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Landscape of Next Generation Sequencing Using Pattern Recognition
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.
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Next-Generation Sequencing
This cutting-edge reference book compiles standard operating procedures, protocols, and applications of Next-Generation Sequencing (NGS). It discusses genomic testing applications through NGS. It pays special focus on the protocols for cataloging variants of uncertain significance. Over the years, NGS and advanced bioinformatics approaches have allowed the transition of genomic assays into translational practices. The book covers visualization of NGS data sets, investigation of early development impairment, and metagenome protocols. It also discusses the challenges in NGS methods.Key Points-· Includes case studies of application of next-generation sequencing in different taxa like humans, rodents, plants, bacteria· Compiles protocols from various reputed companies like Illumina, PacBio, ThermoFisher· Discusses the translational applications of NGS methods· Reviews Machine Learning Heuristics For NGS data interpretation· Discusses emerging genomic assay technologies and characterizing mechanisms of disease prevalenceThe book is meant for researchers and industry experts in genomics, computational biology, and bioinformatics.
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Next-Generation Sequencing Data Analysis
Next-generation DNA and RNA sequencing has revolutionized biology and medicine. With sequencing cost continuously dropping and our ability to generate large datasets rising, data analysis becomes more important than ever. Next-Generation Sequencing Data Analysis walks readers through NGS data analysis step-by-step for a wide range of NGS applications. For each NGS application, this book covers topics from experimental design, sample processing, sequencing strategy formulation, to sequencing reads quality control, data preprocessing, reads mapping or assembly, and more advanced stages that are specific to each application. Major applications include: RNA-seq: both bulk and single-cell (separate chapters) Genotyping and variant discovery through whole genome/exome sequencing Clinical sequencing and detection of actionable variants De novo genome assembly ChIP-seq to map protein-DNA interactions Epigenomics through DNA methylation sequencing Metagenome sequencing for microbiome analysis Before detailing the analytic steps for each of these applications, the book presents introductory cellular and molecular biology as a refresher mostly for data scientists, the ins and outs of widely used NGS platforms, and an overview of computing needs for NGS data management and analysis. The book concludes with a chapter on the changing landscape of NGS technologies and data analytics. The second edition of this book builds on the well-received first edition by providing updates to each chapter. Two brand new chapters are added to meet rising data analysis demands on single-cell RNA-seq and clinical sequencing. The increasing use of long-reads sequencing has also been reflected in all NGS applications. This book discusses concepts and principles that underlie each analytic step, along with software tools for implementation. It highlights key features of the tools while omitting tedious details to provide an easy-to-follow guide for practitioners in life sciences, bioinformatics, biostatistics, and data science. Tools introduced in this book are open-source and freely available.
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Next Generation Sequencing
This volume covers a wide range of various fields of research, with the common thread being Next Generation Sequencing (NGS) related methods and applications, as well as analysis and interpretation of the data obtained. Chapters guide readers through the highly dynamic processes of translational and transcriptional profiling of a cell, method to detect copy number alterations (CNAs), targeted sequencing applications, method called “Hi-Plex” to characterize known polymorphic loci, single-cell of DNA or RNA, identify and characterize rare circulating CD4 T cells, and computational pipeline for RNAseq analysis. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Next Generation Sequencing: Methods and Protocols aims to be useful and informative for further study into this vital field.
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Computational Methods for Next Generation Sequencing Data Analysis
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 algorithmsDiscusses the mathematical and computational challenges in NGS technologiesCovers 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.
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High-Throughput Next Generation Sequencing
Due to their novel concepts and extraordinary high-throughput sequencing capacity, the “next generation sequencing” methods allow scientists to grasp system-wide landscapes of the complex molecular events taking place in various biological systems, including microorganisms and microbial communities. These methods are now being recognized as essential tools for a more comprehensive and deeper understanding of the mechanisms underlying many biological processes. In High-Throughput Next Generation Sequencing: Methods and Applications, experts in the field explore the most recent advances in the applications of next generation sequencing technologies with an emphasis on microorganisms and their communities; however, the methods described in this book will also offer general applications relevant to the study of any living organisms. Written in the highly successful Methods in Molecular Biology™ series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Comprehensive and cutting-edge, High-Throughput Next Generation Sequencing: Methods and Applications is an excellent collection of chapters to aid all scientists who wish to apply these innovative research tools to enhance their own pursuits in microbiology and also biology in general.
