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Computational Systems Biology

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Cover of 'Computational Systems Biology'

Table of Contents

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    Book Overview
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    Chapter 1 DNA Sequencing Data Analysis
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    Chapter 2 Transcriptome Sequencing: RNA-Seq
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    Chapter 3 Capture Hybridization of Long-Range DNA Fragments for High-Throughput Sequencing
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    Chapter 4 The Introduction and Clinical Application of Cell-Free Tumor DNA
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    Chapter 5 Bioinformatics Analysis for Cell-Free Tumor DNA Sequencing Data
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    Chapter 6 An Overview of Genome-Wide Association Studies
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    Chapter 7 Integrative Analysis of Omics Big Data
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    Chapter 8 The Reconstruction and Analysis of Gene Regulatory Networks
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    Chapter 9 Differential Coexpression Network Analysis for Gene Expression Data
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    Chapter 10 iSeq: Web-Based RNA-seq Data Analysis and Visualization
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    Chapter 11 Revisit of Machine Learning Supported Biological and Biomedical Studies
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    Chapter 12 Identifying Interactions Between Long Noncoding RNAs and Diseases Based on Computational Methods
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    Chapter 13 Survey of Computational Approaches for Prediction of DNA-Binding Residues on Protein Surfaces
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    Chapter 14 Computational Prediction of Protein O-GlcNAc Modification
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    Chapter 15 Machine Learning-Based Modeling of Drug Toxicity
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    Chapter 16 Metabolomics: A High-Throughput Platform for Metabolite Profile Exploration
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    Chapter 17 Single-Cell Protein Assays: A Review
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    Chapter 18 Data Analysis in Single-Cell Transcriptome Sequencing
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    Chapter 19 Applications of Single-Cell Sequencing for Multiomics
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    Chapter 20 Progress on Diagnosis of Tuberculous Meningitis
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    Chapter 21 Insights of Acute Lymphoblastic Leukemia with Development of Genomic Investigation
Attention for Chapter 3: Capture Hybridization of Long-Range DNA Fragments for High-Throughput Sequencing
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Chapter title
Capture Hybridization of Long-Range DNA Fragments for High-Throughput Sequencing
Chapter number 3
Book title
Computational Systems Biology
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7717-8_3
Pubmed ID
Book ISBNs
978-1-4939-7716-1, 978-1-4939-7717-8
Authors

Xing Chen, Gang Ni, Kai He, Zhao-Li Ding, Gui-Mei Li, Adeniyi C. Adeola, Robert W. Murphy, Wen-Zhi Wang, Ya-Ping Zhang

Abstract

Capture hybridization coupled with high-throughput sequencing (HTS) has become one of the most popular approaches to address some scientific problems not only for fundamental evolution but also for ecology and human disease in recent years. However, the technical problem of limited probe capture ability affects its widespread application. Here, we propose to capture hybridize long-range DNA fragments for HTS (termed LR-LCH). We provide a case of three amphibian samples to examine LR-LCH with 2 kb libraries and comparison of standard capture hybridization with 480 bp libraries. Capture sensitivity increased from an average 13.57% of standard capture hybridization to an average 19.80% of LR-LCH; capture efficiency also increased from an average 72.56% of standard capture hybridization to an average 97.71% of LR-LCH. These indicate that longer fragments in the library generally contain both relatively variable regions and relatively conservative regions. The divergent parts of target DNA are enriched along with conservative parts of DNA sequence that effectively captured during hybridization. We present a protocol that allows users to overcome the low capture sensitivity problem for high divergent regions.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 24%
Student > Master 2 12%
Student > Doctoral Student 2 12%
Unspecified 1 6%
Other 1 6%
Other 1 6%
Unknown 6 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 29%
Agricultural and Biological Sciences 3 18%
Computer Science 1 6%
Unspecified 1 6%
Unknown 7 41%