Computational Methods For Multi Omics Data Analysis In Cancer Precision Medicine

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Computational Methods for Multi-Omics Data Analysis in Cancer Precision Medicine

Author : Ehsan Nazemalhosseini-Mojarad
Publisher : Frontiers Media SA
ISBN 13 : 2832530389
Total Pages : 433 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Computational Methods for Multi-Omics Data Analysis in Cancer Precision Medicine by : Ehsan Nazemalhosseini-Mojarad

Download or read book Computational Methods for Multi-Omics Data Analysis in Cancer Precision Medicine written by Ehsan Nazemalhosseini-Mojarad and published by Frontiers Media SA. This book was released on 2023-08-02 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer is a complex and heterogeneous disease often caused by different alterations. The development of human cancer is due to the accumulation of genetic and epigenetic modifications that could affect the structure and function of the genome. High-throughput methods (e.g., microarray and next-generation sequencing) can investigate a tumor at multiple levels: i) DNA with genome-wide association studies (GWAS), ii) epigenetic modifications such as DNA methylation, histone changes and microRNAs (miRNAs) iii) mRNA. The availability of public datasets from different multi-omics data has been growing rapidly and could facilitate better knowledge of the biological processes of cancer. Computational approaches are essential for the analysis of big data and the identification of potential biomarkers for early and differential diagnosis, and prognosis.

Advanced Computational Methods for Oncological Image Analysis

Author : Leonardo Rundo
Publisher : Mdpi AG
ISBN 13 : 9783036525549
Total Pages : 262 pages
Book Rating : 4.5/5 (255 download)

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Book Synopsis Advanced Computational Methods for Oncological Image Analysis by : Leonardo Rundo

Download or read book Advanced Computational Methods for Oncological Image Analysis written by Leonardo Rundo and published by Mdpi AG. This book was released on 2021-12-06 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. The ultimate goal is to optimize the clinical workflow by combining accurate diagnosis with the most suitable therapies. Toward this, large-scale machine learning research can define associations among clinical, imaging, and multi-omics studies, making it possible to provide reliable diagnostic and prognostic biomarkers for precision oncology. Such reliable computer-assisted methods (i.e., artificial intelligence) together with clinicians' unique knowledge can be used to properly handle typical issues in evaluation/quantification procedures (i.e., operator dependence and time-consuming tasks). These technical advances can significantly improve result repeatability in disease diagnosis and guide toward appropriate cancer care. Indeed, the need to apply machine learning and computational intelligence techniques has steadily increased to effectively perform image processing operations-such as segmentation, co-registration, classification, and dimensionality reduction-and multi-omics data integration.

Computational Methods for Precision Oncology

Author : Alessandro Laganà
Publisher : Springer Nature
ISBN 13 : 303091836X
Total Pages : 341 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Computational Methods for Precision Oncology by : Alessandro Laganà

Download or read book Computational Methods for Precision Oncology written by Alessandro Laganà and published by Springer Nature. This book was released on 2022-03-01 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precision medicine holds great promise for the treatment of cancer and represents a unique opportunity for accelerated development and application of novel and repurposed therapeutic approaches. Current studies and clinical trials demonstrate the benefits of genomic profiling for patients whose cancer is driven by specific, targetable alterations. However, precision oncologists continue to be challenged by the widespread heterogeneity of cancer genomes and drug responses in designing personalized treatments. Chapters provide a comprehensive overview of the computational approaches, methods, and tools that enable precision oncology, as well as related biological concepts. Covered topics include genome sequencing, the architecture of a precision oncology workflow, and introduces cutting-edge research topics in the field of precision oncology. This book is intended for computational biologists, bioinformaticians, biostatisticians and computational pathologists working in precision oncology and related fields, including cancer genomics, systems biology, and immuno-oncology.

