Leveraging Experimental Details for an Improved Understanding of Host-Pathogen Interactome

Mais Ammari, Fiona M McCarthy, Bindu Nanduri

Research output: Contribution to journalArticle

Abstract

An increasing proportion of curated host-pathogen interaction (HPI) information is becoming available in interaction databases. These data represent detailed, experimentally-verified, molecular interaction data, which may be used to better understand infectious diseases. By their very nature, HPIs are context dependent, where the outcome of two proteins as interacting or not depends on the precise biological conditions studied and approaches used for identifying these interactions. The associated biology and the technical details of the experiments identifying interacting protein molecules are increasing being curated using defined curation standards but are overlooked in current HPI network modeling. Given the increase in data size and complexity, awareness of the process and variables included in HPI identification and curation, and their effect on data analysis and interpretation is crucial in understanding pathogenesis. We describe the use of HPI data for network modeling, aspects of curation that can help researchers to more accurately model specific infection conditions, and provide examples to illustrate these principles.

Original languageEnglish (US)
Pages (from-to)8.26.1-8.26.12
JournalCurrent Protocols in Bioinformatics
Volume61
Issue number1
DOIs
StatePublished - Mar 1 2018

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Host-Pathogen Interactions
Pathogens
Molecular interactions
Communicable Diseases
Proteins
Research Personnel
Databases
Molecules
Infection
Experiments

Keywords

  • biocuration
  • controlled vocabulary
  • host-pathogen interaction
  • interactome
  • network analysis
  • proteomics

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry

Cite this

Leveraging Experimental Details for an Improved Understanding of Host-Pathogen Interactome. / Ammari, Mais; McCarthy, Fiona M; Nanduri, Bindu.

In: Current Protocols in Bioinformatics, Vol. 61, No. 1, 01.03.2018, p. 8.26.1-8.26.12.

Research output: Contribution to journalArticle

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