Introduction to Single Cell Omics

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Publisher : Frontiers Media SA
ISBN 13 : 2889459209
Total Pages : 129 pages
Book Rating : 4.8/5 (894 download)

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Book Synopsis Introduction to Single Cell Omics by : Xinghua Pan

Download or read book Introduction to Single Cell Omics written by Xinghua Pan and published by Frontiers Media SA. This book was released on 2019-09-19 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Single-cell omics is a progressing frontier that stems from the sequencing of the human genome and the development of omics technologies, particularly genomics, transcriptomics, epigenomics and proteomics, but the sensitivity is now improved to single-cell level. The new generation of methodologies, especially the next generation sequencing (NGS) technology, plays a leading role in genomics related fields; however, the conventional techniques of omics require number of cells to be large, usually on the order of millions of cells, which is hardly accessible in some cases. More importantly, harnessing the power of omics technologies and applying those at the single-cell level are crucial since every cell is specific and unique, and almost every cell population in every systems, derived in either vivo or in vitro, is heterogeneous. Deciphering the heterogeneity of the cell population hence becomes critical for recognizing the mechanism and significance of the system. However, without an extensive examination of individual cells, a massive analysis of cell population would only give an average output of the cells, but neglect the differences among cells. Single-cell omics seeks to study a number of individual cells in parallel for their different dimensions of molecular profile on genome-wide scale, providing unprecedented resolution for the interpretation of both the structure and function of an organ, tissue or other system, as well as the interaction (and communication) and dynamics of single cells or subpopulations of cells and their lineages. Importantly single-cell omics enables the identification of a minor subpopulation of cells that may play a critical role in biological process over a dominant subpolulation such as a cancer and a developing organ. It provides an ultra-sensitive tool for us to clarify specific molecular mechanisms and pathways and reveal the nature of cell heterogeneity. Besides, it also empowers the clinical investigation of patients when facing a very low quantity of cell available for analysis, such as noninvasive cancer screening with circulating tumor cells (CTC), noninvasive prenatal diagnostics (NIPD) and preimplantation genetic test (PGT) for in vitro fertilization. Single-cell omics greatly promotes the understanding of life at a more fundamental level, bring vast applications in medicine. Accordingly, single-cell omics is also called as single-cell analysis or single-cell biology. Within only a couple of years, single-cell omics, especially transcriptomic sequencing (scRNA-seq), whole genome and exome sequencing (scWGS, scWES), has become robust and broadly accessible. Besides the existing technologies, recently, multiplexing barcode design and combinatorial indexing technology, in combination with microfluidic platform exampled by Drop-seq, or even being independent of microfluidic platform but using a regular PCR-plate, enable us a greater capacity of single cell analysis, switching from one single cell to thousands of single cells in a single test. The unique molecular identifiers (UMIs) allow the amplification bias among the original molecules to be corrected faithfully, resulting in a reliable quantitative measurement of omics in single cells. Of late, a variety of single-cell epigenomics analyses are becoming sophisticated, particularly single cell chromatin accessibility (scATAC-seq) and CpG methylation profiling (scBS-seq, scRRBS-seq). High resolution single molecular Fluorescence in situ hybridization (smFISH) and its revolutionary versions (ex. seqFISH, MERFISH, and so on), in addition to the spatial transcriptome sequencing, make the native relationship of the individual cells of a tissue to be in 3D or 4D format visually and quantitatively clarified. On the other hand, CRISPR/cas9 editing-based In vivo lineage tracing methods enable dynamic profile of a whole developmental process to be accurately displayed. Multi-omics analysis facilitates the study of multi-dimensional regulation and relationship of different elements of the central dogma in a single cell, as well as permitting a clear dissection of the complicated omics heterogeneity of a system. Last but not the least, the technology, biological noise, sequence dropout, and batch effect bring a huge challenge to the bioinformatics of single cell omics. While significant progress in the data analysis has been made since then, revolutionary theory and algorithm logics for single cell omics are expected. Indeed, single-cell analysis exert considerable impacts on the fields of biological studies, particularly cancers, neuron and neural system, stem cells, embryo development and immune system; other than that, it also tremendously motivates pharmaceutic RD, clinical diagnosis and monitoring, as well as precision medicine. This book hereby summarizes the recent developments and general considerations of single-cell analysis, with a detailed presentation on selected technologies and applications. Starting with the experimental design on single-cell omics, the book then emphasizes the consideration on heterogeneity of cancer and other systems. It also gives an introduction of the basic methods and key facts for bioinformatics analysis. Secondary, this book provides a summary of two types of popular technologies, the fundamental tools on single-cell isolation, and the developments of single cell multi-omics, followed by descriptions of FISH technologies, though other popular technologies are not covered here due to the fact that they are intensively described here and there recently. Finally, the book illustrates an elastomer-based integrated fluidic circuit that allows a connection between single cell functional studies combining stimulation, response, imaging and measurement, and corresponding single cell sequencing. This is a model system for single cell functional genomics. In addition, it reports a pipeline for single-cell proteomics with an analysis of the early development of Xenopus embryo, a single-cell qRT-PCR application that defined the subpopulations related to cell cycling, and a new method for synergistic assembly of single cell genome with sequencing of amplification product by phi29 DNA polymerase. Due to the tremendous progresses of single-cell omics in recent years, the topics covered here are incomplete, but each individual topic is excellently addressed, significantly interesting and beneficial to scientists working in or affiliated with this field.

