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Author: Shruti Mishra
Publisher: Academic Press
ISBN: 0128163577
Category : Science
Languages : en
Pages : 133
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Book Description
Integration and Visualization of Gene Selection and Gene Regulatory Networks for Cancer Genome helps readers identify and select the specific genes causing oncogenes. The book also addresses the validation of the selected genes using various classification techniques and performance metrics, making it a valuable source for cancer researchers, bioinformaticians, and researchers from diverse fields interested in applying systems biology approaches to their studies. - Provides well described techniques for the purpose of gene selection/feature selection for the generation of gene subsets - Presents and analyzes three different types of gene selection algorithms: Support Vector Machine-Bayesian T-Test-Recursive Feature Elimination (SVM-BT-RFE), Canonical Correlation Analysis-Trace Ratio (CCA-TR), and Signal-To-Noise Ratio-Trace Ratio (SNRTR) - Consolidates fundamental knowledge on gene datasets and current techniques on gene regulatory networks into a single resource
Author: Shruti Mishra
Publisher: Academic Press
ISBN: 0128163577
Category : Science
Languages : en
Pages : 133
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Book Description
Integration and Visualization of Gene Selection and Gene Regulatory Networks for Cancer Genome helps readers identify and select the specific genes causing oncogenes. The book also addresses the validation of the selected genes using various classification techniques and performance metrics, making it a valuable source for cancer researchers, bioinformaticians, and researchers from diverse fields interested in applying systems biology approaches to their studies. - Provides well described techniques for the purpose of gene selection/feature selection for the generation of gene subsets - Presents and analyzes three different types of gene selection algorithms: Support Vector Machine-Bayesian T-Test-Recursive Feature Elimination (SVM-BT-RFE), Canonical Correlation Analysis-Trace Ratio (CCA-TR), and Signal-To-Noise Ratio-Trace Ratio (SNRTR) - Consolidates fundamental knowledge on gene datasets and current techniques on gene regulatory networks into a single resource
Author: Alberto Fuente
Publisher: Springer Science & Business Media
ISBN: 3642451616
Category : Science
Languages : en
Pages : 135
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Book Description
This book presents recent methods for Systems Genetics (SG) data analysis, applying them to a suite of simulated SG benchmark datasets. Each of the chapter authors received the same datasets to evaluate the performance of their method to better understand which algorithms are most useful for obtaining reliable models from SG datasets. The knowledge gained from this benchmarking study will ultimately allow these algorithms to be used with confidence for SG studies e.g. of complex human diseases or food crop improvement. The book is primarily intended for researchers with a background in the life sciences, not for computer scientists or statisticians.
Author: Bor-Sen Chen
Publisher: Academic Press
ISBN: 0128173351
Category : Science
Languages : en
Pages : 673
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Book Description
Systems Immunology and Infection Microbiology provides a large amount of biological system models, diagrams and flowcharts to illustrate development procedures and help users understand the results of systems immunology and infection microbiology. Chapters discuss systems immunology, systems infection microbiology, systematic inflammation and immune responses in restoration and regeneration process, systems' innate and adaptive immunity in infection process, systematic genetic and epigenetic pathogenic/defensive mechanism during bacterial infection on human cells is introduced, and the systematic genetic and epigenetic pathogenic/defensive mechanisms during viral infection on human cells. This book provides new big data-driven and systems-driven systems immunology and infection microbiology to researchers applying systems biology and bioinformatics in their work. It is also invaluable to several members of biomedical field who are interested in learning more about those approaches. - Encompasses one applicable example in every chapter to illustrate the solution procedure from big data mining, network modeling, host/pathogen cross-talk detection, drug target identification and systems drug design - Presents flowcharts to represent the development procedure of systematic immunology and infection in a very clear format - Contains 100 color diagrams to help readers understand the related biological networks, their corresponding mechanisms, and significant network biomarkers for therapeutic drug design
Author: Isabelle S. Peter
Publisher: Academic Press
ISBN: 0124047467
Category : Science
Languages : en
Pages : 461
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Book Description
Genomic Control Process explores the biological phenomena around genomic regulatory systems that control and shape animal development processes, and which determine the nature of evolutionary processes that affect body plan. Unifying and simplifying the descriptions of development and evolution by focusing on the causality in these processes, it provides a comprehensive method of considering genomic control across diverse biological processes. This book is essential for graduate researchers in genomics, systems biology and molecular biology seeking to understand deep biological processes which regulate the structure of animals during development. - Covers a vast area of current biological research to produce a genome oriented regulatory bioscience of animal life - Places gene regulation, embryonic and postembryonic development, and evolution of the body plan in a unified conceptual framework - Provides the conceptual keys to interpret a broad developmental and evolutionary landscape with precise experimental illustrations drawn from contemporary literature - Includes a range of material, from developmental phenomenology to quantitative and logic models, from phylogenetics to the molecular biology of gene regulation, from animal models of all kinds to evidence of every relevant type - Demonstrates the causal power of system-level understanding of genomic control process - Conceptually organizes a constellation of complex and diverse biological phenomena - Investigates fundamental developmental control system logic in diverse circumstances and expresses these in conceptual models - Explores mechanistic evolutionary processes, illuminating the evolutionary consequences of developmental control systems as they are encoded in the genome
