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Clustering Algorithms For Next Generation Sequencing Data From Heterogenous Populations
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Book Synopsis Clustering Algorithms for Next-generation Sequencing Data from Heterogenous Populations by : Shruthi Prabhakara
Download or read book Clustering Algorithms for Next-generation Sequencing Data from Heterogenous Populations written by Shruthi Prabhakara and published by . This book was released on 2012 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 2016-10-03 with total page 460 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.
Book Synopsis De Novo Methods for Characterizing Diversity in Populations of Genomes Using Next-generation Sequencing Data by : Raunaq Malhotra
Download or read book De Novo Methods for Characterizing Diversity in Populations of Genomes Using Next-generation Sequencing Data written by Raunaq Malhotra and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Next-generation sequencing (NGS) technologies have enabled fast profiling of diversity in population of closely related genomes over the past two decades in a high throughput fashion. Examples of such applications include reconstructing the haplotypes of viruses replicating within a host, identifying insertional polymorphisms of mobile elements amongst individuals in a species, and characterizing diversity in populations of cancer cell types in an individual. Although a plethora of methods use an existing or assembled reference sequence for characterizing diversity, the usage of de novo methods can be beneficial for studying diversity in a population of closely related genomes. This dissertation aims to develop de novo computational methods for studying diversity in such samples using NGS data. De novo methods rely only on the inherent NGS data collected from a sample and can be applied to study the diversity in organisms where limited prior knowledge is available. In the first part of the dissertation, I discuss a clustering pipeline for clustering NGS data that was obtained from sites of integration of a mobile element in the genome in a panel of individuals. Typically, reads from individuals can be mapped to a reference genome to determine the location of an element-host integration site. However, host regions flanking a mobile element can be modified by the presence of the element and reference genomes are not available for all species. Clustering methods provide an alternative for analyzing such integration site datasets. Here, each cluster ideally represents reads from a single integration site. The main contributions in this chapter are (i) A pipeline for clustering NGS reads from integration site junctions using UCLUST clustering algorithm that empirically determines the optimal clustering threshold; (ii) The optimal threshold is determined based on internal clustering measure, $I-index$, which assesses clusters for small intra-cluster diameters and large inter-cluster distance. We evaluate and test our proposed pipeline to determine the optimal clustering parameters and show improved results on simulated and real datasets. The second and major portion of the dissertation focuses on de novo reconstruction of viral haplotypes in a viral population using paired-end NGS data. We have proposed MLEHaplo, a maximum likelihood de novo assembly algorithm for reconstructing viral haplotypes. Using the pairing information of reads in our proposed Viral Path Reconstruction Algorithm (ViPRA), we generate a small subset of paths from a De Bruijn graph of reads that serve as candidate paths for true viral haplotypes. Our proposed method MLEHaplo then generates a maximum likelihood estimate of the viral population using the paths reconstructed by ViPRA. We evaluate and compare MLEHaplo on simulated datasets at different sequence coverage, and on real datasets. MLEHaplo reconstructs full length viral haplotypes in most of the small genome simulated viral populations. While reference based methods either under-estimate or over-estimate the viral haplotypes, MLEHaplo limits the over-estimation of the size of true viral haplotypes, and reconstructs the full phylogeny of the input viral population. As NGS data is fraught with sequencing errors which significantly impact de novo reconstruction of viral haplotypes, in Chapter 4 we proposed a frame-based representation of k-mers for detecting sequencing errors and rare variants for such data. Frames are sets of non-orthogonal basis functions, traditionally used in signal processing for noise removal. We define a frame for genomes and sequenced reads to consist of discrete spatial signals of every k-mer of a given size. We show that each k-mer in the sequenced data can be projected onto multiple frames and these projections are maximized for spatial signals corresponding to the k-mer's substrings. Our proposed classifier, MultiRes, is trained on the projections of k-mers as features used for marking k-mers as erroneous or true variations in the genome. We evaluate MultiRes on simulated and real viral population datasets and compare it to other error correction methods known in the literature. MultiRes has 4 to 500 times less false positive k-mer predictions compared to other methods, essential for accurate estimation of viral population diversity and their de novo assembly. It has high recall of the true k-mers, comparable to other error correction methods. MultiRes also has greater than 95% recall for detecting single nucleotide polymorphisms (SNPs), has low false positive SNP predictions, while detecting higher number of rare variants compared to other variant calling methods for viral populations.