Precision Medicine for Investigators, Practitioners and Providers

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Publisher : Academic Press
ISBN 13 : 0128191791
Total Pages : 640 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Precision Medicine for Investigators, Practitioners and Providers by : Joel Faintuch

Download or read book Precision Medicine for Investigators, Practitioners and Providers written by Joel Faintuch and published by Academic Press. This book was released on 2019-11-16 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precision Medicine for Investigators, Practitioners and Providers addresses the needs of investigators by covering the topic as an umbrella concept, from new drug trials to wearable diagnostic devices, and from pediatrics to psychiatry in a manner that is up-to-date and authoritative. Sections include broad coverage of concerning disease groups and ancillary information about techniques, resources and consequences. Moreover, each chapter follows a structured blueprint, so that multiple, essential items are not overlooked. Instead of simply concentrating on a limited number of extensive and pedantic coverages, scholarly diagrams are also included. Provides a three-pronged approach to precision medicine that is focused on investigators, practitioners and healthcare providers Covers disease groups and ancillary information about techniques, resources and consequences Follows a structured blueprint, ensuring essential chapters items are not overlooked

Computational Optimal Transport

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Publisher : Foundations and Trends(r) in M
ISBN 13 : 9781680835502
Total Pages : 272 pages
Book Rating : 4.8/5 (355 download)

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Book Synopsis Computational Optimal Transport by : Gabriel Peyre

Download or read book Computational Optimal Transport written by Gabriel Peyre and published by Foundations and Trends(r) in M. This book was released on 2019-02-12 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of Optimal Transport (OT) is to define geometric tools that are useful to compare probability distributions. Their use dates back to 1781. Recent years have witnessed a new revolution in the spread of OT, thanks to the emergence of approximate solvers that can scale to sizes and dimensions that are relevant to data sciences. Thanks to this newfound scalability, OT is being increasingly used to unlock various problems in imaging sciences (such as color or texture processing), computer vision and graphics (for shape manipulation) or machine learning (for regression, classification and density fitting). This monograph reviews OT with a bias toward numerical methods and their applications in data sciences, and sheds lights on the theoretical properties of OT that make it particularly useful for some of these applications. Computational Optimal Transport presents an overview of the main theoretical insights that support the practical effectiveness of OT before explaining how to turn these insights into fast computational schemes. Written for readers at all levels, the authors provide descriptions of foundational theory at two-levels. Generally accessible to all readers, more advanced readers can read the specially identified more general mathematical expositions of optimal transport tailored for discrete measures. Furthermore, several chapters deal with the interplay between continuous and discrete measures, and are thus targeting a more mathematically-inclined audience. This monograph will be a valuable reference for researchers and students wishing to get a thorough understanding of Computational Optimal Transport, a mathematical gem at the interface of probability, analysis and optimization.