Improving Cancer Diagnosis and Care

Author : National Academies of Sciences, Engineering, and Medicine
Publisher : National Academies Press
ISBN 13 : 0309490847
Total Pages : 93 pages
Book Rating : 4.3/5 (94 download)

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Book Synopsis Improving Cancer Diagnosis and Care by : National Academies of Sciences, Engineering, and Medicine

Download or read book Improving Cancer Diagnosis and Care written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-07-15 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hallmark of high-quality cancer care is the delivery of the right treatment to the right patient at the right time. Precision oncology therapies, which target specific genetic changes in a patient's cancer, are changing the nature of cancer treatment by allowing clinicians to select therapies that are most likely to benefit individual patients. In current clinical practice, oncologists are increasingly formulating cancer treatment plans using results from complex laboratory and imaging tests that characterize the molecular underpinnings of an individual patient's cancer. These molecular fingerprints can be quite complex and heterogeneous, even within a single patient. To enable these molecular tumor characterizations to effectively and safely inform cancer care, the cancer community is working to develop and validate multiparameter omics tests and imaging tests as well as software and computational methods for interpretation of the resulting datasets. To examine opportunities to improve cancer diagnosis and care in the new precision oncology era, the National Cancer Policy Forum developed a two-workshop series. The first workshop focused on patient access to expertise and technologies in oncologic imaging and pathology and was held in February 2018. The second workshop, conducted in collaboration with the Board on Mathematical Sciences and Analytics, was held in October 2018 to examine the use of multidimensional data derived from patients with cancer, and the computational methods that analyze these data to inform cancer treatment decisions. This publication summarizes the presentations and discussions from the second workshop.

Machine Learning Advanced Dynamic Omics Data Analysis for Precision Medicine

Author : Tao Zeng
Publisher : Frontiers Media SA
ISBN 13 : 2889635546
Total Pages : 393 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Machine Learning Advanced Dynamic Omics Data Analysis for Precision Medicine by : Tao Zeng

Download or read book Machine Learning Advanced Dynamic Omics Data Analysis for Precision Medicine written by Tao Zeng and published by Frontiers Media SA. This book was released on 2020-03-30 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt:

'Essentials of Cancer Genomic, Computational Approaches and Precision Medicine

Author : Nosheen Masood
Publisher : Springer Nature
ISBN 13 : 9811510679
Total Pages : 499 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis 'Essentials of Cancer Genomic, Computational Approaches and Precision Medicine by : Nosheen Masood

Download or read book 'Essentials of Cancer Genomic, Computational Approaches and Precision Medicine written by Nosheen Masood and published by Springer Nature. This book was released on 2020-03-20 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concisely describes the role of omics in precision medicine for cancer therapies. It outlines our current understanding of cancer genomics, shares insights into the process of oncogenesis, and discusses emerging technologies and clinical applications of cancer genomics in prognosis and precision-medicine treatment strategies. It then elaborates on recent advances concerning transcriptomics and translational genomics in cancer diagnosis, clinical applications, and personalized medicine in oncology. Importantly, it also explains the importance of high-performance analytics, predictive modeling, and system biology in cancer research. Lastly, the book discusses current and potential future applications of pharmacogenomics in clinical cancer therapy and cancer drug development.

Machine Learning Methods for Multi-Omics Data Integration

Author : Abedalrhman Alkhateeb
Publisher : Springer Nature
ISBN 13 : 303136502X
Total Pages : 171 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis Machine Learning Methods for Multi-Omics Data Integration by : Abedalrhman Alkhateeb

Download or read book Machine Learning Methods for Multi-Omics Data Integration written by Abedalrhman Alkhateeb and published by Springer Nature. This book was released on 2023-12-15 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advancement of biomedical engineering has enabled the generation of multi-omics data by developing high-throughput technologies, such as next-generation sequencing, mass spectrometry, and microarrays. Large-scale data sets for multiple omics platforms, including genomics, transcriptomics, proteomics, and metabolomics, have become more accessible and cost-effective over time. Integrating multi-omics data has become increasingly important in many research fields, such as bioinformatics, genomics, and systems biology. This integration allows researchers to understand complex interactions between biological molecules and pathways. It enables us to comprehensively understand complex biological systems, leading to new insights into disease mechanisms, drug discovery, and personalized medicine. Still, integrating various heterogeneous data types into a single learning model also comes with challenges. In this regard, learning algorithms have been vital in analyzing and integrating these large-scale heterogeneous data sets into one learning model. This book overviews the latest multi-omics technologies, machine learning techniques for data integration, and multi-omics databases for validation. It covers different types of learning for supervised and unsupervised learning techniques, including standard classifiers, deep learning, tensor factorization, ensemble learning, and clustering, among others. The book categorizes different levels of integrations, ranging from early, middle, or late-stage among multi-view models. The underlying models target different objectives, such as knowledge discovery, pattern recognition, disease-related biomarkers, and validation tools for multi-omics data. Finally, the book emphasizes practical applications and case studies, making it an essential resource for researchers and practitioners looking to apply machine learning to their multi-omics data sets. The book covers data preprocessing, feature selection, and model evaluation, providing readers with a practical guide to implementing machine learning techniques on various multi-omics data sets.