Book Synopsis Algorithms for Next-Generation Sequencing by : Wing-Kin Sung
Download or read book Algorithms for Next-Generation Sequencing written by Wing-Kin Sung and published by CRC Press. This book was released on 2017-05-18 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in sequencing technology have allowed scientists to study the human genome in greater depth and on a larger scale than ever before – as many as hundreds of millions of short reads in the course of a few days. But what are the best ways to deal with this flood of data? Algorithms for Next-Generation Sequencing is an invaluable tool for students and researchers in bioinformatics and computational biology, biologists seeking to process and manage the data generated by next-generation sequencing, and as a textbook or a self-study resource. In addition to offering an in-depth description of the algorithms for processing sequencing data, it also presents useful case studies describing the applications of this technology.
Book Synopsis Algorithms for Next-Generation Sequencing Data by : Mourad Elloumi
Download or read book Algorithms for Next-Generation Sequencing Data written by Mourad Elloumi and published by Springer. This book was released on 2017-09-18 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 14 contributed chapters in this book survey the most recent developments in high-performance algorithms for NGS data, offering fundamental insights and technical information specifically on indexing, compression and storage; error correction; alignment; and assembly. The book will be of value to researchers, practitioners and students engaged with bioinformatics, computer science, mathematics, statistics and life sciences.
Book Synopsis Data Clustering by : Charu C. Aggarwal
Download or read book Data Clustering written by Charu C. Aggarwal and published by CRC Press. This book was released on 2013-08-21 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.
Book Synopsis Error Correction and Clustering Algorithms for Next Generation Sequencing by : Xiao Yang
Download or read book Error Correction and Clustering Algorithms for Next Generation Sequencing written by Xiao Yang and published by . This book was released on 2011 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computational Methods for Understanding Genetic Variations from Next Generation Sequencing Data by : Soyeon Ahn (Ph. D.)
Download or read book Computational Methods for Understanding Genetic Variations from Next Generation Sequencing Data written by Soyeon Ahn (Ph. D.) and published by . This book was released on 2018 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Studies of human genetic variation reveal critical information about genetic and complex diseases such as cancer, diabetes and heart disease, ultimately leading towards improvements in health and quality of life. Moreover, understanding genetic variations in viral population is of utmost importance to virologists and helps in search for vaccines. Next-generation sequencing technology is capable of acquiring massive amounts of data that can provide insight into the structure of diverse sets of genomic sequences. However, reconstructing heterogeneous sequences is computationally challenging due to the large dimension of the problem and limitations of the sequencing technology.This dissertation is focused on algorithms and analysis for two problems in which we seek to characterize genetic variations: (1) haplotype reconstruction for a single individual, so-called single individual haplotyping (SIH) or haplotype assembly problem, and (2) reconstruction of viral population, the so-called quasispecies reconstruction (QSR) problem. For the SIH problem, we have developed a method that relies on a probabilistic model of the data and employs the sequential Monte Carlo (SMC) algorithm to jointly determine type of variation (i.e., perform genotype calling) and assemble haplotypes. For the QSR problem, we have developed two algorithms. The first algorithm combines agglomerative hierarchical clustering and Bayesian inference to reconstruct quasispecies characterized by low diversity. The second algorithm utilizes tensor factorization framework with successive data removal to reconstruct quasispecies characterized by highly uneven frequencies of its components. Both algorithms outperform existing methods in both benchmarking tests and real data.
Download or read book Clustering written by Rui Xu and published by Wiley-IEEE Press. This book was released on 2009 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to take a truly comprehensive look at clustering. It begins with an introduction to cluster analysis and goes on to explore: proximity measures; hierarchical clustering; partition clustering; neural network-based clustering; kernel-based clustering; sequential data clustering; large-scale data clustering; data visualization and high-dimensional data clustering; and cluster validation. The authors assume no previous background in clustering and their generous inclusion of examples and references help make the subject matter comprehensible for readers of varying levels and backgrounds.