Evolution of Translational Omics

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Publisher : National Academies Press
ISBN 13 : 0309224187
Total Pages : 354 pages
Book Rating : 4.3/5 (92 download)

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Book Synopsis Evolution of Translational Omics by : Institute of Medicine

Download or read book Evolution of Translational Omics written by Institute of Medicine and published by National Academies Press. This book was released on 2012-09-13 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

Graph Representation Learning

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Publisher : Springer Nature
ISBN 13 : 3031015886
Total Pages : 141 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Graph Representation Learning by : William L. William L. Hamilton

Download or read book Graph Representation Learning written by William L. William L. Hamilton and published by Springer Nature. This book was released on 2022-06-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.

Computational Genomics with R

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Publisher : CRC Press
ISBN 13 : 1498781861
Total Pages : 463 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Computational Genomics with R by : Altuna Akalin

Download or read book Computational Genomics with R written by Altuna Akalin and published by CRC Press. This book was released on 2020-12-16 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

Computational Methods for Single-Cell Data Analysis

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Publisher : Humana Press
ISBN 13 : 9781493990566
Total Pages : 271 pages
Book Rating : 4.9/5 (95 download)

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Book Synopsis Computational Methods for Single-Cell Data Analysis by : Guo-Cheng Yuan

Download or read book Computational Methods for Single-Cell Data Analysis written by Guo-Cheng Yuan and published by Humana Press. This book was released on 2019-02-14 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This detailed book provides state-of-art computational approaches to further explore the exciting opportunities presented by single-cell technologies. Chapters each detail a computational toolbox aimed to overcome a specific challenge in single-cell analysis, such as data normalization, rare cell-type identification, and spatial transcriptomics analysis, all with a focus on hands-on implementation of computational methods for analyzing experimental data. 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 cutting-edge, Computational Methods for Single-Cell Data Analysis aims to cover a wide range of tasks and serves as a vital handbook for single-cell data analysis.

Unsupervised Feature Extraction Applied to Bioinformatics

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Publisher : Springer Nature
ISBN 13 : 3030224562
Total Pages : 321 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Unsupervised Feature Extraction Applied to Bioinformatics by : Y-h. Taguchi

Download or read book Unsupervised Feature Extraction Applied to Bioinformatics written by Y-h. Taguchi and published by Springer Nature. This book was released on 2019-08-23 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have become popular, unsupervised methods have their own advantages. He argues that this is the case because unsupervised methods are easy to learn since tensor decomposition is a conventional linear methodology. This book starts from very basic linear algebra and reaches the cutting edge methodologies applied to difficult situations when there are many features (variables) while only small number of samples are available. The author includes advanced descriptions about tensor decomposition including Tucker decomposition using high order singular value decomposition as well as higher order orthogonal iteration, and train tenor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topics. Allows readers to analyze data sets with small samples and many features; Provides a fast algorithm, based upon linear algebra, to analyze big data; Includes several applications to multi-view data analyses, with a focus on bioinformatics.

Precision Medicine in Cancer Therapy

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Publisher : Springer
ISBN 13 : 3030163911
Total Pages : 283 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Precision Medicine in Cancer Therapy by : Daniel D. Von Hoff

Download or read book Precision Medicine in Cancer Therapy written by Daniel D. Von Hoff and published by Springer. This book was released on 2019-06-17 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest advances in precision medicine in some of the most common cancer types, including hematological, lung and breast malignancies. It also discusses emerging technologies that are making a significant impact on precision medicine in cancer therapy. In addition to describing specific approaches that have already entered clinical practice, the book explores new concepts and tools that are being developed. Precision medicine aims to deliver personalized healthcare tailored to a patient’s genetics, lifestyle and environment, and cancer therapy is one of the areas in which it has flourished in recent years. Documenting the latest advances, this book is of interest to physicians and clinical fellows in the front line of the war on cancer, as well as to basic scientists working in the fields of cancer biology, drug development, biomarker discovery, and biomedical engineering. The contributing authors include translational physicians with first-hand experience in precision patient care.

