Essentials of Single-Cell Analysis

Essentials of Single-Cell Analysis PDF Author: Fan-Gang Tseng
Publisher: Springer
ISBN: 3662491184
Category : Technology & Engineering
Languages : en
Pages : 415

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Book Description
This book provides an overview of single-cell isolation, separation, injection, lysis and dynamics analysis as well as a study of their heterogeneity using different miniaturized devices. As an important part of single-cell analysis, different techniques including electroporation, microinjection, optical trapping, optoporation, rapid electrokinetic patterning and optoelectronic tweezers are described in detail. It presents different fluidic systems (e.g. continuous micro/nano-fluidic devices, microfluidic cytometry) and their integration with sensor technology, optical and hydrodynamic stretchers etc., and demonstrates the applications of single-cell analysis in systems biology, proteomics, genomics, epigenomics, cancer transcriptomics, metabolomics, biomedicine and drug delivery systems. It also discusses the future challenges for single-cell analysis, including the advantages and limitations. This book is enjoyable reading material while at the same time providing essential information to scientists in academia and professionals in industry working on different aspects of single-cell analysis. Dr. Fan-Gang Tseng is a Distinguished Professor of Engineering and System Science at the National Tsing Hua University, Taiwan. Dr. Tuhin Subhra Santra is a Research Associate at the California Nano Systems Institute, University of California at Los Angeles, USA.

Essentials of Single-Cell Analysis

Essentials of Single-Cell Analysis PDF Author: Fan-Gang Tseng
Publisher: Springer
ISBN: 3662491184
Category : Technology & Engineering
Languages : en
Pages : 415

Get Book Here

Book Description
This book provides an overview of single-cell isolation, separation, injection, lysis and dynamics analysis as well as a study of their heterogeneity using different miniaturized devices. As an important part of single-cell analysis, different techniques including electroporation, microinjection, optical trapping, optoporation, rapid electrokinetic patterning and optoelectronic tweezers are described in detail. It presents different fluidic systems (e.g. continuous micro/nano-fluidic devices, microfluidic cytometry) and their integration with sensor technology, optical and hydrodynamic stretchers etc., and demonstrates the applications of single-cell analysis in systems biology, proteomics, genomics, epigenomics, cancer transcriptomics, metabolomics, biomedicine and drug delivery systems. It also discusses the future challenges for single-cell analysis, including the advantages and limitations. This book is enjoyable reading material while at the same time providing essential information to scientists in academia and professionals in industry working on different aspects of single-cell analysis. Dr. Fan-Gang Tseng is a Distinguished Professor of Engineering and System Science at the National Tsing Hua University, Taiwan. Dr. Tuhin Subhra Santra is a Research Associate at the California Nano Systems Institute, University of California at Los Angeles, USA.

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

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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.

Computational Methods for Single-Cell Data Analysis

Computational Methods for Single-Cell Data Analysis PDF Author: Guo-Cheng Yuan
Publisher: Humana Press
ISBN: 9781493990566
Category : Science
Languages : en
Pages : 271

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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.

Single Cell Analysis

Single Cell Analysis PDF Author: J. Paul Robinson
Publisher: Springer
ISBN: 9811044996
Category : Technology & Engineering
Languages : en
Pages : 277

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Book Description
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 PDF Author: Jin-Ming Lin
Publisher: Springer Nature
ISBN: 9813297298
Category : Science
Languages : en
Pages : 263

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Book Description
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 Sequencing and Systems Immunology

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

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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.

Single Cell Methods

Single Cell Methods PDF Author: Valentina Proserpio
Publisher:
ISBN: 9781493992423
Category : Cytology
Languages : en
Pages : 452

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Book Description
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.

Enzyme Activity in Single Cells

Enzyme Activity in Single Cells PDF Author:
Publisher: Academic Press
ISBN: 0128170905
Category : Science
Languages : en
Pages : 326

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Book Description
Enzyme Activity in Single Cells, Volume 628, the latest release in the Methods of Enzymology series, discusses groundbreaking cellular physiology research that is taking place in the biological sciences. Chapters in this new release cover Spatial and temporal resolution of caspase waves in single Xenopus eggs during apoptosis, Spatial and temporal organization of metabolic complexes in cells, Measuring cellular efflux and biomolecular delivery: synthetic approaches to imaging and engineering cells, Slide-based, single-cell enzyme assays, Single-cell assays using integrated continuous-flow microfluidics, High-throughput screening of single-cell lysates, Microfluidic capture of single cells for drug resistance assays, and much more.

Genomics, Circuits, and Pathways in Clinical Neuropsychiatry

Genomics, Circuits, and Pathways in Clinical Neuropsychiatry PDF Author: Thomas Lehner
Publisher: Academic Press
ISBN: 0128005300
Category : Science
Languages : en
Pages : 798

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Book Description
This foundational work comprehensively examines the current state of the genetics, genomics and brain circuitry of psychiatric and neurological disorders. It consolidates discoveries of specific genes and genomic regions associated with these conditions, the genetic and anatomic architecture of these syndromes, and addresses how recent advances in genomics are leading to a reappraisal of the biology underlying clinical neuroscience. In doing so, it critically examines the promise and limitations of these discoveries toward treatment, and to the interdisciplinary nature of understanding brain and behavior. Coverage includes new discoveries regarding autism, epilepsy, intellectual disability, dementias, movement disorders, language impairment, disorders of attention, schizophrenia, and bipolar disorder. Genomics, Circuits, and Pathways in Clinical Neuropsychiatry focuses on key concepts, challenges, findings, and methods in genetics, genomics, molecular pathways, brain circuitry, and related neurobiology of neurologic and psychiatric disorders. - Provides interdisciplinary appeal in psychiatry, neurology, neuroscience, and genetics - Identifies key concepts, methods, and findings - Includes coverage of multiple disorders from autism to schizophrenia - Reviews specific genes associated with disorders - Discusses the genetic architecture of these syndromes - Explains how recent findings are influencing the understanding of biology - Clarifies the promise of these findings for future treatment

Graph Representation Learning

Graph Representation Learning PDF Author: William L. William L. Hamilton
Publisher: Springer Nature
ISBN: 3031015886
Category : Computers
Languages : en
Pages : 141

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Book Description
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.