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Algorithms for Next-Generation Sequencing
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.
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Next Generation Sequencing
In recent years, owing to the fast development of a variety of sequencing technologies in the post human genome project era, sequencing analysis of a group of target genes, entire protein coding regions of the human genome, and the whole human genome has become a reality. Next Generation Sequencing (NGS) or Massively Parallel Sequencing (MPS) technologies offers a way to screen for mutations in many different genes in a cost and time efficient manner by deep coverage of the target sequences. This novel technology has now been applied to clinical diagnosis of Mendelian disorders of well characterized or undefined diseases, discovery of new disease genes, noninvasive prenatal diagnosis using maternal blood, and population based carrier testing of severe autosomal recessive disorders. This book covers topics of these applications, including potential limitations and expanded application in the future.
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Rough-Fuzzy Pattern Recognition
Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems development, making it easier to master such tasks as classification, clustering, and feature selection. Rough-Fuzzy Pattern Recognition examines the important underlying theory as well as algorithms and applications, helping readers see the connections between theory and practice. The first chapter provides an introduction to pattern recognition and data mining, including the key challenges of working with high-dimensional, real-life data sets. Next, the authors explore such topics and issues as: Soft computing in pattern recognition and data miningA mathematical framework for generalized rough sets, incorporating the concept of fuzziness in defining the granules as well as the setSelection of non-redundant and relevant features of real-valued data setsSelection of the minimum set of basis strings with maximum information for amino acid sequence analysisSegmentation of brain MR images for visualization of human tissues Numerous examples and case studies help readers better understand how pattern recognition models are developed and used in practice. This textcovering the latest findings as well as directions for future researchis recommended for both students and practitioners working in systems design, pattern recognition, image analysis, data mining, bioinformatics, soft computing, and computational intelligence.
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Scalable Pattern Recognition Algorithms
This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.
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Scalable Pattern Recognition Algorithms
This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.
R 4,110.15
High-Throughput Next Generation Sequencing
Due to their novel concepts and extraordinary high-throughput sequencing capacity, the “next generation sequencing” methods allow scientists to grasp system-wide landscapes of the complex molecular events taking place in various biological systems, including microorganisms and microbial communities. These methods are now being recognized as essential tools for a more comprehensive and deeper understanding of the mechanisms underlying many biological processes. In High-Throughput Next Generation Sequencing: Methods and Applications, experts in the field explore the most recent advances in the applications of next generation sequencing technologies with an emphasis on microorganisms and their communities; however, the methods described in this book will also offer general applications relevant to the study of any living organisms. Written in the highly successful Methods in Molecular Biology™ series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Comprehensive and cutting-edge, High-Throughput Next Generation Sequencing: Methods and Applications is an excellent collection of chapters to aid all scientists who wish to apply these innovative research tools to enhance their own pursuits in microbiology and also biology in general.
R 4,189.97
Pattern Recognition in Bioinformatics
This book constitutes the refereed proceedings of the 7th International Conference on Pattern Recognition in Bioinformatics, PRIB 2012, held in Tokyo, Japan, in November 2012.The 24 revised full papers presented were carefully reviewed and selected from 33 submissions. Their topics are widely ranging from fundamental techniques, sequence analysis to biological network analysis. The papers are organized in topical sections on generic methods, visualization, image analysis, and platforms, applications of pattern recognition techniques, protein structure and docking, complex data analysis, and sequence analysis.
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Pattern Recognition And Big Data
Containing twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications.Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis.
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Next Generation Sequencing and Sequence Assembly
The goal of this book is to introduce the biological and technical aspects of next generation sequencing methods, as well as algorithms to assemble these sequences into whole genomes. The book is organized into two parts; part 1 introduces NGS methods and part 2 reviews assembly algorithms and gives a good insight to these methods for readers new to the field. Gathering information, about sequencing and assembly methods together, helps both biologists and computer scientists to get a clear idea about the field. Chapters will include information about new sequencing technologies such as ChIp-seq, ChIp-chip, and De Novo sequence assembly.
