so-called Cot analysis. This method, which exploits the dependence of the rate of reassociation on the concentration of the two strands, revealed the presence of repeated sequences in the DNA of higher eukaryotes (Britten and Kohne, 1968). An adaptation to RNA, Rot analysis (Melli and Bishop, 1969), was used to measure the abundance of RNAs in a mixed population.


Big Data Analytics in Bioinformatics and Healthcare

Big Data Analytics in Bioinformatics and Healthcare

Author: Wang, Baoying

Publisher: IGI Global

Published: 2014-10-31

Total Pages: 552

ISBN-13: 1466666129

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As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.


Bioinformatics

Bioinformatics

Author: Dev Bukhsh Singh

Publisher: Academic Press

Published: 2021-10-21

Total Pages: 512

ISBN-13: 0323900054

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Bioinformatics: Methods and Applications provides a thorough and detailed description of principles, methods, and applications of bioinformatics in different areas of life sciences. It presents a compendium of many important topics of current advanced research and basic principles/approaches easily applicable to diverse research settings. The content encompasses topics such as biological databases, sequence analysis, genome assembly, RNA sequence data analysis, drug design, and structural and functional analysis of proteins. In addition, it discusses computational approaches for vaccine design, systems biology and big data analysis, and machine learning in bioinformatics.It is a valuable source for bioinformaticians, computer biologists, and members of biomedical field who needs to learn bioinformatics approaches to apply to their research and lab activities. - Covers basic and more advanced developments of bioinformatics with a diverse and interdisciplinary approach to fulfill the needs of readers from different backgrounds - Explains in a practical way how to decode complex biological problems using computational approaches and resources - Brings case studies, real-world examples and several protocols to guide the readers with a problem-solving approach


Postgenomics

Postgenomics

Author: Sarah S. Richardson

Publisher: Duke University Press

Published: 2015-05-29

Total Pages: 286

ISBN-13: 0822375443

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Ten years after the Human Genome Project’s completion the life sciences stand in a moment of uncertainty, transition, and contestation. The postgenomic era has seen rapid shifts in research methodology, funding, scientific labor, and disciplinary structures. Postgenomics is transforming our understanding of disease and health, our environment, and the categories of race, class, and gender. At the same time, the gene retains its centrality and power in biological and popular discourse. The contributors to Postgenomics analyze these ruptures and continuities and place them in historical, social, and political context. Postgenomics, they argue, forces a rethinking of the genome itself, and opens new territory for conversations between the social sciences, humanities, and life sciences. Contributors. Russ Altman, Rachel A. Ankeny, Catherine Bliss, John Dupré, Michael Fortun, Evelyn Fox Keller, Sabina Leonelli, Adrian Mackenzie, Margot Moinester, Aaron Panofsky, Sarah S. Richardson, Sara Shostak, Hallam Stevens


Topological Data Analysis for Genomics and Evolution

Topological Data Analysis for Genomics and Evolution

Author: Raúl Rabadán

Publisher: Cambridge University Press

Published: 2019-10-31

Total Pages: 521

ISBN-13: 1108753396

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Biology has entered the age of Big Data. The technical revolution has transformed the field, and extracting meaningful information from large biological data sets is now a central methodological challenge. Algebraic topology is a well-established branch of pure mathematics that studies qualitative descriptors of the shape of geometric objects. It aims to reduce questions to a comparison of algebraic invariants, such as numbers, which are typically easier to solve. Topological data analysis is a rapidly-developing subfield that leverages the tools of algebraic topology to provide robust multiscale analysis of data sets. This book introduces the central ideas and techniques of topological data analysis and its specific applications to biology, including the evolution of viruses, bacteria and humans, genomics of cancer and single cell characterization of developmental processes. Bridging two disciplines, the book is for researchers and graduate students in genomics and evolutionary biology alongside mathematicians interested in applied topology.


Bioinformatics Data Skills

Bioinformatics Data Skills

Author: Vince Buffalo

Publisher: "O'Reilly Media, Inc."

Published: 2015-07

Total Pages: 538

ISBN-13: 1449367518

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Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, youâ??ll learn how to use freely available open source tools to extract meaning from large complex biological data sets. At no other point in human history has our ability to understand lifeâ??s complexities been so dependent on our skills to work with and analyze data. This intermediate-level book teaches the general computational and data skills you need to analyze biological data. If you have experience with a scripting language like Python, youâ??re ready to get started. Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Process bioinformatics data with powerful Unix pipelines and data tools Learn how to use exploratory data analysis techniques in the R language Use efficient methods to work with genomic range data and range operations Work with common genomics data file formats like FASTA, FASTQ, SAM, and BAM Manage your bioinformatics project with the Git version control system Tackle tedious data processing tasks with with Bash scripts and Makefiles


Artificial Intelligence

Artificial Intelligence

Author:

Publisher: BoD – Books on Demand

Published: 2019-07-31

Total Pages: 142

ISBN-13: 1789840171

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Artificial intelligence (AI) is taking on an increasingly important role in our society today. In the early days, machines fulfilled only manual activities. Nowadays, these machines extend their capabilities to cognitive tasks as well. And now AI is poised to make a huge contribution to medical and biological applications. From medical equipment to diagnosing and predicting disease to image and video processing, among others, AI has proven to be an area with great potential. The ability of AI to make informed decisions, learn and perceive the environment, and predict certain behavior, among its many other skills, makes this application of paramount importance in today's world. This book discusses and examines AI applications in medicine and biology as well as challenges and opportunities in this fascinating area.


Advances in Bioinformatics

Advances in Bioinformatics

Author: Vijai Singh

Publisher: Springer Nature

Published: 2021-07-31

Total Pages: 446

ISBN-13: 9813361913

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This book presents the latest developments in bioinformatics, highlighting the importance of bioinformatics in genomics, transcriptomics, metabolism and cheminformatics analysis, as well as in drug discovery and development. It covers tools, data mining and analysis, protein analysis, computational vaccine, and drug design. Covering cheminformatics, computational evolutionary biology and the role of next-generation sequencing and neural network analysis, it also discusses the use of bioinformatics tools in the development of precision medicine. This book offers a valuable source of information for not only beginners in bioinformatics, but also for students, researchers, scientists, clinicians, practitioners, policymakers, and stakeholders who are interested in harnessing the potential of bioinformatics in many areas.


Applied Bioinformatics

Applied Bioinformatics

Author: Paul Maria Selzer

Publisher: Springer Science & Business Media

Published: 2008-01-18

Total Pages: 297

ISBN-13: 3540728007

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At last, here is a baseline book for anyone who is confused by cryptic computer programs, algorithms and formulae, but wants to learn about applied bioinformatics. Now, anyone who can operate a PC, standard software and the internet can also learn to understand the biological basis of bioinformatics, of the existence as well as the source and availability of bioinformatics software, and how to apply these tools and interpret results with confidence. This process is aided by chapters that introduce important aspects of bioinformatics, detailed bioinformatics exercises (including solutions), and to cap it all, a glossary of definitions and terminology relating to bioinformatics.