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Scalable Methods For In Situ Genomics
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Book Synopsis Scalable Methods for in Situ Genomics by : Andrew Colin Payne
Download or read book Scalable Methods for in Situ Genomics written by Andrew Colin Payne and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We conclude with a discussion of IGS scaling properties, by which we can anticipate many-fold future improvements in yield and resolution. We anticipate IGS and related scalable in situ methods will be instrumental in unifying genomics and microscopy, enabling scientists to map genome organization from single base pairs to whole organisms and ultimately to connect genome structure and function.
Book Synopsis Scalable Methods for Genome Assembly by : Priyanka Ghosh
Download or read book Scalable Methods for Genome Assembly written by Priyanka Ghosh and published by . This book was released on 2019 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: De novo genome assembly is a fundamental problem in the field of computational biology. The goal is to reconstruct an unknown genome from short DNA fragments (called "reads") obtained from it. Over the last decade, with the advent of numerous next-generation sequencing (NGS) platforms (e.g., Illumina, 454 Roche), billions of reads can be generated in a matter of hours, leading to vast amounts of data accumulation per day. This has necessitated efficient parallelization of the assembly process to meet the growing data demands. While multiple parallel solutions to the problem have been proposed in the past, there still exists a gap in terms of the processing power between massively parallel NGS technologies and the ability of current state-of-the-art assemblers to analyze and assemble large and complex genomes. Conducting genome assembly at scale remains a challenge owing to the intense computational and memory requirements of the problem, coupled with inherent complexities in existing parallel tools associated with data movement, use of complex data structures, unstructured memory accesses and repeated I/O operations. In this dissertation, we address the challenges of conducting genome assembly at scale and develop new methods for conducting extreme-scale genome assembly for microbial and complex eukaryotic genomes. Our approach to the problem is two-fold, wherein we make the following contributions: i) FastEtch- a new method targeting fast and space-efficient assemblies, using probabilistic data structures (Count-Min sketch) that executes efficiently on shared-memory platforms with a minimal computational footprint (both memory and time). ii) PaKman- a fully distributed method that tackles assembly of large genomes through the combination of a novel data-structure (PaK-Graph) and algorithmic strategies to simplify the communication and I/O footprint during the assembly process. We present an extensive performance and qualitative evaluation of both our algorithms including comparisons to other state-of-the-art methods. Our results demonstrate that FastEtch can yield one of the best time-memory-quality trade-offs, when compared against many state-of-the-art genome assemblers. PaKman has shown the ability to achieve near-linear speedups on up to 8K cores; outperform state-of-the-art distributed and shared memory tools in performance while delivering comparable (if not better) quality; and reduce time to solution significantly.
Book Synopsis Scalable Parallel Algorithms for Genome Analysis by : Evangelos Georganas
Download or read book Scalable Parallel Algorithms for Genome Analysis written by Evangelos Georganas and published by . This book was released on 2016 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: A critical problem for computational genomics is the problem of de novo genome assembly: the development of robust scalable methods for transforming short randomly sampled "shotgun" sequences, namely reads, into the contiguous and accurate reconstruction of complex genomes. These reads are significantly shorter (e.g. hundreds of bases long) than the size of chromosomes and also include errors. While advanced methods exist for assembling the small and haploid genomes of prokaryotes, the genomes of eukaryotes are more complex. Moreover, de novo assembly has been unable to keep pace with the flood of data, due to the dramatic increases in genome sequencer capabilities, combined with the computational requirements and the algorithmic complexity of assembling large scale genomes and metagenomes. In this dissertation, we address this challenge head on by developing parallel algorithms for de novo genome assembly with the ambition to scale to massive concurrencies. Our work is based on the Meraculous assembler, a state-of-the-art de novo assembler for short reads developed at