Multi-omic Data Integration in Oncology

Author : Chiara Romualdi
Publisher : Frontiers Media SA
ISBN 13 : 2889661512
Total Pages : 187 pages
Book Rating : 4.8/5 (896 download)

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Book Synopsis Multi-omic Data Integration in Oncology by : Chiara Romualdi

Download or read book Multi-omic Data Integration in Oncology written by Chiara Romualdi and published by Frontiers Media SA. This book was released on 2020-12-03 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.

Computational Systems Biology Approaches in Cancer Research

Author : Inna Kuperstein
Publisher : CRC Press
ISBN 13 : 1000682927
Total Pages : 167 pages
Book Rating : 4.0/5 (6 download)

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Book Synopsis Computational Systems Biology Approaches in Cancer Research by : Inna Kuperstein

Download or read book Computational Systems Biology Approaches in Cancer Research written by Inna Kuperstein and published by CRC Press. This book was released on 2019-09-09 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Computational Systems BiologyApproaches in Cancer Research: "Complex concepts are written clearly and with informative illustrations and useful links. The book is enjoyable to read yet provides sufficient depth to serve as a valuable resource for both students and faculty." — Trey Ideker, Professor of Medicine, UC Xan Diego, School of Medicine "This volume is attractive because it addresses important and timely topics for research and teaching on computational methods in cancer research. It covers a broad variety of approaches, exposes recent innovations in computational methods, and provides acces to source code and to dedicated interactive web sites." — Yves Moreau, Department of Electrical Engineering, SysBioSys Centre for Computational Systems Biology, University of Leuven With the availability of massive amounts of data in biology, the need for advanced computational tools and techniques is becoming increasingly important and key in understanding biology in disease and healthy states. This book focuses on computational systems biology approaches, with a particular lens on tackling one of the most challenging diseases - cancer. The book provides an important reference and teaching material in the field of computational biology in general and cancer systems biology in particular. The book presents a list of modern approaches in systems biology with application to cancer research and beyond. It is structured in a didactic form such that the idea of each approach can easily be grasped from the short text and self-explanatory figures. The coverage of topics is diverse: from pathway resources, through methods for data analysis and single data analysis to drug response predictors, classifiers and image analysis using machine learning and artificial intelligence approaches. Features Up to date using a wide range of approaches Applicationexample in each chapter Online resources with useful applications’

Computational Methods in Biomedical Research

Author : Ravindra Khattree
Publisher : CRC Press
ISBN 13 : 9781420010923
Total Pages : 432 pages
Book Rating : 4.0/5 (19 download)

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Book Synopsis Computational Methods in Biomedical Research by : Ravindra Khattree

Download or read book Computational Methods in Biomedical Research written by Ravindra Khattree and published by CRC Press. This book was released on 2007-12-12 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continuing advances in biomedical research and statistical methods call for a constant stream of updated, cohesive accounts of new developments so that the methodologies can be properly implemented in the biomedical field. Responding to this need, Computational Methods in Biomedical Research explores important current and emerging computational statistical methods that are used in biomedical research. Written by active researchers in the field, this authoritative collection covers a wide range of topics. It introduces each topic at a basic level, before moving on to more advanced discussions of applications. The book begins with microarray data analysis, machine learning techniques, and mass spectrometry-based protein profiling. It then uses state space models to predict US cancer mortality rates and provides an overview of the application of multistate models in analyzing multiple failure times. The book also describes various Bayesian techniques, the sequential monitoring of randomization tests, mixed-effects models, and the classification rules for repeated measures data. The volume concludes with estimation methods for analyzing longitudinal data. Supplying the knowledge necessary to perform sophisticated statistical analyses, this reference is a must-have for anyone involved in advanced biomedical and pharmaceutical research. It will help in the quest to identify potential new drugs for the treatment of a variety of diseases.