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Pattern Recognition
The multi-volume set LNCS 16812-16827 constitutes the refereed proceedings of the 28th International Conference on Pattern Recognition, ICPR 2026, held in Lyon, France, during August 17-21, 2026. The total of 714 full papers included in the proceedings was carefully reviewed and selected from 1362 submissions. They focus on topics such as Artificial Intelligence, Pattern Recognition and Machine Learning; Computer and Robot Vision; Image, Speech, Signal and Video Processing; Biometrics and Human Computer Interaction; Document Analysis and Recognition; and Biomedical Imaging and Bioinformatics.
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Next Generation Sequencing Technologies and Challenges in Sequence Assembly
The introduction of Next Generation Sequencing (NGS) technologies resulted in a major transformation in the way scientists extract genetic information from biological systems, revealing limitless insight about the genome, transcriptome and epigenome of any species. However, with NGS, came its own challenges that require continuous development in the sequencing technologies and bioinformatics analysis of the resultant raw data and assembly of the full length genome and transcriptome. Such developments lead to outstanding improvements of the performance and coverage of sequencing and improved quality for the assembled sequences, nevertheless, challenges such as sequencing errors, expensive processing and memory usage for assembly and sequencer specific errors remains major challenges in the field.This book aims to provide brief overviews the NGS field with special focus on the challenges facing the NGS field, including information on different experimental platforms, assembly algorithms and software tools, assembly error correction approaches and the correlated challenges.
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Sequencing Technologies in Microbial Food Safety and Quality
Molecular landscape for food safety analysis is rapidly revolutionizing because of high resolution and value added resulting analysis of next-generation sequencing (NGS) approaches. These modern sequencing technologies drive worldwide advancements in food safety and quality. Sequencing Technologies in Microbial Food Safety and Quality reviews several practices in that NGS contributes to foodborne pathogens functional characterization, management and control. This book focuses on potential uses of sequencing technologies in microbial food safety and quality and highlights present challenges in the food industry. Key Features: Application of whole genome sequencing technologies in disease diagnostics, surveillance, transmission, and outbreak investigation in food sector Impact of sequencing tools in the area of food microbiology Recent advances in genomic DNA sequencing of microbial species from single cells Microbial bioinformatics resources for food microbiology High-throughput insertion tracking by deep sequencing for the analysis of food pathogensThis book includes contributions from experts who have manipulated sequencing tools in relation to microbial food safety and quality. Presenting comprehensive details about NGS approaches in food science, this book is an updated and reliable reference for food scientists, nutritionists, food product investigators to study and implement the sequencing technologies for developing quality and safe food. This book would also serve as informative resource for food industry officials, government researchers, food science or food nutrition students who seek comprehensive knowledge about the role of emerging sequencing technologies in revolutionizing the food industry.
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Pattern Recognition
Explores the heart of pattern recognition concepts, methods and applications using statistical, syntactic and neural approaches. Divided into four sections, it clearly demonstrates the similarities and differences among the three approaches. The second part deals with the statistical pattern recognition approach, starting with a simple example and finishing with unsupervised learning through clustering. Section three discusses the syntactic approach and explores such topics as the capabilities of string grammars and parsing; higher dimensional representations and graphical approaches. Part four presents an excellent overview of the emerging neural approach including an examination of pattern associations and feedforward nets. Along with examples, each chapter provides the reader with pertinent literature for a more in-depth study of specific topics.
R 8,326.00
Pattern Recognition
The multi-volume set LNCS 16812-16827 constitutes the refereed proceedings of the 28th International Conference on Pattern Recognition, ICPR 2026, held in Lyon, France, during August 17-21, 2026. The total of 714 full papers included in the proceedings was carefully reviewed and selected from 1362 submissions. They focus on topics such as Artificial Intelligence, Pattern Recognition and Machine Learning; Computer and Robot Vision; Image, Speech, Signal and Video Processing; Biometrics and Human Computer Interaction; Document Analysis and Recognition; and Biomedical Imaging and Bioinformatics.
R 4,345.40
Pattern Recognition
This book constitutes the proceedings of the 14th Mexican Conference on Pattern Recognition, MCPR 2022, which was held in planned to be held Ciudad Juárez, Mexico, in June 2022. The 33 papers presented in this volume were carefully reviewed and selected from 66 submissions. They are organized in the following topical sections: pattern recognition techniques; neural networks and deep learning; image and signal processing and analysis; natural language processing and recognition; robotics and remote sensing applications of pattern recognition; medical applications of pattern recognition.