Compositional Data Analysis

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Publisher : John Wiley & Sons
ISBN 13 : 0470711353
Total Pages : 405 pages
Book Rating : 4.4/5 (77 download)

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Book Synopsis Compositional Data Analysis by : Vera Pawlowsky-Glahn

Download or read book Compositional Data Analysis written by Vera Pawlowsky-Glahn and published by John Wiley & Sons. This book was released on 2011-09-19 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern for more than 100 years. It is even more difficult to realize that so many statisticians and users of statistics are unaware of the particular problems affecting compositional data, as well as their solutions. The issue of ``spurious correlation'', as the situation was phrased by Karl Pearson back in 1897, affects all data that measures parts of some whole, such as percentages, proportions, ppm and ppb. Such measurements are present in all fields of science, ranging from geology, biology, environmental sciences, forensic sciences, medicine and hydrology. This book presents the history and development of compositional data analysis along with Aitchison's log-ratio approach. Compositional Data Analysis describes the state of the art both in theoretical fields as well as applications in the different fields of science. Key Features: Reflects the state-of-the-art in compositional data analysis. Gives an overview of the historical development of compositional data analysis, as well as basic concepts and procedures. Looks at advances in algebra and calculus on the simplex. Presents applications in different fields of science, including, genomics, ecology, biology, geochemistry, planetology, chemistry and economics. Explores connections to correspondence analysis and the Dirichlet distribution. Presents a summary of three available software packages for compositional data analysis. Supported by an accompanying website featuring R code. Applied scientists working on compositional data analysis in any field of science, both in academia and professionals will benefit from this book, along with graduate students in any field of science working with compositional data.

Genomics in the Cloud

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Publisher : O'Reilly Media
ISBN 13 : 1491975164
Total Pages : 496 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Genomics in the Cloud by : Geraldine A. Van der Auwera

Download or read book Genomics in the Cloud written by Geraldine A. Van der Auwera and published by O'Reilly Media. This book was released on 2020-04-02 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytes—or over 50 million gigabytes—of genomic data, and they’re turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that volume of data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Geraldine Van der Auwera, longtime custodian of the GATK user community, and Brian O’Connor of the UC Santa Cruz Genomics Institute, guide you through the process. You’ll learn by working with real data and genomics algorithms from the field. This book covers: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK, plus three major GATK Best Practices pipelines Automating analysis with scripted workflows using WDL and Cromwell Scaling up workflow execution in the cloud, including parallelization and cost optimization Interactive analysis in the cloud using Jupyter notebooks Secure collaboration and computational reproducibility using Terra

Molecular Medicine

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Publisher : BoD – Books on Demand
ISBN 13 : 183962759X
Total Pages : 168 pages
Book Rating : 4.8/5 (396 download)

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Book Synopsis Molecular Medicine by : Sinem Nalbantoglu

Download or read book Molecular Medicine written by Sinem Nalbantoglu and published by BoD – Books on Demand. This book was released on 2019-11-06 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Molecular medicine is an applied science focused on human genes/transcripts, proteins, metabolites, and metabolic networks that describes molecular and cellular processes of health and disease onset and progression. Molecular medicine-based integrative identification and characterization of biomarker targets and their clinical translations is essential to explain/decipher the mechanism(s) underlying physiological pathways and pathological conditions, and acquire cell-targeted early interventional and therapeutic strategies in the context of precision medicine and public health. Principally, Molecular Medicine provides an overview of the latest headlines/developments of systems and molecular medicine, highlighting the emerging high-throughput technologies, promising potential applications, and progress in biomedical research and development strategies.