Computational Genomics with R

Author : Altuna Akalin
Publisher : CRC Press
ISBN 13 : 1498781861
Total Pages : 462 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Computational Genomics with R by : Altuna Akalin

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.

Analyzing Network Data in Biology and Medicine

Author : Nataša Pržulj
Publisher : Cambridge University Press
ISBN 13 : 1108432239
Total Pages : 647 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Analyzing Network Data in Biology and Medicine by : Nataša Pržulj

Download or read book Analyzing Network Data in Biology and Medicine written by Nataša Pržulj and published by Cambridge University Press. This book was released on 2019-03-28 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.

Pharmacogenomics

Author : Ambily Sivadas
Publisher :
ISBN 13 : 9781864905328
Total Pages : 0 pages
Book Rating : 4.9/5 (53 download)

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Book Synopsis Pharmacogenomics by : Ambily Sivadas

Download or read book Pharmacogenomics written by Ambily Sivadas and published by . This book was released on 2023-09-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a comprehensive guide to the field of pharmacogenomics, which combines genomics, transcriptomics, epigenomics, proteomics, and metabolomics to understand how individual genetic variations influence drug response. The book covers a wide range of topics, including big data, machine learning, artificial intelligence, data integration, multi-omics, single-cell analysis, biomarker discovery, drug discovery, drug development, clinical trials, adverse drug reactions, pharmacokinetics, pharmacodynamics, gene expression, regulatory genomics, network analysis, pathway analysis, variant analysis, GWAS, eQTL mapping, splicing analysis, gene ontology, functional enrichment, drug-target interactions, drug repurposing, precision medicine, cancer genomics, infectious disease genomics, neurogenomics, cardiovascular genomics, rare disease genomics, omics data visualization, data sharing, open science, reproducibility, ethics, and data privacy. The book emphasizes the importance of personalized medicine, where drug treatments are tailored to individual patients based on their genetic makeup, to improve drug efficacy and reduce adverse drug reactions. It provides detailed descriptions of computational methods and genome integration techniques used in pharmacogenomics research. It also covers the latest developments in the field, including the use of machine learning and artificial intelligence to analyze large-scale omics data, and the application of regulatory genomics and network analysis to identify drug-target interactions and potential drug repurposing opportunities. The book also addresses the challenges and ethical considerations involved in pharmacogenomics research, such as data privacy and the need for open science and reproducibility. It is a valuable resource for researchers, clinicians, and students interested in pharmacogenomics and personalized medicine. Overall, "Pharmacogenomics: Computational Methods, Genome Integration" provides a comprehensive overview of the field, highlighting the potential of omics data to transform drug discovery and development, and improve patient outcomes.

DNA Methylation

Author : J. Jost
Publisher : Birkhäuser
ISBN 13 : 3034891180
Total Pages : 581 pages
Book Rating : 4.0/5 (348 download)

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Book Synopsis DNA Methylation by : J. Jost

Download or read book DNA Methylation written by J. Jost and published by Birkhäuser. This book was released on 2013-11-11 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: The occurrence of 5-methylcytosine in DNA was first described in 1948 by Hotchkiss (see first chapter). Recognition of its possible physiologi cal role in eucaryotes was first suggested in 1964 by Srinivasan and Borek (see first chapter). Since then work in a great many laboratories has established both the ubiquity of 5-methylcytosine and the catholicity of its possible regulatory function. The explosive increase in the number of publications dealing with DNA methylation attests to its importance and makes it impossible to write a comprehensive coverage of the literature within the scope of a general review. Since the publication of the 3 most recent books dealing with the subject (DNA methylation by Razin A. , Cedar H. and Riggs A. D. , 1984 Springer Verlag; Molecular Biology of DNA methylation by Adams R. L. P. and Burdon R. H. , 1985 Springer Verlag; Nucleic Acids Methylation, UCLA Symposium suppl. 128, 1989) considerable progress both in the techniques and results has been made in the field of DNA methylation. Thus we asked several authors to write chapters dealing with aspects of DNA methyla tion in which they are experts. This book should be most useful for students, teachers as well as researchers in the field of differentiation and gene regulation. We are most grateful to all our colleagues who were willing to spend much time and effort on the publication of this book. We also want to express our gratitude to Yan Chim Jost for her help in preparing this book.