JGI. Meraculous identifies non-erroneous overlapping substrings of length k (k-mers) with high quality extensions and uniquely assembles genome regions into uncontested sequences called contigs by constructing and traversing a de Bruijn graph of k-mers, a special graph that is used to represent overlaps among k-mers. The original reads are subsequently aligned onto the contigs to obtain information regarding the relative orientation of the contigs. Contigs are then linked together to create scaffolds, sequences of contigs that may contain gaps among them. Finally gaps are filled using localized assemblies based on the original reads. First, we design efficient scalable algorithms for k-mer analysis and contig generation. K-mer analysis is characterized by intensive communication and I/O requirements and our parallel algorithms successfully reduce the memory requirements by 7×. Then, contig generation relies on efficient parallelization of the de Bruijn graph construction and traversal, which necessitates a distributed hash table and is a key component of most de novo assemblers. We present a novel algorithm that leverages one-sided communication capabilities of the UPC to facilitate the requisite fine-grained, irregular parallelism and the avoidance of data hazards. The sequence alignment is characterized by intensive I/O and large computation requirements. We introduce mer-Aligner, a highly parallel sequence aligner that employs parallelism in all of its components. Finally, this thesis details the parallelization of the scaffolding modules, enabling the first massively scalable, high quality, complete end-to-end de novo assembly pipeline. Experimental large-scale results using human and wheat genomes demonstrate efficient performance and scalability on thousands of cores. Compared to the original Meraculous code, which requires approximately 48 hours to assemble the human genome, our pipeline called HipMer computes the assembly in only 4 minutes using 23,040 cores of Edison - an overall speedup of approximately 720×. In the last part of the dissertation we tackle the problem of metagenome assembly. Metagenomics is currently the leading technology to study the uncultured microbial diversity. While accessing an unprecedented number of environmental samples that consist of thousands of individual microbial genomes is now possible, the bottleneck is becoming computational, since the sequencing cost improvements exceed that of Moore's Law. Metagenome assembly is further complicated by repeated sequences across genomes, polymorphisms within a species and variable frequency of the genomes within the sample. In our work we repurpose HipMer components for the problem of metagenome assembly and we design a versatile, high-performance metagenome assembly pipeline that outperforms state-of-the-art tools in both quality and performance.
Book Synopsis Scalable Algorithms for Analysis of Genomic Diversity Data by : Bogdan Pașaniuc
Download or read book Scalable Algorithms for Analysis of Genomic Diversity Data written by Bogdan Pașaniuc and published by . This book was released on 2008 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Scaling Single Cell Genomics Analysis to Millions of Cells by : Benjamin Ezra Parks
Download or read book Scaling Single Cell Genomics Analysis to Millions of Cells written by Benjamin Ezra Parks and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improved experimental methods in single cell genomics have increased dataset sizes by two orders of magnitude in the last five years, such that software scalability is quickly becoming a key bottleneck in our ability to analyze and understand multi-million cell atlases. Most analysis methods load full datasets in memory, resulting in excessive memory usage that scales one-to-one with dataset size. Furthermore, existing compressed storage formats for single cell datasets are so slow to read that practical analysis must be performed on uncompressed data. This work describes BPCells, a software package for scalable analysis of massive single cell RNA-seq and ATAC-seq datasets. BPCells provides lossless, seekable bitpacking compression for scATAC-seq fragment alignments and sparse single cell counts matrices. These compression formats are so fast that a single thread can decompress a dataset faster than loading an uncompressed version from a hard drive. Additionally, BPCells implements disk-backed streaming computations that can reduce memory requirements by two orders of magnitude compared to popular tools like Scanpy and Seurat, while incurring little or no speed penalty. Notably, BPCells can reproduce the results of existing software packages to within numerical precision, making it a drop-in replacement for existing tools. This work covers the design and implementation of BPCells, along with applications of single cell analysis.