Next-Generation Sequencing and Sequence Data Analysis

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Publisher : Bentham Science Publishers
ISBN 13 : 1681080923
Total Pages : 160 pages
Book Rating : 4.6/5 (81 download)

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Book Synopsis Next-Generation Sequencing and Sequence Data Analysis by : Kuo Ping Chiu

Download or read book Next-Generation Sequencing and Sequence Data Analysis written by Kuo Ping Chiu and published by Bentham Science Publishers. This book was released on 2015-11-04 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nucleic acid sequencing techniques have enabled researchers to determine the exact order of base pairs - and by extension, the information present - in the genome of living organisms. Consequently, our understanding of this information and its link to genetic expression at molecular and cellular levels has lead to rapid advances in biology, genetics, biotechnology and medicine. Next-Generation Sequencing and Sequence Data Analysis is a brief primer on DNA sequencing techniques and methods used to analyze sequence data. Readers will learn about recent concepts and methods in genomics such as sequence library preparation, cluster generation for PCR technologies, PED sequencing, genome assembly, exome sequencing, transcriptomics and more. This book serves as a textbook for students undertaking courses in bioinformatics and laboratory methods in applied biology. General readers interested in learning about DNA sequencing techniques may also benefit from the simple format of information presented in the book.

Single Cell Methods

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Publisher :
ISBN 13 : 9781493992423
Total Pages : 452 pages
Book Rating : 4.9/5 (924 download)

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Book Synopsis Single Cell Methods by : Valentina Proserpio

Download or read book Single Cell Methods written by Valentina Proserpio and published by . This book was released on 2019 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a comprehensive overview for investigating biology at the level of individual cells. Chapters are organized into eight parts detailing a single-cell lab, single cell DNA-seq, RNA-seq, single cell proteomic and epigenetic, single cell multi-omics, single cell screening, and single cell live imaging. 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 cutting-edge, Single Cell Methods: Sequencing and Proteomics aims to make each experiment easily reproducible in every lab.

Single Cell Metabolism

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Publisher : Humana
ISBN 13 : 9781493998296
Total Pages : 0 pages
Book Rating : 4.9/5 (982 download)

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Book Synopsis Single Cell Metabolism by : Bindesh Shrestha

Download or read book Single Cell Metabolism written by Bindesh Shrestha and published by Humana. This book was released on 2019-09-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume explores the latest techniques and workflow for the analysis of single cells metabolism. The chapters in this book cover topics such as the development of mass spectrometry-based single cell approaches, Pico-ESI-MS for single-cell metabolomics analysis; laser capture microdissection; ambient single cell metabolite profile (DESI and LAESI); and MALDI-MS methodology, quantum dots for quantitative cytology to study metabolic heterogeneity of single cells. Written in the highly successful Methods in Molecular Biology series format, the chapters consist of introductions to the topic, lists of the necessary materials and reagents, step-by-step guidelines, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Comprehensive and authoritative, Single Cell Metabolism: Methods and Protocols is a valuable resource for any researcher and scientist interested in learning more about this field.

Integrating Omics Data

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Publisher : Cambridge University Press
ISBN 13 : 1107069114
Total Pages : 497 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Integrating Omics Data by : George Tseng

Download or read book Integrating Omics Data written by George Tseng and published by Cambridge University Press. This book was released on 2015-09-23 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tutorial chapters by leaders in the field introduce state-of-the-art methods to handle information integration problems of omics data.

Relative Distribution Methods in the Social Sciences

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Publisher : Springer Science & Business Media
ISBN 13 : 0387226583
Total Pages : 272 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Relative Distribution Methods in the Social Sciences by : Mark S. Handcock

Download or read book Relative Distribution Methods in the Social Sciences written by Mark S. Handcock and published by Springer Science & Business Media. This book was released on 2006-05-10 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents methods for full comparative distributional analysis based on the relative distribution. This provides a general integrated framework for analysis, a graphical component that simplifies exploratory data analysis and display, a statistically valid basis for the development of hypothesis-driven summary measures, and the potential for decomposition - enabling the examination of complex hypotheses regarding the origins of distributional changes within and between groups. Written for data analysts and those interested in measurement, the text can also serve as a textbook for a course on distributional methods.