Computational Methods for Single-Cell Data Analysis
Computational Methods for Single-Cell Data Analysis

Author: Guo-Cheng Yuan

Publisher: Humana Press

Published: 2019-02-14

Total Pages: 271

ISBN-13: 9781493990566

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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.

High-Dimensional Single Cell Analysis
High-Dimensional Single Cell Analysis

Author: Harris G. Fienberg

Publisher: Springer

Published: 2014-04-22

Total Pages: 224

ISBN-13: 364254827X

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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.

Clustering Stability
Clustering Stability

Author: Ulrike Von Luxburg

Publisher: Now Publishers Inc

Published: 2010

Total Pages: 53

ISBN-13: 1601983441

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A popular method for selecting the number of clusters is based on stability arguments: one chooses the number of clusters such that the corresponding clustering results are most stable. In recent years, a series of papers has analyzed the behavior of this method from a theoretical point of view. However, the results are very technical and difficult to interpret for non-experts. In this paper we give a high-level overview about the existing literature on clustering stability. In addition to presenting the results in a slightly informal but accessible way, we relate them to each other and discuss their different implications.

Single Cell Analysis
Single Cell Analysis

Author: J. Paul Robinson

Publisher: Springer

Published: 2017-04-18

Total Pages: 277

ISBN-13: 9811044996

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This book highlights the current state of the art in single cell analysis, an area that involves many fields of science – from clinical hematology, functional analysis and drug screening, to platelet and microparticle analysis, marine biology and fundamental cancer research. This book brings together an eclectic group of current applications, all of which have a significant impact on our current state of knowledge. The authors of these chapters are all pioneering researchers in the field of single cell analysis. The book will not only appeal to those readers more focused on clinical applications, but also those interested in highly technical aspects of the technologies. All of the technologies identified utilize unique applications of photon detection systems.

Microfluidics for Single-Cell Analysis
Microfluidics for Single-Cell Analysis

Author: Jin-Ming Lin

Publisher: Springer Nature

Published: 2019-08-28

Total Pages: 263

ISBN-13: 9813297298

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This book summarizes the various microfluidic-based approaches for single-cell capture, isolation, manipulation, culture and observation, lysis, and analysis. Single-cell analysis reveals the heterogeneities in morphology, functions, composition, and genetic performance of seemingly identical cells, and advances in single-cell analysis can overcome the difficulties arising due to cell heterogeneity in the diagnostics for a targeted model of disease. This book provides a detailed review of the state-of-the-art techniques presenting the pros and cons of each of these methods. It also offers lessons learned and tips from front-line investigators to help researchers overcome bottlenecks in their own studies. Highlighting a number of techniques, such as microfluidic droplet techniques, combined microfluidics-mass-spectrometry systems, and nanochannel sampling, it describes in detail a new microfluidic chip-based live single-cell extractor (LSCE) developed in the editor’s laboratory, which opens up new avenues to use open microfluidics in single-cell extraction, single-cell mass spectrometric analysis, single-cell adhesion analysis and subcellular operations. Serving as both an elementary introduction and advanced guidebook, this book interests and inspires scholars and students who are currently studying or wish to study microfluidics-based cell analysis methods.

Single Cell Methods
Single Cell Methods

Author: Valentina Proserpio

Publisher:

Published: 2019

Total Pages: 452

ISBN-13: 9781493992423

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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.

Tumor Immunology and Immunotherapy - Cellular Methods Part B
Tumor Immunology and Immunotherapy - Cellular Methods Part B

Author:

Publisher: Academic Press

Published: 2020-01-28

Total Pages: 586

ISBN-13: 0128186755

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Tumor Immunology and Immunotherapy - Cellular Methods Part B, Volume 632, the latest release in the Methods in Enzymology series, continues the legacy of this premier serial with quality chapters authored by leaders in the field. Topics covered include Quantitation of calreticulin exposure associated with immunogenic cell death, Side-by-side comparisons of flow cytometry and immunohistochemistry for detection of calreticulin exposure in the course of immunogenic cell death, Quantitative determination of phagocytosis by bone marrow-derived dendritic cells via imaging flow cytometry, Cytofluorometric assessment of dendritic cell-mediated uptake of cancer cell apoptotic bodies, Methods to assess DC-dependent priming of T cell responses by dying cells, and more.

RNA-seq Data Analysis
RNA-seq Data Analysis

Author: Eija Korpelainen

Publisher: CRC Press

Published: 2014-09-19

Total Pages: 314

ISBN-13: 1466595019

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The State of the Art in Transcriptome AnalysisRNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine differential expression at gene, exon, and transcript le

Finding Groups in Data
Finding Groups in Data

Author: Leonard Kaufman

Publisher: Wiley-Interscience

Published: 1990-03-22

Total Pages: 376

ISBN-13:

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Partitioning around medoids (Program PAM). Clustering large applications (Program CLARA). Fuzzy analysis (Program FANNY). Agglomerative Nesting (Program AGNES). Divisive analysis (Program DIANA). Monothetic analysis (Program MONA). Appendix.