Single Cell 'Omics of Neuronal Cells

by Jonathan V. Sweedler (Editor), James Eberwine (Editor), Scott E. Fraser (Editor)

Overview

This volume discusses the latest techniques used in the diverse fields of single cell ‘omics and covers topics such as quantifying the single cell transcriptome; isolation of cells in nanoliter volumes for single cell proteomics measurements by nano-LC-MS/MS; and single cell protein characterization by immunoblotting. A wide range of methodologies are highlighted, ranging from high-yield chemical amplification to mass spectrometry and nanotechnology for the analysis of the chemical constituents of cells. In the Neuromethods series style, chapters include both in-depth overviews, as well as detailed prools that provide the key advice from specialists you need to get successful results in your laboratory.

Cutting-edge and comprehensive, Single Cell ‘Omics of Neuronal Cells is a valuable resource for experienced and novice researchers interested in learning more about this field and its future developments.

Product Details

ISBN-13:	9781071625279
Publisher:	Springer US
Publication date:	08/12/2023
Series:	Neuromethods , #184
Edition description:	1st ed. 2022
Pages:	294
Product dimensions:	7.01(w) x 10.00(h) x (d)

Table of Contents

Singe Cell aRNA-Seq for Transcriptomics and Cellular Phenotyping.- Single Cell Genomic and Epigenomic DNA Analyses.- Single-Cell Proteome Profiling of Neuronal Cells.- Joint Analysis of Transcriptome and Proteome Measurements in Single Cells with TotalVI.- Single-Cell Mass Spectrometry of Metabolites and Proteins for Systems and Functional Biology.- High-Throughout Image-Guided Microprobe Mass Spectrometric Analysis of Single Cells.- Single-Cell Resolution Immunoblotting.- Quantifying Enzyme Activity and Gene Expression within Single-Cells using a Multiplexed Capillary Electrophoresis Platform.- Quantitative Chemical Imaging at the Cell Level-SIMS, Fluorescence, and Correlative Techniques.- Electrophysiology and Single Cells.- Genetically Encoded Biosensors Reveal Spatiotemporal Dynamics and Cellular Heterogeneity of Neuronal Cells.