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Author: Masahiro Kasahara
Publisher: Imperial College Press
ISBN: 1860946356
Category : Science
Languages : en
Pages : 252
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Book Description
Efficient computer programs have made it possible to elucidate and analyze large-scale genomic sequences. Fundamental tasks, such as the assembly of numerous whole-genome shotgun fragments, the alignment of complementary DNA sequences with a long genome, and the design of gene-specific primers or oligomers, require efficient algorithms and state-of-the-art implementation techniques. This textbook emphasizes basic software implementation techniques for processing large-scale genome sequences and provides executable sample programs. Book jacket.
Author: Masahiro Kasahara
Publisher: Imperial College Press
ISBN: 1860946356
Category : Science
Languages : en
Pages : 252
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Book Description
Efficient computer programs have made it possible to elucidate and analyze large-scale genomic sequences. Fundamental tasks, such as the assembly of numerous whole-genome shotgun fragments, the alignment of complementary DNA sequences with a long genome, and the design of gene-specific primers or oligomers, require efficient algorithms and state-of-the-art implementation techniques. This textbook emphasizes basic software implementation techniques for processing large-scale genome sequences and provides executable sample programs. Book jacket.
Author: Donald Adjeroh
Publisher: Springer Science & Business Media
ISBN: 038778909X
Category : Computers
Languages : en
Pages : 353
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Book Description
The Burrows-Wheeler Transform is one of the best lossless compression me- ods available. It is an intriguing — even puzzling — approach to squeezing redundancy out of data, it has an interesting history, and it has applications well beyond its original purpose as a compression method. It is a relatively late addition to the compression canon, and hence our motivation to write this book, looking at the method in detail, bringing together the threads that led to its discovery and development, and speculating on what future ideas might grow out of it. The book is aimed at a wide audience, ranging from those interested in learning a little more than the short descriptions of the BWT given in st- dard texts, through to those whose research is building on what we know about compression and pattern matching. The ?rst few chapters are a careful description suitable for readers with an elementary computer science ba- ground (and these chapters have been used in undergraduate courses), but later chapters collect a wide range of detailed developments, some of which are built on advanced concepts from a range of computer science topics (for example, some of the advanced material has been used in a graduate c- puter science course in string algorithms). Some of the later explanations require some mathematical sophistication, but most should be accessible to those with a broad background in computer science.
Author: Jerzy Kulski
Publisher: BoD – Books on Demand
ISBN: 9535122401
Category : Medical
Languages : en
Pages : 466
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Book Description
Next generation sequencing (NGS) has surpassed the traditional Sanger sequencing method to become the main choice for large-scale, genome-wide sequencing studies with ultra-high-throughput production and a huge reduction in costs. The NGS technologies have had enormous impact on the studies of structural and functional genomics in all the life sciences. In this book, Next Generation Sequencing Advances, Applications and Challenges, the sixteen chapters written by experts cover various aspects of NGS including genomics, transcriptomics and methylomics, the sequencing platforms, and the bioinformatics challenges in processing and analysing huge amounts of sequencing data. Following an overview of the evolution of NGS in the brave new world of omics, the book examines the advances and challenges of NGS applications in basic and applied research on microorganisms, agricultural plants and humans. This book is of value to all who are interested in DNA sequencing and bioinformatics across all fields of the life sciences.
Author: Dan Gusfield
Publisher: Cambridge University Press
ISBN: 1139811002
Category : Computers
Languages : en
Pages : 556
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Book Description
String algorithms are a traditional area of study in computer science. In recent years their importance has grown dramatically with the huge increase of electronically stored text and of molecular sequence data (DNA or protein sequences) produced by various genome projects. This book is a general text on computer algorithms for string processing. In addition to pure computer science, the book contains extensive discussions on biological problems that are cast as string problems, and on methods developed to solve them. It emphasises the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics. Its discussion of current algorithms and techniques also makes it a reference for professionals.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309038405
Category : Science
Languages : en
Pages : 128
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Book Description
There is growing enthusiasm in the scientific community about the prospect of mapping and sequencing the human genome, a monumental project that will have far-reaching consequences for medicine, biology, technology, and other fields. But how will such an effort be organized and funded? How will we develop the new technologies that are needed? What new legal, social, and ethical questions will be raised? Mapping and Sequencing the Human Genome is a blueprint for this proposed project. The authors offer a highly readable explanation of the technical aspects of genetic mapping and sequencing, and they recommend specific interim and long-range research goals, organizational strategies, and funding levels. They also outline some of the legal and social questions that might arise and urge their early consideration by policymakers.