Computational Methods in Drug Discovery and Repurposing for Cancer Therapy

Author : Ganji Purnachandra Nagaraju
Publisher : Elsevier
ISBN 13 : 0443152810
Total Pages : 460 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Computational Methods in Drug Discovery and Repurposing for Cancer Therapy by : Ganji Purnachandra Nagaraju

Download or read book Computational Methods in Drug Discovery and Repurposing for Cancer Therapy written by Ganji Purnachandra Nagaraju and published by Elsevier. This book was released on 2023-03-22 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Methods in Drug Discovery and Repurposing for Cancer Therapy provides knowledge about ongoing research as well as computational approaches for drug discovery and repurposing for cancer therapy. The book also provides detailed descriptions about target molecules, pathways, and their inhibitors for easy understanding and applicability. The book discusses tools and techniques such as integrated bioinformatics approaches, systems biology tools, molecular docking, computational chemistry, artificial intelligence, machine learning, structure-based virtual screening, biomarkers, and transcriptome; those are discussed in the context of different cancer types, such as colon, pancreatic, glioblastoma, endometrial, and retinoblastoma, among others. This book is a valuable resource for researchers, students, and members of the biomedical and medical fields who want to learn more about the use of computational modeling to better tailor the treatment for cancer patients. Discusses in silico remodeling of effective phytochemical compounds for discovering improved anticancer agents for substantial/significant cancer therapy Covers potential tools of bioinformatics that are applied toward discovering new targets by drug repurposing and strategies to cure different types of cancers Demonstrates the significance of computational and artificial intelligence approaches in anticancer drug discovery Explores how these various advances can be integrated into a precision and personalized medicine approach that can eventually enhance patient care

Computational Biology

Author : Tuan Pham
Publisher : Springer Science & Business Media
ISBN 13 : 1441908110
Total Pages : 309 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Computational Biology by : Tuan Pham

Download or read book Computational Biology written by Tuan Pham and published by Springer Science & Business Media. This book was released on 2009-09-23 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume covers techniques in computational biology and their applications in oncology. It details advanced statistical methods, heuristic algorithms, cluster analysis, data modeling, and image and pattern analysis applied to cancer research.

Computational Methods for Next Generation Sequencing Data Analysis

Author : Ion Mandoiu
Publisher : John Wiley & Sons
ISBN 13 : 1119272173
Total Pages : 464 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Computational Methods for Next Generation Sequencing Data Analysis by : Ion Mandoiu

Download or read book Computational Methods for Next Generation Sequencing Data Analysis written by Ion Mandoiu and published by John Wiley & Sons. This book was released on 2016-09-12 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces readers to core algorithmic techniques for next-generation sequencing (NGS) data analysis and discusses a wide range of computational techniques and applications This book provides an in-depth survey of some of the recent developments in NGS and discusses mathematical and computational challenges in various application areas of NGS technologies. The 18 chapters featured in this book have been authored by bioinformatics experts and represent the latest work in leading labs actively contributing to the fast-growing field of NGS. The book is divided into four parts: Part I focuses on computing and experimental infrastructure for NGS analysis, including chapters on cloud computing, modular pipelines for metabolic pathway reconstruction, pooling strategies for massive viral sequencing, and high-fidelity sequencing protocols. Part II concentrates on analysis of DNA sequencing data, covering the classic scaffolding problem, detection of genomic variants, including insertions and deletions, and analysis of DNA methylation sequencing data. Part III is devoted to analysis of RNA-seq data. This part discusses algorithms and compares software tools for transcriptome assembly along with methods for detection of alternative splicing and tools for transcriptome quantification and differential expression analysis. Part IV explores computational tools for NGS applications in microbiomics, including a discussion on error correction of NGS reads from viral populations, methods for viral quasispecies reconstruction, and a survey of state-of-the-art methods and future trends in microbiome analysis. Computational Methods for Next Generation Sequencing Data Analysis: Reviews computational techniques such as new combinatorial optimization methods, data structures, high performance computing, machine learning, and inference algorithms Discusses the mathematical and computational challenges in NGS technologies Covers NGS error correction, de novo genome transcriptome assembly, variant detection from NGS reads, and more This text is a reference for biomedical professionals interested in expanding their knowledge of computational techniques for NGS data analysis. The book is also useful for graduate and post-graduate students in bioinformatics.