Leveraging Experimental Details for an Improved Understanding of Host‐Pathogen Interactome. Issue 1 (9th April 2018)

• Record Type: Journal Article
• Authors: Ammari, Mais; McCarthy, Fiona; Nanduri, Bindu
• Editors: Baxevanis, Andreas D.; Petsko, Gregory A.; Stein, Lincoln D.; Stormo, Gary D.
• Is Part Of: Current protocols in bioinformatics. Volume 61:Issue 1(2018)
• Page Start: 8.26.1
• Page End: 8.26.12
• Publication Date: 2018-04-09
• Subjects: biocuration -- controlled vocabulary -- host‐pathogen interaction -- interactome -- network analysis -- proteomics; Bioinformatics -- Laboratory manuals; Nucleotide sequence -- Laboratory manuals; Amino acid sequence -- Laboratory manuals; Base Sequence; Amino Acid Sequence; Computational Biology -- methods; Databases, Genetic; Proteins -- analysis; Sequence Analysis -- methods; Sequence Homology; Amino acid sequence; Bioinformatics; Nucleotide sequence; Laboratory Manuals; Laboratory manuals; 570.285
• DOI: 10.1002/cpbi.44
• Languages: English
• ISSNs: 1934-3396

Abstract

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. © 2018 by John Wiley & Sons, Inc.