R 3,332.94
Pattern Recognition
The multi-volume set LNCS 16812-16827 constitutes the refereed proceedings of the 28th International Conference on Pattern Recognition, ICPR 2026, held in Lyon, France, during August 17-21, 2026. The total of 714 full papers included in the proceedings was carefully reviewed and selected from 1362 submissions. They focus on topics such as Artificial Intelligence, Pattern Recognition and Machine Learning; Computer and Robot Vision; Image, Speech, Signal and Video Processing; Biometrics and Human Computer Interaction; Document Analysis and Recognition; and Biomedical Imaging and Bioinformatics.
R 4,347.14
Pattern Recognition
This book constitutes the refereed proceedings of the 36th German Conference on Pattern Recognition, GCPR 2014, held in Münster, Germany, in September 2014. The 58 revised full papers and 8 short papers were carefully reviewed and selected from 153 submissions. The papers are organized in topical sections on variational models for depth and flow, reconstruction, bio-informatics, deep learning and segmentation, feature computation, video interpretation, segmentation and labeling, image processing and analysis, human pose and people tracking, interpolation and inpainting.
R 2,253.69
Bioinformatics: A Practical Handbook Of Next Generation Sequencing And Its Applications
Rapid technological developments have led to increasingly efficient sequencing approaches. Next Generation Sequencing (NGS) is increasingly common and has become cost-effective, generating an explosion of sequenced data that need to be analyzed. The skills required to apply computational analysis to target research on a wide range of applications that include identifying causes of cancer, vaccine design, new antibiotics, drug development, personalized medicine and higher crop yields in agriculture are highly sought after.This invaluable book provides step-by-step guides to complex topics that make it easy for readers to perform essential analyses from raw sequenced data to answering important biological questions. It is an excellent hands-on material for teachers who conduct courses in bioinformatics and as a reference material for professionals. The chapters are written to be standalone recipes making it suitable for readers who wish to self-learn selected topics. Readers will gain skills necessary to work on sequenced data from NGS platforms and hence making themselves more attractive to employers who need skilled bioinformaticians to handle the deluge of data.
R 3,649.00
Pattern Recognition
This book constitutes the refereed proceedings of the 37th German Conference on Pattern Recognition, GCPR 2015, held in Aachen, Germany, in October 2015. The 45 revised full papers and one Young Researchers Forum presented were carefully reviewed and selected from 108 submissions. The papers are organized in topical sections on motion and reconstruction; mathematical foundations and image processing; biomedical image analysis and applications; human pose analysis; recognition and scene understanding.
R 2,219.58
Pattern Recognition
The multi-volume set LNCS 16812-16827 constitutes the refereed proceedings of the 28th International Conference on Pattern Recognition, ICPR 2026, held in Lyon, France, during August 17-21, 2026. The total of 714 full papers included in the proceedings was carefully reviewed and selected from 1362 submissions. They focus on topics such as Artificial Intelligence, Pattern Recognition and Machine Learning; Computer and Robot Vision; Image, Speech, Signal and Video Processing; Biometrics and Human Computer Interaction; Document Analysis and Recognition; and Biomedical Imaging and Bioinformatics.
R 4,346.12
Pattern Recognition
The book provides a comprehensive view of pattern recognition concepts and methods, illustrated with real-life applications in several areas. A CD-ROM offered with the book includes datasets and software tools, making it easier to follow in a hands-on fashion, right from the start.
