This volume introduces the reader to the latest experimental and bioinformatics methods for DNA sequencing, RNA sequencing, cell-free tumour DNA sequencing, single cell sequencing, single-cell proteomics and metabolomics.

DNA Sequencing Data Analysis.- Transcriptome Sequencing: RNA-seq.- Capture Hybridization of Long-range DNA Fragments for High-throughput Sequencing.- The Introduction and Clinical Application of Cell-free Tumour DNA.- Bioinformatics Analysis for Cell-free Tumor DNA Sequencing Data.- An Overview of Genome-Wide Association Studies.- Integrative Analysis of Omics Big Data.- The Reconstruction and Analysis of Gene Regulatory Networks.- Differential Coexpression Network Analysis for Gene Expression Data.- iSeq: Web-based RNA-seq Data Analysis and Visualization.- Revisit of Machine Learning Supported Biological and Biomedical Studies.- Identifying Interactions Between Long Non-coding RNAs and Diseases Based on Computational Methods.- Survey Of Computational Approaches For Prediction of DNA-binding Residues on Protein Surfaces.- Computational Prediction of Protein O-GlcNAc Modification.- Machine Learning Based Modeling of Drug Toxicity.- Metabolomics: A High-throughput Platform for Metabolite Profile Exploration.- Single-Cell Protein Assays--A Review.- Data Analysis in Single-cell Transcriptome Sequencing.- Applications of Single-cell Sequencing For Multi-omics.- Progress on Diagnosis of Tuberculous Meningitis.- Insights of Acute Lymphoblastic Leukemia with Development of Genomic Investigation.

This volume introduces the reader to the latest experimental and bioinformatics methods for DNA sequencing, RNA sequencing, cell-free tumour DNA sequencing, single cell sequencing, single-cell proteomics and metabolomics. Chapters detail advanced analysis methods, such as Genome-Wide Association Studies (GWAS), machine learning, reconstruction and analysis of gene regulatory networks and differential coexpression network analysis, and gave a practical guide for how to choose and use the right algorithm or software to handle specific high throughput data or multi-omics 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 Systems Biology: Methods and Protocols aims to ensuresuccessful results in the further study of this vital field.