Download or read book Repetitive Structures in Biological Sequences and Applications in High Throughput Technologies written by Pavlos Antoniou and published by . This book was released on 2009 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Repetitive Structures in Biological Sequences Algorithms and Applications written by Marco Pellegrini and published by Frontiers Media SA. This book was released on 2016-10-27 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: Repetitive structures in biological sequences are emerging as an active focus of research and the unifying concept of "repeatome" (the ensemble of knowledge associated with repeating structures in genomic/proteomic sequences) has been recently proposed in order to highlight several converging trends. One main trend is the ongoing discovery that genomic repetitions are linked to many biological significant events and functions. Diseases (e.g. Huntington's disease) have been causally linked with abnormal expansion of certain repeating sequences in the human genome. Deletions or multiple copy duplications of genes (Copy Number Variations) are important in the aetiology of cancer, Alzheimer, and Parkinson diseases. A second converging trend has been the emergence of many different models and algorithms for detecting non-obvious repeating patterns in strings with applications to in genomic data. Borrowing methodologies from combinatorial pattern, matching, string algorithms, data structures, data mining and machine learning these new approaches break the limitations of the current approaches and offer a new way to design better trans-disciplinary research. The articles collected in this book provides a glance into the rich emerging area of repeatome research, addressing some of its pressing challenges. We believe that these contributions are valuable resources for repeatome research and will stimulate further research from bioinformatic, statistical, and biological points of view.
Download or read book Biological Sequence Analysis written by Richard Durbin and published by Cambridge University Press. This book was released on 1998-04-23 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
Download or read book Computational Tools for High throughput Discovery in Biology written by Neil Christopher Jones and published by . This book was released on 2007 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finally, we present a framework for application scheduling that is specifically targeted at computational scientists. This framework allows for the selection of scheduling objective function, but generally aims at dependability over speed because of the inherent need for reproducibility of results.
Download or read book Introduction to Computational Biology written by Michael S. Waterman and published by CRC Press. This book was released on 2018-05-02 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biology is in the midst of a era yielding many significant discoveries and promising many more. Unique to this era is the exponential growth in the size of information-packed databases. Inspired by a pressing need to analyze that data, Introduction to Computational Biology explores a new area of expertise that emerged from this fertile field- the combination of biological and information sciences. This introduction describes the mathematical structure of biological data, especially from sequences and chromosomes. After a brief survey of molecular biology, it studies restriction maps of DNA, rough landmark maps of the underlying sequences, and clones and clone maps. It examines problems associated with reading DNA sequences and comparing sequences to finding common patterns. The author then considers that statistics of pattern counts in sequences, RNA secondary structure, and the inference of evolutionary history of related sequences. Introduction to Computational Biology exposes the reader to the fascinating structure of biological data and explains how to treat related combinatorial and statistical problems. Written to describe mathematical formulation and development, this book helps set the stage for even more, truly interdisciplinary work in biology.
