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
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.
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
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.
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.
Analysis and Control of Cellular Ensembles. Exploiting dimensionality reduction in single-cell data and models
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.
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.
Inflammation
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.
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.
Kernel Methods for Pattern Analysis
Author: John Shawe-Taylor
Publisher: Cambridge University Press
ISBN: 9780521813976
Category : Computers
Languages : en
Pages : 520
Book Description
Publisher Description
Publisher: Cambridge University Press
ISBN: 9780521813976
Category : Computers
Languages : en
Pages : 520
Book Description
Publisher Description
Machine Learning in Single-Cell RNA-seq Data Analysis
Author: Khalid Raza
Publisher: Springer Nature
ISBN: 9819767032
Category :
Languages : en
Pages : 104
Book Description
Publisher: Springer Nature
ISBN: 9819767032
Category :
Languages : en
Pages : 104
Book Description
Statistical and Computational Method Development and Benchmarking for Analysis of High-dimensional Single-cell Cytometry Data
Genes & Signals
Author: Mark Ptashne
Publisher: CSHL Press
ISBN: 9780879696337
Category : Medical
Languages : en
Pages : 212
Book Description
P. 103.
Publisher: CSHL Press
ISBN: 9780879696337
Category : Medical
Languages : en
Pages : 212
Book Description
P. 103.
Next-Generation Sequencing Data Analysis
Author: Xinkun Wang
Publisher: CRC Press
ISBN: 1000897192
Category : Mathematics
Languages : en
Pages : 435
Book Description
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
Publisher: CRC Press
ISBN: 1000897192
Category : Mathematics
Languages : en
Pages : 435
Book Description
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
Computational Methods for Single-Cell Data Analysis
Author: Guo-Cheng Yuan
Publisher: Humana Press
ISBN: 9781493990566
Category : Science
Languages : en
Pages : 271
Book Description
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.
Publisher: Humana Press
ISBN: 9781493990566
Category : Science
Languages : en
Pages : 271
Book Description
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.