R 2,015.00
Pattern Recognition
We are proud to present the proceedings of DAGM 2003, and we want to express our appreciation to the many people whose e?orts made this conference such a success. We received about 140 papers from around the world, but we could only acceptabouthalfofthesesubmissionsfororalandposterpresentationssoasnot to overload the agenda. Each paper was assigned three reviewers who followed a careful anonymous selection procedure. The quality of the research paper and its suitability for presentation were the main criteria in this very di?cult selection process.Our32reviewershadatoughjobevaluatingthesepapersand,ofcourse, the job was even tougher whenever contributions were rejected. We thank the reviewers for their time and e?ort. The program committee awarded prizes for the best papers, and we want to sincerely thank the donors. The following three invited papers were among the highlights: - Anil K. Jain (Michigan State University, USA): Who's Who? Challenges in Biometric Authentication - Michael Unser (EPFL Lausanne, Switzerland): Splines and Wavelets: New Perspectives and Opportunities for Pattern Recognition - Bernd Jahne ..(Heidelberg University, Germany): Image Sequence Analysis in Environmental and Life Sciences We are also very grateful and proud that several well-known experts enhanced our conference by o?ering tutorial sessions to our participants: - Christian Perwass, Gerald Sommer (Christian-Albrechts-University, Kiel, Germany): (Cli?ord) Algebra - Introduction and Applications - Hans-HeinrichBothe (TechnicalUniversityofDenmark,Oersted-DTU):- aptive Paradigms for Pattern Recognition - Peter Kau?, Oliver Schreer (Frauenhofer Institut fur .. Nachrichtentechnik, Heinrich-Hertz-Institute, Berlin, Germany): Concepts, Systems and Al- rithms for Immersive Video Communication - Michael Felsberg (Link. oping University, Sweden): Systematic Approaches to
R 4,030.00
Pattern Recognition
This book constitutes the refereed proceedings of the 8th Mexican Conference on Pattern Recognition, MCPR 2016, held in Guanajuato, Mexico, in June 2016. The 34 revised full papers presented were carefully reviewed and selected from 60 submissions. The papers are organized in topical sections on computer vision and image analysis; pattern recognition and artificial intelligent techniques; signal processing and analysis; and applications of pattern recognition.
R 2,185.65
Pattern Recognition
This 2-volume set LNCS 15297-15298 constitutes the refereed proceedings of the 46th Annual Conference of the German Association for Pattern Recognition, DAGM-GCPR 2024, held in Munich, Germany, during September 10-13, 2024.The 44 full papers included in these proceedings were carefully reviewed and selected from 81 submissions. They are organized in these topical sections: Part I: Clustering and Segmentation; Learning Techniques; Medical and Biological Applications; Uncertainty and Explainability.Part II: Modelling of Faces and Shapes; Image Generation and Reconstruction; 3D Analysis and Sythesis; Video Analysis; Photogrammetry and Remote Sensing.
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Algorithms for Next-Generation Sequencing Data
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.
R 5,184.00
Pattern Recognition
We are proud to present the DAGM 2002 proceedings, which are the result of the e?orts of many people. First, there are the many authors, who have submitted so many excellent cont- butions. We received more than 140 papers, of which we could only accept about half in order not to overload the program. Only about one in seven submitted papers could be delivered as an oral presentation, for the same reason. But it needs to be said that almost all submissions were of a really high quality. This strong program could not have been put together without the support of the Program Committee. They took their responsibility most seriously and we are very grateful for their reviewing work, which certainly took more time than anticipated, given the larger than usual number of submissions. Our three invited speakers added a strong multidisciplinary component to the conference. Dr. Antonio Criminisi of Microsoft Research (Redmond, USA) dem- strated how computer vision can literally bring a new dimension to the app- ciation of art. Prof. Philippe Schyns (Dept. of Psychology, Univ. of Glasgow, UK) presented intriguing insights into the human perception of patterns, e.g., the role of scale. Complementary to this presentation, Prof. Manabu Tanifuji of the Brain Science Institute in Japan (Riken) discussed novel neurophysiological ?ndings on how the brain deals with the recognition of objects and their parts.
R 3,094.64
Pattern Recognition
This book constitutes the proceedings of the 10th Mexican Conference on Pattern Recognition, MCPR 2018, held in Puebla, Mexico, in June 2018. The 28 papers presented in this volume were carefully reviewed and selected from 44 submissions. They were organized in topical sections named: pattern recognition principles; deep learning, neural networks and associative memories; data mining; and computer vision.
R 2,364.56
Pattern Recognition
This book constitutes the proceedings of the 13th Mexican Conference on Pattern Recognition, MCPR 2021, which was planned to be held in Mexico City, Mexico, in June 2021. The conference was instead held virtually.The 35 papers presented in this volume were carefully reviewed and selected from 75 submissions. They are organized in the following topical sections: artificial intelligence techniques and recognition; pattern recognition techniques; neural networks and deep learning; computer vision; image processing and analysis; and medical applications of pattern recognition.
