2014
DOI: 10.1186/1745-6150-9-5
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Stringent homology-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions

Abstract: BackgroundH. sapiens-M. tuberculosis H37Rv protein-protein interaction (PPI) data are essential for understanding the infection mechanism of the formidable pathogen M. tuberculosis H37Rv. Computational prediction is an important strategy to fill the gap in experimental H. sapiens-M. tuberculosis H37Rv PPI data. Homology-based prediction is frequently used in predicting both intra-species and inter-species PPIs. However, some limitations are not properly resolved in several published works that predict eukaryot… Show more

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Cited by 66 publications
(59 citation statements)
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“…Additionally, potential drug targets of the pathogen that interact with the host have been identified to understand the infection mechanism using a dataset obtained from a computational prediction of Homo sapiens-Mycobacterium tuberculosis H37Rv protein-protein interactions [25]. This dataset is thought as a golden dataset for host-pathogen interaction.…”
Section: Resultsmentioning
confidence: 99%
“…Additionally, potential drug targets of the pathogen that interact with the host have been identified to understand the infection mechanism using a dataset obtained from a computational prediction of Homo sapiens-Mycobacterium tuberculosis H37Rv protein-protein interactions [25]. This dataset is thought as a golden dataset for host-pathogen interaction.…”
Section: Resultsmentioning
confidence: 99%
“…In the future work, author would extend the application of the proposed method on improving the works of Zhou et al those are related to computational biology [44], [45], [46].…”
Section: Discussionmentioning
confidence: 99%
“…There are several way to functionally and structurally annotate/predict important residues (Zhou et al 2013).…”
Section: Identification Of Functionally and Structurally Important Rementioning
confidence: 99%