Book Synopsis The Mouse Nervous System by : Charles Watson
Download or read book The Mouse Nervous System written by Charles Watson and published by Academic Press. This book was released on 2011-11-28 with total page 815 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Mouse Nervous System provides a comprehensive account of the central nervous system of the mouse. The book is aimed at molecular biologists who need a book that introduces them to the anatomy of the mouse brain and spinal cord, but also takes them into the relevant details of development and organization of the area they have chosen to study. The Mouse Nervous System offers a wealth of new information for experienced anatomists who work on mice. The book serves as a valuable resource for researchers and graduate students in neuroscience. Systematic consideration of the anatomy and connections of all regions of the brain and spinal cord by the authors of the most cited rodent brain atlases A major section (12 chapters) on functional systems related to motor control, sensation, and behavioral and emotional states A detailed analysis of gene expression during development of the forebrain by Luis Puelles, the leading researcher in this area Full coverage of the role of gene expression during development and the new field of genetic neuroanatomy using site-specific recombinases Examples of the use of mouse models in the study of neurological illness
Book Synopsis Scalable Optimization Algorithms for High-throughput Genomic Data by :
Download or read book Scalable Optimization Algorithms for High-throughput Genomic Data written by and published by . This book was released on 2015 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Distance-aware Algorithms for Scalable Evolutionary and Ecological Analyses by : Metin Balaban
Download or read book Distance-aware Algorithms for Scalable Evolutionary and Ecological Analyses written by Metin Balaban and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thanks to the advances in sequencing technologies in the last two decades, the set of available whole-genome sequences has been expanding rapidly. One of the challenges in phylogenetics is accurate large-scale phylogenetic inference based on whole-genome sequences. A related challenge is using incomplete genome-wide data in an assembly-free manner for accurate sample identification with reference to phylogeny. This dissertation proposes new scalable and accurate algorithms to address these two challenges. First, I present a family of scalable methods called TreeCluster for breaking a large set of sequences into evolutionary homogeneous clusters. Second, I present two algorithms for accurate phylogenetic placement of genomic sequences on ultra-large single-gene and whole-genome based trees. The first version, APPLES, scales linearly with the reference size while APPLES-2 scales sub-linearly thanks to a divide-and-conquer strategy based on the TreeCluster method. Third, I develop a solution for assembly-free sample phylogenetic placement for a particularly challenging case when the specimen is a mixture of two cohabiting species or a hybrid of two species. Fourth, I address one limitation of assembly-free methods--their reliance on simple models of sequence evolution--by developing a technique to compute evolutionary distances under a complex 4-parameter model called TK4. Finally, I introduce a divide-and-conquer workflow for incrementally growing and updating ultra-large phylogenies using many of the ingredients developed in other chapters. This workflow (uDance) is accurate in simulations and can build a 200,000-genome microbial tree-of-life based on 388 marker genes.
Book Synopsis Scalable and Accurate Algorithms for Search in Genomic Big Data and Analysis of Genetic Variants by : Chen Sun
Download or read book Scalable and Accurate Algorithms for Search in Genomic Big Data and Analysis of Genetic Variants written by Chen Sun and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Next generation sequencing technology has been extensively used in biological and medical research. With abundant genomic data generated, new challenges also arise: the expanding capacity of genomic data pushes the boundaries of current searching and analysis methods. Two of the main challenges for genomic big data are how to efficiently search to identify datasets of interest, and how to deeply analyze the large volume of data to discover new knowledge in genomics.In this dissertation, we present four research achievements that aim to tackle the above two challenges in genomic data. The AllSome Sequence Bloom Tree data structure and associated search algorithms are first introduced to help find datasets of interest, filter out futile ones, and narrow down the data size. To meet the demand of further deep analysis, several scalable algorithms for sequence analysis are introduced. Based on them, a genetic variant analysis toolkit is developed, which contains three methods (ISVDA, VarGeno and VarMatch), which address different directions of small genetic variant study. ISVDA is an iterative small variant discovery algorithm that can detect small genetic variants that are previously hard to detect. VarGeno is a fast and accurate single nucleotide polymorphism genotyping tool. VarMatch is introduced to find high confidence variants among multiple variant detection results. It can also be used to evaluate variant calling results.