Download or read book Multiple Biological Sequence Alignment written by Ken Nguyen and published by John Wiley & Sons. This book was released on 2016-07-18 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covers the fundamentals and techniques of multiple biological sequence alignment and analysis, and shows readers how to choose the appropriate sequence analysis tools for their tasks This book describes the traditional and modern approaches in biological sequence alignment and homology search. This book contains 11 chapters, with Chapter 1 providing basic information on biological sequences. Next, Chapter 2 contains fundamentals in pair-wise sequence alignment, while Chapters 3 and 4 examine popular existing quantitative models and practical clustering techniques that have been used in multiple sequence alignment. Chapter 5 describes, characterizes and relates many multiple sequence alignment models. Chapter 6 describes how traditionally phylogenetic trees have been constructed, and available sequence knowledge bases can be used to improve the accuracy of reconstructing phylogeny trees. Chapter 7 covers the latest methods developed to improve the run-time efficiency of multiple sequence alignment. Next, Chapter 8 covers several popular existing multiple sequence alignment server and services, and Chapter 9 examines several multiple sequence alignment techniques that have been developed to handle short sequences (reads) produced by the Next Generation Sequencing technique (NSG). Chapter 10 describes a Bioinformatics application using multiple sequence alignment of short reads or whole genomes as input. Lastly, Chapter 11 provides a review of RNA and protein secondary structure prediction using the evolution information inferred from multiple sequence alignments. • Covers the full spectrum of the field, from alignment algorithms to scoring methods, practical techniques, and alignment tools and their evaluations • Describes theories and developments of scoring functions and scoring matrices •Examines phylogeny estimation and large-scale homology search Multiple Biological Sequence Alignment: Scoring Functions, Algorithms and Applications is a reference for researchers, engineers, graduate and post-graduate students in bioinformatics, and system biology and molecular biologists. Ken Nguyen, PhD, is an associate professor at Clayton State University, GA, USA. He received his PhD, MSc and BSc degrees in computer science all from Georgia State University. His research interests are in databases, parallel and distribute computing and bioinformatics. He was a Molecular Basis of Disease fellow at Georgia State and is the recipient of the highest graduate honor at Georgia State, the William M. Suttles Graduate Fellowship. Xuan Guo, PhD, is a postdoctoral associate at Oak Ridge National Lab, USA. He received his PhD degree in computer science from Georgia State University in 2015. His research interests are in bioinformatics, machine leaning, and cloud computing. He is an editorial assistant of International Journal of Bioinformatics Research and Applications. Yi Pan, PhD, is a Regents' Professor of Computer Science and an Interim Associate Dean and Chair of Biology at Georgia State University. He received his BE and ME in computer engineering from Tsinghua University in China and his PhD in computer science from the University of Pittsburgh. Dr. Pan's research interests include parallel and distributed computing, optical networks, wireless networks and bioinformatics. He has published more than 180 journal papers with about 60 papers published in various IEEE/ACM journals. He is co-editor along with Albert Y. Zomaya of the Wiley Series in Bioinformatics.
Download or read book Computational Genomics with R written by Altuna Akalin and published by CRC Press. This book was released on 2020-12-16 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Download or read book Application of Intelligent Systems in Multi modal Information Analytics written by Vijayan Sugumaran and published by Springer Nature. This book was released on 2021-04-16 with total page 970 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides comprehensive coverage of the latest advances and trends in information technology, science and engineering. Specifically, it addresses a number of broad themes, including multi-modal informatics, data mining, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies. The contributions cover a wide range of topics such as AI applications and innovations in health and education informatics; data and knowledge management; multi-modal application management; and web/social media mining for multi-modal informatics. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals, and a useful reference guide for newcomers to the field. This book is a compilation of the papers presented in the 2021 International Conference on Multi-modal Information Analytics, held in Huhehaote, China, on April 23–24, 2021.
Download or read book Identification and Application of Repetitive Biological Sequences written by Xuehui Li and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: Biological sequences are rich in repeats. For example, more than 50% of the human genome consists of repeats and approximately one-quarter of the amino acids are in repeats. Repeats are subsequences of biased composition. They vary in size from less than a hundred bases to tens of kilobases. They are found as either tandem arrays or dispersed throughout the genome. Repeats can generate insertions, deletions, and unequal crossing-over within genomes and affect protein functions. Hence, repeats play important roles in genome evolution. Repeat identification is normally the first step of studying repeats and a critical part of sequence analysis. For protein sequences, some repeats are popularly referred as low complexity regions (LCRs). Although some computational tools have been developed to identify genomic repeats or LCRs, they all are geared toward specific situations and suffer from different problems. We develop novel methods to identify genomic repeats and LCRs, respectively. Genomic repeats and LCRs present difficulties in genome annotation and analyses. Local alignments between repeats cause many false positives to sequence similarity search. These false positives can cause misassembly of genome sequences or misidentification of repeats as gene/protein sequences. Existing sequence similarity search algorithms either ignore the existence of these repeats or completely remove them. The first strategy produces false positives. The second strategy is not desirable, since no LCR-identification tool is 100% accurate. We develop new algorithms that use LCR information wisely to improve the accuracy and efficiency of sequence search.