Book Synopsis Landscape of Next Generation Sequencing Using Pattern Recognition by : Saurav Mallik
Download or read book Landscape of Next Generation Sequencing Using Pattern Recognition written by Saurav Mallik and published by CRC Press. This book was released on 2024-10-23 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on an eminent technology called next generation sequencing (NGS) which has entirely changed the procedure of examining organisms and will have a great impact on biomedical research and disease diagnosis. Numerous computational challenges have been brought on by the rapid advancement of large-scale next-generation sequencing (NGS) technologies and their application. The term ""biomedical imaging"" refers to the use of a variety of imaging techniques (such as X-rays, CT scans, MRIs, ultrasounds, etc.) to get images of the interior organs of a human being for potential diagnostic, treatment planning, follow-up, and surgical purposes. In these circumstances, deep learning, a new learning method that uses multi-layered artificial neural networks (ANNs) for unsupervised, supervised, and semi-supervised learning, has attracted a lot of interest for applications to NGS and imaging, even when both of these data are used for the same group of patients. The three main research phenomena in biomedical research are disease classification, feature dimension reduction, and heterogeneity. AI approaches are used by clinical researchers to efficiently analyse extremely complicated biomedical datasets (e.g., multi-omic datasets. With the use of NGS data and biomedical imaging of various human organs, researchers may predict diseases using a variety of deep learning models. Unparalleled prospects to improve the work of radiologists, clinicians, and biomedical researchers, speed up disease detection and diagnosis, reduce treatment costs, and improve public health are presented by using deep learning models in disease prediction using NGS and biomedical imaging. This book influences a variety of critical disease data and medical images.
Book Synopsis Intracranial EEG by : Nikolai Axmacher
Download or read book Intracranial EEG written by Nikolai Axmacher and published by Springer Nature. This book was released on 2023-08-01 with total page 909 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers the first, comprehensive guide to planning and conducting intracranial EEG studies, and analyzing intracranial EEG data. The chapters address core questions in the field of intracranial EEG research. They are written by internationally recognized experts in the domain of intracranial EEG and acknowledge the heterogeneity of approaches in this field. The particular format of the book allows readers to find clear guidelines, hands-on expertise and invaluable background information for planning and conducting state-of-the-art intracranial EEG research projects. Besides offering a reference guide to newcomers in the field, it also provides scholarly information for the more experienced researcher and inspiration for the expert. The book covers a wide range of topics, with a special emphasis on aspects in which intracranial EEG data differ from other types of data in the cognitive neurosciences. It discusses typical patient characteristics and implantation schemes, ethical issues, and practical considerations for planning and running intracranial EEG experiments. It addresses signal characteristics and the physiological background of oscillatory and non-oscillatory aspects of intracranial EEG signals. It describes complex pre-processing steps such as advantages and disadvantages of different referencing schemes, and how to identify the location of electrodes. In addition, it answers specific questions on data processing, addressing core aspects of statistical analysis, and suggesting guidelines for data presentation. Further, it covers advanced topics such as causal interventions (i.e. deep brain stimulation), acquisition and analysis of single-unit data and multimodal recordings, and discusses important future challenges and opportunities in the field of intracranial EEG research.
Book Synopsis Next Generation Sequencing (NGS) for Rare Diseases Diagnosis by : Xiu-An Yang
Download or read book Next Generation Sequencing (NGS) for Rare Diseases Diagnosis written by Xiu-An Yang and published by Frontiers Media SA. This book was released on 2022-01-28 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Transcriptomics and Gene Regulation by : Jiaqian Wu
Download or read book Transcriptomics and Gene Regulation written by Jiaqian Wu and published by Springer. This book was released on 2015-11-17 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on modern computational and statistical tools for translational gene expression and regulation research to improve prognosis, diagnostics, prediction of severity, and therapies for human diseases. It introduces some of state of the art technologies as well as computational and statistical tools for translational bioinformatics in the areas of gene transcription and regulation, including the tools for next generation sequencing analyses, alternative spicing, the modeling of signaling pathways, network analyses in predicting disease genes, as well as protein and gene expression data integration in complex human diseases etc. The book is particularly useful for researchers and students in the field of molecular biology, clinical biology and bioinformatics, as well as physicians etc. Dr. Jiaqian Wu is assistant professor in the Vivian L. Smith Department of Neurosurgery and Center for Stem Cell and Regenerative Medicine, University of Texas Health Science Centre, Houston, TX, USA.