Book Synopsis Infrastructure for Scalable Analysis of Genomic Variation by : Adam M. Novak
Download or read book Infrastructure for Scalable Analysis of Genomic Variation written by Adam M. Novak and published by . This book was released on 2017 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scale of the problems which human genomics is asked to solve necessitates that the field develop an ability to integrate and synthesize information across the entire human population. The abstraction of a single-copy human reference genome assembly, and the linear coordinate space that it induces, are more of a hindrance than a help at these scales. They can only ever represent one sample at any given place, and they make combining information about human variation across multiple studies and modalities difficult. To rectify these problems, I propose the construction and adoption of a graph-based alternative to the human reference genome assembly: a Human Genome Variation Map. I present here four research projects. The first is a theory of mapping to references that is extensible to graphs. The second describes a novel data structure for embedding individual haplotype sequences into a graph reference. The third surveys graph construction techniques to discover methods that produce graphs yielding read mapping and variant calling results superior to those obtained with linear, variation-free references. The fourth extends these improvement results to chromosome-scale graphs constructed from multiple sources and modalities of variation data. These four projects describe a research program aimed towards the eventual release of an official Human Genome Variation Map build, providing a piece of vital infrastructure for the analysis of human genomic variation at population scale.
Book Synopsis Leveraging Big Data and Machine Learning Technologies for Accurate and Scalable Genomic Analysis by : Lizhen Shi
Download or read book Leveraging Big Data and Machine Learning Technologies for Accurate and Scalable Genomic Analysis written by Lizhen Shi and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The revolution in next-generation DNA sequencing technologies is leading to explosive data growth in genomics, posing a significant challenge to the computing infrastructure and software algorithms for genomics analysis. Various big data and machine learning technologies have been explored to mine the complex large-scale genomics data. In this dissertation, we first survey some of the existing scalable approaches for genomic analysis and identify the limitations of these solutions. We then investigate the still-unsolved challenges faced by computational biologists in large-scale genomic analysis. Specifically, in terms of using MapReduce-based bioinformatics analysis tools, Hadoop has a large number of parameters to control the behavior of a MapReduce job. The unique characteristics of MapReduce-based bioinformatics tools makes all the existing guidelines inapplicable; In Metagenomics, the intrinsic complexity and massive quantity of metagenomic data create tremendous challenges for microbial genomes recovery; When we applying NLP technologies to genome analysis, the enormous k-mer size and the low-frequency k-mers caused by the sequencing errors post significant challenges for k-mer embedding. To overcome the aforementioned problems, this dissertation introduces three countermeasures. First, we extract the key parameters from the large space of MapReduce parameters and present an exemplary case for tuning MapReduce-based bioinformatics analysis tools based on their unique characteristics. Second, we design and implement SpaRC, a scalable sequence clustering tool built on Apache Spark, to partition reads based on their molecules of origin to enable downstream assembly optimization in Metagenomics. SpaRC achieves high clustering accuracy, with the capability of scaling near linearly with the data size and the number of computing nodes. Lastly, we leverage Locality Sensitive Hashing (LSH) to overcome the two challenges faced by $k$-mer embedding and design LSHvec. With LSHvec, a DNA sequence can be represented as a dense low-dimensional vector. The trained sequence vectors are capable of capturing the rich characteristics of DNA sequences and can be fed to machine learning models for a wide variety of applications in genomics analysis. We compare our approaches with existing solutions. The experiments demonstrate our approaches achieve the state-of-the-art results. We open source our implementation of SpaRC and LSHvec to facilitate comparison of future work and inspire future research in genomic analysis.
