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Methods, Tools and Current Perspectives in Proteogenomics

delete2017-06-01
delete117
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OA
AI
K
Kelly V. Ruggles
K
Karsten Krug
王肖静 封面图
王肖静 (Xiaojing Wang)
K
Karl R. Clauser
王
王静 (Jing Wang)
S
Samuel Payne
D
David Fenyö
张
张冰 (Bing Zhang)
D
D.R. Mani *
DOI:10.1074/mcp.MR117.000024delete
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摘要

摘要

En 中文
With combined technological advancements in high-throughput next-generation sequencing and deep mass spectrometry-based proteomics, proteogenomics, i.e. the integrative analysis of proteomic and genomic data, has emerged as a new research field. Early efforts in the field were focused on improving protein identification using sample-specific genomic and transcriptomic sequencing data. More recently, integrative analysis of quantitative measurements from genomic and proteomic studies have identified novel insights into gene expression regulation, cell signaling, and disease. Many methods and tools have been developed or adapted to enable an array of integrative proteogenomic approaches and in this article, we systematically classify published methods and tools into four major categories, (1) Sequence-centric proteogenomics; (2) Analysis of proteogenomic relationships; (3) Integrative modeling of proteogenomic data; and (4) Data sharing and visualization. We provide a comprehensive review of methods and available tools in each category and highlight their typical applications.
Keyword:
MASS-SPECTROMETRY DATA
OMICS DATA
RNA-SEQ
POSTTRANSLATIONAL MODIFICATIONS
PROTEIN IDENTIFICATION
GENOME ANNOTATION
ANALYSIS REVEALS
GENE-EXPRESSION
INTEGRATIVE PROTEOGENOMICS
STRUCTURAL ANNOTATION
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期刊

M
Molecular and Cellular Proteomics
IF:
5.5
论文数:
4.8K
被引数:
1.7W

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Harvard University
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26.5W
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N
New York University
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B
Baylor College of Medicine
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4.1W
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被引数: 4.2W
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