Download or read book Data Processing Handbook for Complex Biological Data Sources written by Gauri Misra and published by Academic Press. This book was released on 2019-03-23 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Processing Handbook for Complex Biological Data provides relevant and to the point content for those who need to understand the different types of biological data and the techniques to process and interpret them. The book includes feedback the editor received from students studying at both undergraduate and graduate levels, and from her peers. In order to succeed in data processing for biological data sources, it is necessary to master the type of data and general methods and tools for modern data processing. For instance, many labs follow the path of interdisciplinary studies and get their data validated by several methods. Researchers at those labs may not perform all the techniques themselves, but either in collaboration or through outsourcing, they make use of a range of them, because, in the absence of cross validation using different techniques, the chances for acceptance of an article for publication in high profile journals is weakened. Explains how to interpret enormous amounts of data generated using several experimental approaches in simple terms, thus relating biology and physics at the atomic level Presents sample data files and explains the usage of equations and web servers cited in research articles to extract useful information from their own biological data Discusses, in detail, raw data files, data processing strategies, and the web based sources relevant for data processing
Download or read book Evolution of Translational Omics written by Institute of Medicine and published by National Academies Press. This book was released on 2012-09-13 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.
Download or read book BIOTECHNOLOGY Volume VIII written by Horst W. Doelle and published by EOLSS Publications. This book was released on 2009-11-16 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Encyclopedia of Biotechnology is a component of the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Biotechnology draws on the pure biological sciences (genetics, animal cell culture, molecular biology, microbiology, biochemistry, embryology, cell biology) and in many instances is also dependent on knowledge and methods from outside the sphere of biology (chemical engineering, bioprocess engineering, information technology, biorobotics). This 15-volume set contains several chapters, each of size 5000-30000 words, with perspectives, applications and extensive illustrations. It carries state-of-the-art knowledge in the field and is aimed, by virtue of the several applications, at the following five major target audiences: University and College Students, Educators, Professional Practitioners, Research Personnel and Policy Analysts, Managers, and Decision Makers and NGOs.
Download or read book Current Frontiers and Perspectives in Cell Biology written by Stevo Najman and published by BoD – Books on Demand. This book was released on 2012-04-25 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: A numerous internationally renowned authors in the pages of this book present the views of the fields of cell biology and their own research results or review of current knowledge. Chapters are divided into five sections that are dedicated to cell structures and functions, genetic material, regulatory mechanisms, cellular biomedicine and new methods in cell biology. Multidisciplinary and often quite versatile approach by many authors have imposed restrictions of this classification, so it is certain that many chapters could belong to the other sections of this book. The current frontiers, on the manner in which they described in the book, can be a good inspiration to many readers for further improving, and perspectives which are highlighted can be seen in many areas of fundamental biology, biomedicine, biotechnology and other applications of knowledge of cell biology. The book will be very useful for beginners to gain insight into new area, as well as experts to find new facts and expanding horizons.
