Mapping Biological Networks from Quantitative Data-Independent Acquisition Mass Spectrometry: Data to Knowledge Pipelines.
Methods Mol Biol
; 1558: 395-413, 2017.
Article
en En
| MEDLINE
| ID: mdl-28150249
Data-independent acquisition mass spectrometry (DIA-MS) strategies and applications provide unique advantages for qualitative and quantitative proteome probing of a biological sample allowing constant sensitivity and reproducibility across large sample sets. These advantages in LC-MS/MS are being realized in fundamental research laboratories and for clinical research applications. However, the ability to translate high-throughput raw LC-MS/MS proteomic data into biological knowledge is a complex and difficult task requiring the use of many algorithms and tools for which there is no widely accepted standard and best practices are slowly being implemented. Today a single tool or approach inherently fails to capture the full interpretation that proteomics uniquely supplies, including the dynamics of quickly reversible chemically modified states of proteins, irreversible amino acid modifications, signaling truncation events, and, finally, determining the presence of protein from allele-specific transcripts. This chapter highlights key steps and publicly available algorithms required to translate DIA-MS data into knowledge.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Espectrometría de Masas
/
Programas Informáticos
/
Biología Computacional
/
Minería de Datos
Tipo de estudio:
Guideline
/
Qualitative_research
Idioma:
En
Revista:
Methods Mol Biol
Asunto de la revista:
BIOLOGIA MOLECULAR
Año:
2017
Tipo del documento:
Article
País de afiliación:
Estados Unidos