Book Synopsis Toward a More Accurate Genome by : William Jacob Benhardt Biesinger
Download or read book Toward a More Accurate Genome written by William Jacob Benhardt Biesinger and published by . This book was released on 2014 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: High-throughput sequencing enables basic and translational biology to query the mechanics of both life and disease at single-nucleotide resolution and with breadth that spans the genome. This revolutionary technology is a major tool in biomedical research, impacting our understanding of life's most basic mechanics and affecting human health and medicine. Unfortunately, this important technology produces very large, error-prone datasets that require substantial computational processing before experimental conclusions can be made. Since errors and hidden biases in the data may influence empirically-derived conclusions, accurate algorithms and models of the data are critical. This thesis focuses on the development of statistical models for high-throughput sequencing data which are capable of handling errors and which are built to reflect biological realities. First, we focus on increasing the fraction of the genome that can be reliably queried in biological experiments using high-throughput sequencing methods by expanding analysis into repeat regions of the genome. The method allows partial observation of the gene regulatory network topology through identification of transcription factor binding sites using Chromatin Immunoprecipitation followed by high-throughput sequencing (ChIP-seq). Binding site clustering, or "peak-calling", can be frustrated by the complex, repetitive nature of genomes. Traditionally, these regions are censored from any interpretation, but we re-enable their interpretation using a probabilistic method for realigning problematic DNA reads. Second, we leverage high-throughput sequencing data for the empirical discovery of underlying epigenetic cell state, enabled through analysis of combinations of histone marks. We use a novel probabilistic model to perform spatial and temporal clustering of histone marks and capture mark combinations that correlate well with cell activity. A first in epigenetic modeling with high-throughput sequencing data, we not only pool information across cell types, but directly model the relationship between them, improving predictive power across several datasets. Third, we develop a scalable approach to genome assembly using high-throughput sequencing reads. While several assembly solutions exist, most don't scale well to large datasets, requiring computers with copious memory to assemble large genomes. Throughput continues to increase and the large datasets available today and in the near future will require truly scalable methods. We present a promising distributed method for genome assembly which distributes the de Bruijn graph across many computers and seamlessly spills to disk when main memory is insufficient. We also show novel graph cleaning algorithms which should handle increased errors from large datasets better than traditional graph structure-based cleaning. High-throughput sequencing plays an important role in biomedical research, and has already affected human health and medicine. Future experimental procedures will continue to rely on statistical methods to provide crucial error and bias correction, in addition to modeling expected outcomes. Thus, further development of robust statistical models is critical to the future high-throughput sequencing, ensuring a strong foundation for correct biological conclusions.
Book Synopsis Molecular Diagnostics by : George P. Patrinos
Download or read book Molecular Diagnostics written by George P. Patrinos and published by Academic Press. This book was released on 2016-10-27 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: Molecular Diagnostics, Third Edition, focuses on the technologies and applications that professionals need to work in, develop, and manage a clinical diagnostic laboratory. Each chapter contains an expert introduction to each subject that is next to technical details and many applications for molecular genetic testing that can be found in comprehensive reference lists at the end of each chapter. Contents are divided into three parts, technologies, application of those technologies, and related issues. The first part is dedicated to the battery of the most widely used molecular pathology techniques. New chapters have been added, including the various new technologies involved in next-generation sequencing (mutation detection, gene expression, etc.), mass spectrometry, and protein-specific methodologies. All revised chapters have been completely updated, to include not only technology innovations, but also novel diagnostic applications. As with previous editions, each of the chapters in this section includes a brief description of the technique followed by examples from the area of expertise from the selected contributor. The second part of the book attempts to integrate previously analyzed technologies into the different aspects of molecular diagnostics, such as identification of genetically modified organisms, stem cells, pharmacogenomics, modern forensic science, molecular microbiology, and genetic diagnosis. Part three focuses on various everyday issues in a diagnostic laboratory, from genetic counseling and related ethical and psychological issues, to safety and quality management. - Presents a comprehensive account of all new technologies and applications used in clinical diagnostic laboratories - Explores a wide range of molecular-based tests that are available to assess DNA variation and changes in gene expression - Offers clear translational presentations by the top molecular pathologists, clinical chemists, and molecular geneticists in the field
Book Synopsis Metagenomics by : Muniyandi Nagarajan
