High-Dimensional Single Cell Analysis PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download High-Dimensional Single Cell Analysis PDF full book. Access full book title High-Dimensional Single Cell Analysis by Harris G. Fienberg. Download full books in PDF and EPUB format.

High-Dimensional Single Cell Analysis

High-Dimensional Single Cell Analysis PDF Author: Harris G. Fienberg
Publisher: Springer
ISBN: 364254827X
Category : Medical
Languages : en
Pages : 224

Book Description
This volume highlights the most interesting biomedical and clinical applications of high-dimensional flow and mass cytometry. It reviews current practical approaches used to perform high-dimensional experiments and addresses key bioinformatic techniques for the analysis of data sets involving dozens of parameters in millions of single cells. Topics include single cell cancer biology; studies of the human immunome; exploration of immunological cell types such as CD8+ T cells; decipherment of signaling processes of cancer; mass-tag cellular barcoding; analysis of protein interactions by proximity ligation assays; Cytobank, a platform for the analysis of cytometry data; computational analysis of high-dimensional flow cytometric data; computational deconvolution approaches for the description of intracellular signaling dynamics and hyperspectral cytometry. All 10 chapters of this book have been written by respected experts in their fields. It is an invaluable reference book for both basic and clinical researchers.

High-Dimensional Single Cell Analysis

High-Dimensional Single Cell Analysis PDF Author: Harris G. Fienberg
Publisher: Springer
ISBN: 364254827X
Category : Medical
Languages : en
Pages : 224

Book Description
This volume highlights the most interesting biomedical and clinical applications of high-dimensional flow and mass cytometry. It reviews current practical approaches used to perform high-dimensional experiments and addresses key bioinformatic techniques for the analysis of data sets involving dozens of parameters in millions of single cells. Topics include single cell cancer biology; studies of the human immunome; exploration of immunological cell types such as CD8+ T cells; decipherment of signaling processes of cancer; mass-tag cellular barcoding; analysis of protein interactions by proximity ligation assays; Cytobank, a platform for the analysis of cytometry data; computational analysis of high-dimensional flow cytometric data; computational deconvolution approaches for the description of intracellular signaling dynamics and hyperspectral cytometry. All 10 chapters of this book have been written by respected experts in their fields. It is an invaluable reference book for both basic and clinical researchers.

Learning Cell States from High-dimensional Single-cell Data

Learning Cell States from High-dimensional Single-cell Data PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
Recent developments in single-cell measurement technologies have yielded dramatic increases in throughput (measured cells per experiment) and dimensionality (measured features per cell). In particular, the introduction of mass cytometry has made possible the simultaneous quantification of dozens of protein species in millions of individual cells in a single experiment. The raw data produced by such high-dimensional single-cell measurements provide unprecedented potential to reveal the phenotypic heterogeneity of cellular systems. In order to realize this potential, novel computational techniques are required to extract knowledge from these complex data. Analysis of single-cell data is a new challenge for computational biology, as early development in the field was tailored to technologies that sacrifice single-cell resolution, such as DNA microarrays. The challenges for single-cell data are quite distinct and require multidimensional modeling of complex population structure. Particular challenges include nonlinear relationships between measured features and non-convex subpopulations.

Immunophenotyping

Immunophenotyping PDF Author: J Philip McCoy Jr
Publisher: Humana
ISBN: 9781493996490
Category : Medical
Languages : en
Pages : 375

Book Description
This volume presents the latest collection of immunophenotypic techniques and applications used in research and clinical settings. Chapters in this book cover topics such as constructions of high dimensions fluorescence and mass cytometry panels; fluorescence barcoding; using dried or lyophilized reagents; and immunophenotypic examples of specific cell types. The book concludes with a discussion on the critical roles of quality control and immunophenotyping in the clinical environment. 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. Cutting-edge and comprehensive, Immunophenotyping: Methods and Protocols is a valuable resource for any researchers, clinician, or scientist interested in learning more about this evolving field.

Analysis and Control of Cellular Ensembles. Exploiting dimensionality reduction in single-cell data and models

Analysis and Control of Cellular Ensembles. Exploiting dimensionality reduction in single-cell data and models PDF Author: Karsten Kuritz
Publisher: Logos Verlag Berlin GmbH
ISBN: 383255209X
Category : Language Arts & Disciplines
Languages : en
Pages : 150

Book Description
An ensemble system is a collection of nearly identical dynamical systems which admit a certain degree of heterogeneity, and which are subject to the restriction that they may only be manipulated or observed as a whole. This thesis presents analysis and control methods for cellular ensembles by considering reduced 1-dimensional dynamics of biological processes in high-dimensional single-cell data and models. To be more specific, we address the quest for real-time analysis of biological processes within single-cell data by introducing the measure-preserving map of pseudotime into real-time, in short MAPiT. MAPiT enables the reconstruction of temporal and spatial dynamics from single-cell snapshot experiments. In addition, we propose a PDE-constrained learning algorithm which allows for efficient inference of changes in cell cycle progression from time series single-cell snapshot data. The second part of this thesis, is devoted to controlling a heterogeneous cell population, in the sense, that we aim at achieving a desired distribution of cellular oscillators on their periodic orbit. A systems theoretic approach to the ensemble control problem provides novel necessary and sufficient conditions for the control of phase distributions in terms of the Fourier coefficients of the phase response curve. This thesis establishes a connection between the previously separate areas of single cell analysis and ensemble control. Our holistic view opens new perspectives for theoretic concepts in basic research and therapeutic strategies in precision medicine.

