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Cancer Driver Genes

Overview of attention for book
Cover of 'Cancer Driver Genes'

Table of Contents

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    Book Overview
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    Chapter 1 Cancer Gene Discovery: Past to Present
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    Chapter 2 Identification of Cancer Driver Genes from a Custom Set of Next Generation Sequencing Data
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    Chapter 3 Cancer Gene Discovery by Network Analysis of Somatic Mutations Using the MUFFINN Server
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    Chapter 4 Identifying Driver Interfaces Enriched for Somatic Missense Mutations in Tumors
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    Chapter 5 Identification of Cancer Genes Based on De Novo Transposon Insertion Site Analysis Using RNA and DNA Sequencing
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    Chapter 6 A Cell-Based Method for Identification of Chemotherapy Resistance Cancer Genes
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    Chapter 7 Engineering a Bioartificial Human Colon Model Through Decellularization and Recellularization
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    Chapter 8 Mutagenesis Screens for Prostate Cancer Using Replication-Incompetent Lentiviral Vectors
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    Chapter 9 Arrayed shRNA Screening to Identify Suppressors of Anchorage-Independent Growth
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    Chapter 10 Genome-Wide CRISPR/Cas9 Screening for Identification of Cancer Genes in Cell Lines
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    Chapter 11 CRISPR/Cas9-Based Positive Screens for Cancer-Related Traits
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    Chapter 12 Ex Vivo Transposon-Mediated Genetic Screens for Cancer Gene Discovery
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    Chapter 13 Cancer Gene Discovery Utilizing Sleeping Beauty Transposon Mutagenesis
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    Chapter 14 PiggyBac Transposon-Based Insertional Mutagenesis in Mice
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    Chapter 15 Liver-Specific Delivery of Sleeping Beauty Transposon System by Hydrodynamic Injection for Cancer Gene Validation
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    Chapter 16 Engineering Large Genomic Rearrangement in Mouse Embryonic Stem Cell for Cancer Gene Discovery
Overall attention for this book and its chapters
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Title
Cancer Driver Genes
Published by
Springer New York, February 2019
DOI 10.1007/978-1-4939-8967-6
ISBNs
978-1-4939-8966-9, 978-1-4939-8967-6
Editors

Starr, Timothy K.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 33%
Student > Ph. D. Student 3 25%
Student > Master 2 17%
Student > Bachelor 2 17%
Unspecified 1 8%
Other 0 0%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 25%
Unspecified 2 17%
Biochemistry, Genetics and Molecular Biology 2 17%
Immunology and Microbiology 2 17%
Social Sciences 1 8%
Other 2 17%