Download or read book Metagenomics written by Muniyandi Nagarajan and published by Academic Press. This book was released on 2017-10-29 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metagenomics: Perspectives, Methods, and Applications provides thorough coverage of the growing field of metagenomics. A diverse range of chapters from international experts offer an introduction to the field and examine methods for metagenomic analysis of microbiota, metagenomic computational tools, and recent metagenomic studies in various environments. The emphasis on application makes this text particularly useful for applied researchers, practitioners, clinicians and students seeking to employ metagenomic approaches to advance knowledge in the biomedical and life sciences. Case-study based application chapters examine topics ranging from viral metagenome profiling, metagenomics in oral disease and health, metagenomic insights into the human gut microbiome and metabolic syndromes, and more. Additionally, perspectives on future potential at the end of each chapter provoke new thought and motivations for continued study in this exciting and fruitful research area. Provides thorough coverage of the rapidly growing field of metagenomics, with an emphasis on applications of relevance to translational researchers, practitioners, clinicians and students Features a diverse range of chapters from international experts that offer an introduction to the field and examine methods for metagenomic analysis of microbiota, metagenomic computational tools and research pipelines Highlights perspectives on future potential at the end of each chapter to provoke new thought and motivations for continued study in this exciting and fruitful research area
Download or read book Genomics written by Charles R. Cantor and published by John Wiley & Sons. This book was released on 2004-01-06 with total page 621 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique exploration of the principles and methods underlying the Human Genome Project and modern molecular genetics and biotechnology-from two top researchers In Genomics, Charles R. Cantor, former director of the Human Genome Project, and Cassandra L. Smith give the first integral overview of the strategies and technologies behind the Human Genome Project and the field of molecular genetics and biotechnology. Written with a range of readers in mind-from chemists and biologists to computer scientists and engineers-the book begins with a review of the basic properties of DNA and the chromosomes that package it in cells. The authors describe the three main techniques used in DNA analysis-hybridization, polymerase chain reaction, and electrophoresis-and present a complete exploration of DNA mapping in its many different forms. By explaining both the theoretical principles and practical foundations of modern molecular genetics to a wide audience, the book brings the scientific community closer to the ultimate goal of understanding the biological function of DNA. Genomics features: * Topical organization within chapters for easy reference * A discussion of the developing methods of sequencing, such as sequencing by hybridization (SBH) in which data is read through words instead of letters * Detailed explanations and critical evaluations of the many different types of DNA maps that can be generated-including cytogenic and restriction maps as well as interspecies cell hybrids * Informed predictions for the future of DNA sequencing
Book Synopsis Bioinformatics of Genome Regulation, Volume I, 2nd Edition by : Yuriy L. Orlov
Download or read book Bioinformatics of Genome Regulation, Volume I, 2nd Edition written by Yuriy L. Orlov and published by Frontiers Media SA. This book was released on with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher’s note: In this 2nd edition, the following article has been updated: Orlov YL, Tatarinova TV, Oparina NY, Galieva ER and Baranova AV (2021) Editorial: Bioinformatics of Genome Regulation, Volume I. Front. Genet. 12:803273. doi: 10.3389/fgene.2021.803273
Download or read book Cytogenomics written by Thomas Liehr and published by Academic Press. This book was released on 2021-05-25 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cytogenomics demonstrates that chromosomes are crucial in understanding the human genome and that new high-throughput approaches are central to advancing cytogenetics in the 21st century. After an introduction to (molecular) cytogenetics, being the basic of all cytogenomic research, this book highlights the strengths and newfound advantages of cytogenomic research methods and technologies, enabling researchers to jump-start their own projects and more effectively gather and interpret chromosomal data. Methods discussed include banding and molecular cytogenetics, molecular combing, molecular karyotyping, next-generation sequencing, epigenetic study approaches, optical mapping/karyomapping, and CRISPR-cas9 applications for cytogenomics. The book’s second half demonstrates recent applications of cytogenomic techniques, such as characterizing 3D chromosome structure across different tissue types and insights into multilayer organization of chromosomes, role of repetitive elements and noncoding RNAs in human genome, studies in topologically associated domains, interchromosomal interactions, and chromoanagenesis. This book is an important reference source for researchers, students, basic and translational scientists, and clinicians in the areas of human genetics, genomics, reproductive medicine, gynecology, obstetrics, internal medicine, oncology, bioinformatics, medical genetics, and prenatal testing, as well as genetic counselors, clinical laboratory geneticists, bioethicists, and fertility specialists. Offers applied approaches empowering a new generation of cytogenomic research using a balanced combination of classical and advanced technologies Provides a framework for interpreting chromosome structure and how this affects the functioning of the genome in health and disease Features chapter contributions from international leaders in the field