Download or read book Systems Medicine written by and published by Academic Press. This book was released on 2020-08-24 with total page 1571 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological advances in generated molecular and cell biological data are transforming biomedical research. Sequencing, multi-omics and imaging technologies are likely to have deep impact on the future of medical practice. In parallel to technological developments, methodologies to gather, integrate, visualize and analyze heterogeneous and large-scale data sets are needed to develop new approaches for diagnosis, prognosis and therapy. Systems Medicine: Integrative, Qualitative and Computational Approaches is an innovative, interdisciplinary and integrative approach that extends the concept of systems biology and the unprecedented insights that computational methods and mathematical modeling offer of the interactions and network behavior of complex biological systems, to novel clinically relevant applications for the design of more successful prognostic, diagnostic and therapeutic approaches. This 3 volume work features 132 entries from renowned experts in the fields and covers the tools, methods, algorithms and data analysis workflows used for integrating and analyzing multi-dimensional data routinely generated in clinical settings with the aim of providing medical practitioners with robust clinical decision support systems. Importantly the work delves into the applications of systems medicine in areas such as tumor systems biology, metabolic and cardiovascular diseases as well as immunology and infectious diseases amongst others. This is a fundamental resource for biomedical students and researchers as well as medical practitioners who need to need to adopt advances in computational tools and methods into the clinical practice. Encyclopedic coverage: ‘one-stop’ resource for access to information written by world-leading scholars in the field of Systems Biology and Systems Medicine, with easy cross-referencing of related articles to promote understanding and further research Authoritative: the whole work is authored and edited by recognized experts in the field, with a range of different expertise, ensuring a high quality standard Digitally innovative: Hyperlinked references and further readings, cross-references and diagrams/images will allow readers to easily navigate a wealth of information
Download or read book Diagnostic Molecular Biology written by Chang-Hui Shen and published by Elsevier. This book was released on 2023-06-29 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diagnostic Molecular Biology, Second Edition describes the fundamentals of molecular biology in a clear, concise manner with each technique explained within its conceptual framework and current applications of clinical laboratory techniques comprehensively covered. This targeted approach covers the principles of molecular biology, including basic knowledge of nucleic acids, proteins and chromosomes; the basic techniques and instrumentations commonly used in the field of molecular biology, including detailed procedures and explanations; and the applications of the principles and techniques currently employed in the clinical laboratory. Topics such as whole exome sequencing, whole genome sequencing, RNA-seq, and ChIP-seq round out the discussion. Fully updated, this new edition adds recent advances in the detection of respiratory virus infections in humans, like influenza, RSV, hAdV, hRV but also corona. This book expands the discussion on NGS application and its role in future precision medicine. Provides explanations on how techniques are used to diagnosis at the molecular level Explains how to use information technology to communicate and assess results in the lab Enhances our understanding of fundamental molecular biology and places techniques in context Places protocols into context with practical applications Includes extra chapters on respiratory viruses (Corona)
Download or read book Fundamental Neuropathology for Pathologists and Toxicologists written by Brad Bolon and published by John Wiley & Sons. This book was released on 2011-08-08 with total page 661 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers pathologists, toxicologists, other medical professionals, and students an introduction to the discipline and techniques of neuropathology – including chemical and environmental, biological, medical, and regulatory details important for performing an analysis of toxicant-induced neurodiseases. In addition to a section on fundamentals, the book provides detailed coverage of current practices (bioassays, molecular analysis, and nervous system pathology) and practical aspects (data interpretation, regulatory considerations, and tips for preparing reports).
Download or read book Hands on Data Science for Biologists Using Python written by Yasha Hasija and published by CRC Press. This book was released on 2021-04-08 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hands-on Data Science for Biologists using Python has been conceptualized to address the massive data handling needs of modern-day biologists. With the advent of high throughput technologies and consequent availability of omics data, biological science has become a data-intensive field. This hands-on textbook has been written with the inception of easing data analysis by providing an interactive, problem-based instructional approach in Python programming language. The book starts with an introduction to Python and steadily delves into scrupulous techniques of data handling, preprocessing, and visualization. The book concludes with machine learning algorithms and their applications in biological data science. Each topic has an intuitive explanation of concepts and is accompanied with biological examples. Features of this book: The book contains standard templates for data analysis using Python, suitable for beginners as well as advanced learners. This book shows working implementations of data handling and machine learning algorithms using real-life biological datasets and problems, such as gene expression analysis; disease prediction; image recognition; SNP association with phenotypes and diseases. Considering the importance of visualization for data interpretation, especially in biological systems, there is a dedicated chapter for the ease of data visualization and plotting. Every chapter is designed to be interactive and is accompanied with Jupyter notebook to prompt readers to practice in their local systems. Other avant-garde component of the book is the inclusion of a machine learning project, wherein various machine learning algorithms are applied for the identification of genes associated with age-related disorders. A systematic understanding of data analysis steps has always been an important element for biological research. This book is a readily accessible resource that can be used as a handbook for data analysis, as well as a platter of standard code templates for building models.