R 2,189.03
Next Generation Sequencing in Forensic Science
Next Generation Sequencing in Forensic Science: A Primer addresses next generation sequencing (NGS) specific to its application to forensic science. The first part of the book offers a history of human identity approaches, including VNTR, RFLP, STR, and SNP DNA typing. It discusses the history of sequencing for human DNA typing, including Sanger sequencing, SNaPshot, pyrosequencing, and principles of next generation sequencing. The chapters present an overview of the forensically focused AmpliSeq, ForenSeq, Precision ID, PowerSeq, and QIAseq panels for human DNA typing using autosomal, Y and X chromosome STRs and SNPs using the MiSeq FGx and Ion Torrent System. The authors outline the steps included in DNA extraction and DNA quantitation that are performed prior to preparing libraries with the NGS kits.The second half of the book details the implementation of ForenSeq and Precision ID to amplify and tag targets to create the library, enrich targets to attach indexes and adaptors, perform library purification and normalization, pool the libraries, and load samples to the cartridge to perform the sequencing on the instrument. Coverage addresses the operation of the MiSeq FGx and Ion Chef, including creating a sample list, executing wash steps, performing NGS, understanding the run feedback files from the instrument, and troubleshooting. ForenSeq and Precision ID panel data analysis are explained, including how to analyze and interpret NGS data and output graphs and charts. The book concludes with mitochondrial DNA (mtDNA) sequencing and SNPs analysis, including the issue of heteroplasmy. The final chapters review forensic applications of microbial DNA, NGS in body fluid analysis, and challenges and considerations for future applications.FEATURES Focuses on human identification using traditional and NGS DNA typing methods targeting short tandem repeats (STRs) Applies the technology and its application to law enforcement investigations and identity and ancestry single nucleotide polymorphisms (SNPs) for investigational leads, mass disaster, and ancestry cases Presents the underlying principles of NGS in a clear, easy-to-understand format for practitioners and students studying DNA in forensic programsThis is the first book to prepare practitioners to utilize and implement this new technology in their lab for casework, highlighting early applications of how NGS results have been used in court. The book can be utilized for upper-level undergraduate and graduate students taking courses focused on NGS concepts. Readers are expected to have a basic understanding of molecular and cellular biology and DNA typing.
R 3,114.00
Next Generation Sequencing in Forensic Science
Next Generation Sequencing in Forensic Science: A Primer addresses next generation sequencing (NGS) specific to its application to forensic science. The first part of the book offers a history of human identity approaches, including VNTR, RFLP, STR, and SNP DNA typing. It discusses the history of sequencing for human DNA typing, including Sanger sequencing, SNaPshot, pyrosequencing, and principles of next generation sequencing. The chapters present an overview of the forensically focused AmpliSeq, ForenSeq, Precision ID, PowerSeq, and QIAseq panels for human DNA typing using autosomal, Y and X chromosome STRs and SNPs using the MiSeq FGx and Ion Torrent System. The authors outline the steps included in DNA extraction and DNA quantitation that are performed prior to preparing libraries with the NGS kits.The second half of the book details the implementation of ForenSeq and Precision ID to amplify and tag targets to create the library, enrich targets to attach indexes and adaptors, perform library purification and normalization, pool the libraries, and load samples to the cartridge to perform the sequencing on the instrument. Coverage addresses the operation of the MiSeq FGx and Ion Chef, including creating a sample list, executing wash steps, performing NGS, understanding the run feedback files from the instrument, and troubleshooting. ForenSeq and Precision ID panel data analysis are explained, including how to analyze and interpret NGS data and output graphs and charts. The book concludes with mitochondrial DNA (mtDNA) sequencing and SNPs analysis, including the issue of heteroplasmy. The final chapters review forensic applications of microbial DNA, NGS in body fluid analysis, and challenges and considerations for future applications.FEATURES Focuses on human identification using traditional and NGS DNA typing methods targeting short tandem repeats (STRs) Applies the technology and its application to law enforcement investigations and identity and ancestry single nucleotide polymorphisms (SNPs) for investigational leads, mass disaster, and ancestry cases Presents the underlying principles of NGS in a clear, easy-to-understand format for practitioners and students studying DNA in forensic programsThis is the first book to prepare practitioners to utilize and implement this new technology in their lab for casework, highlighting early applications of how NGS results have been used in court. The book can be utilized for upper-level undergraduate and graduate students taking courses focused on NGS concepts. Readers are expected to have a basic understanding of molecular and cellular biology and DNA typing.
