Bioinformatics for cancer immunotherapy : methods and protocols

著者

• Boegel, Sebastian

書誌事項

Bioinformatics for cancer immunotherapy : methods and protocols

edited by Sebastian Boegel

（Methods in molecular biology / John M. Walker, series editor, 2120）（Springer protocols）

Humana Press, c2020

注記

Includes bibliographical references and index

内容説明・目次

内容説明

This volume focuses on a variety of in silico protocols of the latest bioinformatics tools and computational pipelines developed for neo-antigen identification and immune cell analysis from high-throughput sequencing data for cancer immunotherapy. The chapters in this book cover topics that discuss the two emerging concepts in recognition of tumor cells using endogenous T cells: cancer vaccines against neo-antigens presented on HLA class I and II alleles, and checkpoint inhibitors. 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. Cutting-edge and authoritative, Bioinformatics for Cancer Immunotherapy: Methods and Protocols is a valuable research tool for any scientist and researcher interested in learning more about this exciting and developing field.

目次

Preface... Table of Contents... Contributing Authors... 1 Bioinformatics for Cancer Immunotherapy Christoph Holtstrater, Barbara Schroers, Thomas Bukur, and Martin Loewer 2 An Individualized Approach for Somatic Variant Discovery Minghao Li, Ting He, Chen Cao, and Quan Long 3 Ensemble-Based Somatic Mutation Calling in Cancer Genomes Weitai Huang, Yu Amanda Guo, Mei Mei Chang, and Anders Jacobsen Skanderup 4 SomaticSeq: An Ensemble and Machine Learning Method to Detect Somatic Mutations Li Tai Fang 5 HLA Typing from RNA Sequencing and Applications to Cancer Rose Orenbuch, Ioan Filip, and Raul Rabadan 6 Rapid High-Resolution Typing of Class I HLA Genes by Nanopore Sequencing Chang Liu and Rick Berry 7 HLApers: HLA Typing and Quantification of Expression with Personalized Index Vitor R. C. Aguiar, Cibele Masotti, Anamaria A. Camargo, and Diogo Meyer 8 High-Throughput MHC I Ligand Prediction using MHCflurry Timothy O'Donnell and Alex Rubinsteyn 9 In Silico Prediction of Tumor Neoantigens with TIminer Alexander Kirchmair and Francesca Finotello 10 OpenVax: An Open-Source Computational Pipeline for Cancer Neoantigen Prediction Julia Kodysh and Alex Rubinsteyn 11 Improving MHC-I Ligand Identification by Incorporating Targeted Searches of Mass Spectrometry Data Prathyusha Konda, J. Patrick Murphy, and Shashi Gujar 12 The SysteMHC Atlas: A Computational Pipeline, A Website, and A Data Repository for Immunopeptidomics Analysis Wenguang Shao, Etienne Caron, Patrick Pedrioli, and Ruedi Aebersold 13 Identification of Epitope-Specific T Cells in T Cell Receptor Repertoires Sofie Gielis, Pieter Moris, Wout Bittremieux, Nicolas De Neuter, Benson Ogunjimi, Kris Laukens, and Pieter Meysman 14 Modeling and Viewing T Cell Receptors using TCRmodel and TCR3d Ragul Gowthaman and Brian G. Pierce 15 In Silico Cell Type Deconvolution Methods in Cancer Immunotherapy Gregor Sturm, Francesca Finotello, and Markus List 16 Immunedeconv - An R Package for Unified Access to Computational Methods for Estimating Immune Cell Fractions from Bulk RNA Sequencing Data Gregor Sturm, Francesca Finotello, and Markus List 17 EPIC: A Tool to Estimate the Proportions of Different Cell Types from Bulk Gene Expression Data Julien Racle and David Gfeller 18 Computational Deconvolution of Tumor-Infiltrating Immune Components with Bulk Tumor Gene Expression Data Bo Li, Taiwen Li, Jun S. Liu, and X. Shirley Liu 19 Cell Type Enrichment Analysis of Bulk Transcriptomes using xCell Dvir Aran 20 Cap Analysis of Gene Expression (CAGE), A Quantitative and Genome-Wide Assay of Transcription Start Sites Masaki Suimye Morioka, Hideya Kawaji, Hiromi Nishiyori-Sueki, Mitsuyoshi Murata, Miki Kojima-Ishiyama, Piero Carninci, and Masayoshi Itoh

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詳細情報

• NII書誌ID(NCID): BC08274518
• ISBN:
  • 9781071603260
• 出版国コード: us
• タイトル言語コード: eng
• 本文言語コード: eng
• 出版地: New York
• ページ数/冊数: xii, 304 p.
• 大きさ: 26 cm
• 親書誌ID:
  • BA10794673
  • BA88873632