Single Cell Sequencing and Systems Immunology

Single Cell Sequencing and Systems Immunology PDF Author: Xiangdong Wang
Publisher: Springer
ISBN: 9401797536
Category : Medical
Languages : en
Pages : 184

Book Description
The volume focuses on the genomics, proteomics, metabolomics, and bioinformatics of a single cell, especially lymphocytes and on understanding the molecular mechanisms of systems immunology. Based on the author’s personal experience, it provides revealing insights into the potential applications, significance, workflow, comparison, future perspectives and challenges of single-cell sequencing for identifying and developing disease-specific biomarkers in order to understand the biological function, activation and dysfunction of single cells and lymphocytes and to explore their functional roles and responses to therapies. It also provides detailed information on individual subgroups of lymphocytes, including cell characters, function, surface markers, receptor function, intracellular signals and pathways, production of inflammatory mediators, nuclear receptors and factors, omics, sequencing, disease-specific biomarkers, bioinformatics, networks and dynamic networks, their role in disease and future prospects. Dr. Xiangdong Wang is a Professor of Medicine, Director of Shanghai Institute of Clinical Bioinformatics, Director of Fudan University Center for Clinical Bioinformatics, Director of the Biomedical Research Center of Zhongshan Hospital, Deputy Director of Shanghai Respiratory Research Institute, Shanghai, China.

Kernel Methods for Pattern Analysis

Kernel Methods for Pattern Analysis PDF Author: John Shawe-Taylor
Publisher: Cambridge University Press
ISBN: 9780521813976
Category : Computers
Languages : en
Pages : 520

Book Description
Publisher Description

Inflammation

Inflammation PDF Author: Björn E. Clausen
Publisher: Humana
ISBN: 9781493967841
Category : Medical
Languages : en
Pages : 0

Book Description
This volume presents a broad selection of cutting-edge methods and tools that will enable the reader to investigate the multi-faceted manifestations of inflammation. Inflammation: Methods and Protocols is divided into four sections: the first three sections describe protocols investigating immune-mediated inflammatory disease models affecting barrier organs to the environment; the skin, the lung, and the intestinal and oral mucosa. The fourth section illustrates inflammatory disease models of the brain, joints, and vasculature. 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 notes on troubleshooting and avoiding known pitfalls. Authoritative and practical, Inflammation: Methods and Protocols aims to inspire the experienced investigator and the young experimenter alike to disentangle the fascinating process of inflammation.

Statistical and Computational Method Development and Benchmarking for Analysis of High-dimensional Single-cell Cytometry Data

Statistical and Computational Method Development and Benchmarking for Analysis of High-dimensional Single-cell Cytometry Data PDF Author: Lukas Martin Weber
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description


Introduction to High-Dimensional Statistics

Introduction to High-Dimensional Statistics PDF Author: Christophe Giraud
Publisher: CRC Press
ISBN: 1000408353
Category : Computers
Languages : en
Pages : 410

Book Description
Praise for the first edition: "[This book] succeeds singularly at providing a structured introduction to this active field of research. ... it is arguably the most accessible overview yet published of the mathematical ideas and principles that one needs to master to enter the field of high-dimensional statistics. ... recommended to anyone interested in the main results of current research in high-dimensional statistics as well as anyone interested in acquiring the core mathematical skills to enter this area of research." —Journal of the American Statistical Association Introduction to High-Dimensional Statistics, Second Edition preserves the philosophy of the first edition: to be a concise guide for students and researchers discovering the area and interested in the mathematics involved. The main concepts and ideas are presented in simple settings, avoiding thereby unessential technicalities. High-dimensional statistics is a fast-evolving field, and much progress has been made on a large variety of topics, providing new insights and methods. Offering a succinct presentation of the mathematical foundations of high-dimensional statistics, this new edition: Offers revised chapters from the previous edition, with the inclusion of many additional materials on some important topics, including compress sensing, estimation with convex constraints, the slope estimator, simultaneously low-rank and row-sparse linear regression, or aggregation of a continuous set of estimators. Introduces three new chapters on iterative algorithms, clustering, and minimax lower bounds. Provides enhanced appendices, minimax lower-bounds mainly with the addition of the Davis-Kahan perturbation bound and of two simple versions of the Hanson-Wright concentration inequality. Covers cutting-edge statistical methods including model selection, sparsity and the Lasso, iterative hard thresholding, aggregation, support vector machines, and learning theory. Provides detailed exercises at the end of every chapter with collaborative solutions on a wiki site. Illustrates concepts with simple but clear practical examples.

Genes & Signals

Genes & Signals PDF Author: Mark Ptashne
Publisher: CSHL Press
ISBN: 9780879696337
Category : Medical
Languages : en
Pages : 212

Book Description
P. 103.