R 8,572.00
Pattern Recognition
Pattern recognition is traditionally considered to cover all aspects of sensory data perception ranging from data acquisition, through preprocessing and low level analysis, to high level interpretation. Owing to its breadth and important application potential, the field of pattern recognition has been attracting considerable attention of researchers in academia and industry and consequently it has been witnessing a rapid growth and perpetual development. The need for dissemination of the latest results is being served by a host of international conferences on pattern recognition. One such series of meetings is regularly held in the United Kingdom under the auspices of the British Pattern Recognition Association. This volume contains papers presented at the BPRA 4th International Conference on Pattern Recognition held in Cambridge, March 28-30, 1988. Alongside the conventional topics of statistical and syntactic pattern recognition, contributions address issues in the hot subject areas of adaptive learning networks, computer vision, knowledge base methods and architectures for pattern processing, and among others, report progress in the application domains of document processing, speech and text recognition and shape analysis for industrial robotics. It is believed that the collection is not merely a report on current activities but that it will also be an important source of inspiration for future developments in the field of pattern recognition.
R 2,015.00
Pattern Recognition
The multi-volume set LNCS 16812-16827 constitutes the refereed proceedings of the 28th International Conference on Pattern Recognition, ICPR 2026, held in Lyon, France, during August 17-21, 2026. The total of 714 full papers included in the proceedings was carefully reviewed and selected from 1362 submissions. They focus on topics such as Artificial Intelligence, Pattern Recognition and Machine Learning; Computer and Robot Vision; Image, Speech, Signal and Video Processing; Biometrics and Human Computer Interaction; Document Analysis and Recognition; and Biomedical Imaging and Bioinformatics.
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Pattern Recognition
This book constitutes the refereed proceedings of the 9th Mexican Conference on Pattern Recognition, MCPR 2017, held in Huatulco, Mexico, in June 2017. The 29 revised full papers presented were carefully reviewed and selected from 55 submissions. The papers are organized in topical sections on pattern recognition and artificial intelligence techniques, image processing and analysis, robotics and remote sensing, natural language processing and recognition, applications of pattern recognition.
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Pattern Recognition
This 2-volume set LNCS 15297-15298 constitutes the refereed proceedings of the 46th Annual Conference of the German Association for Pattern Recognition, DAGM-GCPR 2024, held in Munich, Germany, during September 10-13, 2024.The 44 full papers included in these proceedings were carefully reviewed and selected from 81 submissions. They are organized in these topical sections:Part I: Clustering and Segmentation; Learning Techniques; Medical and Biological Applications; Uncertainty and Explainability.Part II: Modelling of Faces and Shapes; Image Generation and Reconstruction; 3D Analysis and Sythesis; Video Analysis; Photogrammetry and Remote Sensing.
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Next Generation Sequencing and Data Analysis
This textbook provides step-by-step protocols and detailed explanations for RNA Sequencing, ChIP-Sequencing and Epigenetic Sequencing applications. The reader learns how to perform Next Generation Sequencing data analysis, how to interpret and visualize the data, and acquires knowledge on the statistical background of the used software tools. Written for biomedical scientists and medical students, this textbook enables the end user to perform and comprehend various Next Generation Sequencing applications and their analytics without prior understanding in bioinformatics or computer sciences.
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Pattern Recognition
This book constitutes the proceedings of the 11th Mexican Conference on Pattern Recognition, MCPR 2019, held in Querétaro, Mexico, in June 2019. The 40 papers presented in this volume were carefully reviewed and selected from 86 submissions. They were organized in topical sections named: artificial intelligence techniques and recognition; computer vision; industrial and medical applications of pattern recognition; image processing and analysis; pattern recognition techniques; signal processing and analysis; natural language, and processing and recognition.
R 2,199.59