Author: Altuna Akalin
Publisher: CRC Press
ISBN: 1498781861
Category : Mathematics
Languages : en
Pages : 462
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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: Veli Mäkinen
Publisher: Cambridge University Press
ISBN: 1009341219
Category : Computers
Languages : en
Pages : 470
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Book Description
Guided by standard bioscience workflows in high-throughput sequencing analysis, this book for graduate students, researchers, and professionals in bioinformatics and computer science offers a unified presentation of genome-scale algorithms. This new edition covers the use of minimizers and other advanced data structures in pangenomics approaches.
Author: Felix Kallenborn
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
With the technological advances in the field of genomics and sequencing, the processing of vast amounts of generated data becomes more and more challenging. Nowadays, software for processing large-scale datasets of sequencing reads may take hours to days to complete, even on high-end workstations. This explains the need for new approaches to achieve faster, high-performance applications. In contrast to traditional CPU-based software, algorithms utilizing the massively-parallel many-core architecture and fast memory of GPUs are potentially able to deliver the desired performance in many fields. In this thesis, we introduce two novel GPU-accelerated applications, CARE and CAREx, for common steps in sequence processing pipelines, error correction and read extension of Next Generation Sequencing (NGS) Illumina data, to improve the results of down-stream data analysis. To the best of our knowledge, CARE and CAREx are the first modern GPU-accelerated solutions for the respective problems. A key component of our algorithm is the identification of similar DNA sequences within a dataset. For this purpose, we developed a minhashing-based index data structure for large-scale read datasets. In conjunction with our fast bit-parallel shifted hamming distance computations, this allows for the efficient identification of similar reads. The resulting set of similar sequences is subsequently arranged into a gap-free multiple-sequence alignment to solve the problem at hand. Sequencing machines introduce both systematic errors and random errors. CARE, Context-Aware Read Error corrector, accurately removes errors introduced by NGS sequencing machines during the initial sequencing of a biological sample. With the help of a pre-trained Random Forest, CARE generates two orders-of-magnitude fewer false positives than its competitors. At the same time, it shows similar numbers of true positives. Read extension describes the process of elongating DNA sequences. The presence of longer sequences improves the resolution of more, larger structures within a genome. CAREx, Context-Aware Read Extender, produces longer sequences, so called pseudo-long reads, by connecting the two reads of read pairs which were sequenced in close proximity. Evaluation shows that CAREx produces significantly more highly accurate pseudo-long reads than the state-of-the-art. With algorithms tailored towards high-performance GPU computations, both CARE and CAREx run significantly faster than the CPU-based competitors, while, at the same time, produce more accurate results. The processing of a large Human dataset with 30x coverage with CARE requires less than 30 minutes using a single A100 GPU. This time can be further reduced down to 10 minutes on multi-GPU systems. In contrast, CPU-based tools like Musket or BFC take 3 hours and 1.5 hours, respectively. Read extension of a Human dataset with CAREx takes 3.3 hours to complete on a single GPU, whereas Konnector2 requires over a day to complete. This shows that large-scale sequence processing can greatly benefit from the usage of GPUs, and that multiple-sequence alignment-based algorithms should be considered despite their increased complexity because they provide great accuracy. While our general building blocks have been tailored towards our needs for error correction and read extension, they could also prove useful in other GPU-accelerated applications that process sequence data.
Author: Wing-Kin Sung
Publisher: CRC Press
ISBN: 1498752985
Category : Computers
Languages : en
Pages : 233
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Book Description
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.
Author: Margi Sheth
Publisher: Academic Press
ISBN: 0128023686
Category : Science
Languages : en
Pages : 146
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Book Description
Collaborative Genomics Projects: A Comprehensive Guide contains operational procedures, policy considerations, and the many lessons learned by The Cancer Genome Atlas Project. This book guides the reader through methods in patient sample acquisition, the establishment of data generation and analysis pipelines, data storage and dissemination, quality control, auditing, and reporting. This book is essential for those looking to set up or collaborate within a large-scale genomics research project. All authors are contributors to The Cancer Genome Atlas (TCGA) Program, a NIH- funded effort to generate a comprehensive catalog of genomic alterations in more than 35 cancer types. As the cost of genomic sequencing is decreasing, more and more researchers are leveraging genomic data to inform the biology of disease. The amount of genomic data generated is growing exponentially, and protocols need to be established for the long-term storage, dissemination, and regulation of this data for research. The book's authors create a complete handbook on the management of research projects involving genomic data as learned through the evolution of the TCGA program, a project that was primarily carried out in the US, but whose impact and lessons learned can be applied to international audiences. Establishes a framework for managing large-scale genomic research projects involving multiple collaborators Describes lessons learned through TCGA to prepare for potential roadblocks Evaluates policy considerations that are needed to avoid pitfalls Recommends strategies to make project management more efficient