Author: Graham Dellaire
Publisher: Academic Press
ISBN: 0123972744
Category : Science
Languages : en
Pages : 511
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Book Description
Cancer Genomics addresses how recent technological advances in genomics are shaping how we diagnose and treat cancer. Built on the historical context of cancer genetics over the past 30 years, the book provides a snapshot of the current issues and state-of-the-art technologies used in cancer genomics. Subsequent chapters highlight how these approaches have informed our understanding of hereditary cancer syndromes and the diagnosis, treatment and outcome in a variety of adult and pediatric solid tumors and hematologic malignancies. The dramatic increase in cancer genomics research and ever-increasing availability of genomic testing are not without significant ethical issues, which are addressed in the context of the return of research results and the legal considerations underlying the commercialization of genomic discoveries. Finally, the book concludes with "Future Directions", examining the next great challenges to face the field of cancer genomics, namely the contribution of non-coding RNAs to disease pathogenesis and the interaction of the human genome with the environment. - Tools such as sidebars, key concept summaries, a glossary, and acronym and abbreviation definitions make this book highly accessible to researchers from several fields associated with cancer genomics. - Contributions from thought leaders provide valuable historical perspective to relate the advances in the field to current technologies and literature.
Author: Trygve O Tollefsbol
Publisher: Academic Press
ISBN: 0128194154
Category : Medical
Languages : en
Pages : 740
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Book Description
In recent years, the field of epigenetics has grown significantly, driving new understanding of human developmental processes and disease expression, as well as advances in diagnostics and therapeutics. As the field of epigenetics continues to grow, methods and technologies have multiplied, resulting in a wide range of approaches and tools researchers might employ. Epigenetics Methods offers comprehensive instruction in methods, protocols, and experimental approaches applied in field of epigenetics. Here, across thirty-five chapters, specialists offer step-by-step overviews of methods used to study various epigenetic mechanisms, as employed in basic and translational research. Leading the reader from fundamental to more advanced methods, the book begins with thorough instruction in DNA methylation techniques and gene or locus-specific methylation analyses, followed by histone modification methods, chromatin evaluation, enzyme analyses of histone methylation, and studies of non-coding RNAs as epigenetic modulators. Recently developed techniques and technologies discussed include single-cell epigenomics, epigenetic editing, computational epigenetics, systems biology epigenetic methods, and forensic epigenetic approaches. Epigenetics methods currently in-development, and their implication for future research, are also considered in-depth. In addition, as with the wider life sciences, reproducibility across experiments, labs, and subdisciplines is a growing issue for epigenetics researchers. This volume provides consensus-driven methods instruction and overviews. Tollefsbol and contributing authors survey the range of existing methods; identify best practices, common themes, and challenges; and bring unity of approach to a diverse and ever-evolving field. - Includes contributions by leading international investigators involved in epigenetic research and clinical and therapeutic application - Integrates technology and translation with fundamental chapters on epigenetics methods, as well as chapters on more novel and advanced epigenetics methods - Written at verbal and technical levels that can be understood by scientists and students alike - Includes chapters on state-of-the-art techniques such as single-cell epigenomics, use of CRISPR/Cas9 for epigenetic editing, and epigenetics methods applied to forensics
Author: Altuna Akalin
Publisher: CRC Press
ISBN: 1498781861
Category : Mathematics
Languages : en
Pages : 463
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Book Description
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.
Author: Francois Ferre
Publisher: Springer Science & Business Media
ISBN: 1461241642
Category : Medical
Languages : en
Pages : 379
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Book Description
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.
Author: Bernhard Palsson
Publisher: Cambridge University Press
ISBN: 1107038855
Category : Medical
Languages : en
Pages : 551
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Book Description
The first comprehensive single-authored textbook on genome-scale models and the bottom-up approach to systems biology.
Author: George Tseng
Publisher: Cambridge University Press
ISBN: 1107069114
Category : Mathematics
Languages : en
Pages : 497
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Book Description
Tutorial chapters by leaders in the field introduce state-of-the-art methods to handle information integration problems of omics data.