Book Synopsis Proceedings of the 2nd International Conference on Healthcare Science and Engineering by : Chase Q. Wu
Download or read book Proceedings of the 2nd International Conference on Healthcare Science and Engineering written by Chase Q. Wu and published by Springer. This book was released on 2019-05-09 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a compilation of selected papers from the 2nd International Conference on Healthcare Science and Engineering (Healthcare 2018). The work focuses on novel computing, networking, and data analytics techniques for various issues in healthcare. The book is a valuable resource for academic researchers and practitioners working in the field.
Book Synopsis Mandell, Douglas, and Bennett's Principles and Practice of Infectious Diseases E-Book by : John E. Bennett
Download or read book Mandell, Douglas, and Bennett's Principles and Practice of Infectious Diseases E-Book written by John E. Bennett and published by Elsevier Health Sciences. This book was released on 2019-08-08 with total page 5208 pages. Available in PDF, EPUB and Kindle. Book excerpt: For four decades, physicians and other healthcare providers have trusted Mandell, Douglas, and Bennett's Principles and Practice of Infectious Diseases to provide expert guidance on the diagnosis and treatment of these complex disorders. The 9th Edition continues the tradition of excellence with newly expanded chapters, increased global coverage, and regular updates to keep you at the forefront of this vitally important field. Meticulously updated by Drs. John E. Bennett, Raphael Dolin, and Martin J. Blaser, this comprehensive, two-volume masterwork puts the latest information on challenging infectious diseases at your fingertips. Provides more in-depth coverage of epidemiology, etiology, pathology, microbiology, immunology, and treatment of infectious agents than any other infectious disease resource. Features an increased focus on antibiotic stewardship; new antivirals for influenza, cytomegalovirus, hepatitis C, hepatitis B., and immunizations; and new recommendations for vaccination against infection with pneumococci, papillomaviruses, hepatitis A, and pertussis. Covers newly recognized enteroviruses causing paralysis (E-A71, E-D68); emerging viral infections such as Ebola, Zika, Marburg, SARS, and MERS; and important updates on prevention and treatment of C. difficile infection, including new tests that diagnose or falsely over-diagnose infectious diseases. Offers fully revised content on bacterial pathogenesis, antibiotic use and toxicity, the human microbiome and its effects on health and disease, immunological mechanisms and immunodeficiency, and probiotics and alternative approaches to treatment of infectious diseases. Discusses up-to-date topics such as use of the new PCR panels for diagnosis of meningitis, diarrhea and pneumonia; current management of infected orthopedic implant infections; newly recognized infections transmitted by black-legged ticks in the USA: Borrelia miyamotoi and Powassan virus; infectious complications of new drugs for cancer; new drugs for resistant bacteria and mycobacteria; new guidelines for diagnosis and therapy of HIV infections; and new vaccines against herpes zoster, influenza, meningococci. PPID continues its tradition of including leading experts from a truly global community, including authors from Australia, Canada and countries in Europe, Asia, and South America. Features more than 1,500 high-quality, full-color photographs—with hundreds new to this edition.
Book Synopsis Cryptic Species by : Alexandre K. Monro
Download or read book Cryptic Species written by Alexandre K. Monro and published by Cambridge University Press. This book was released on 2022-09-08 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book critically evaluates cryptic species - a growing trend in taxonomy - and their importance for evolutionary biology.
Book Synopsis Detection Methods in Precision Medicine by : Mengsu Yang
Download or read book Detection Methods in Precision Medicine written by Mengsu Yang and published by Royal Society of Chemistry. This book was released on 2020-12-14 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will be among the first to cover the detection methods for precision medicine that are set to transform health care in the future.
