ArticleBMC bioinformatics2008
Ortholog-based protein-protein interaction prediction and its application to inter-species interactions.
Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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53 citing papers in PubMed, 113 citations in OpenAlex.
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- An Improved Genome-Wide Association Procedure Explores Gene-Allele Constitutions and Evolutionary Drives of Growth Period Traits in the Global Soybean Germplasm Population.International journal of molecular sciences · 2023Article
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- Computational Network Inference for Bacterial Interactomics.mSystems · 2022Review
- Protein-protein interaction prediction with deep learning: A comprehensive review.Computational and structural biotechnology journal · 2022Review
- Deep learning frameworks for protein-protein interaction prediction.Computational and structural biotechnology journal · 2022Review
- Decrypting the complexity of the human malaria parasite biology through systems biology approaches.Frontiers in systems biology · 2022Article
- Host-pathogen protein-nucleic acid interactions: A comprehensive review.Computational and structural biotechnology journal · 2022Review
- Protein-protein interactions: Methods, databases, and applications in virus-host study.World journal of virology · 2021Review
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- Prediction of Human-Bioinformatics and biology insights · 2021Article
- HMI-PRED: A Web Server for Structural Prediction of Host-Microbe Interactions Based on Interface Mimicry.Journal of molecular biology · 2020Article
- An Integrative Computational Approach for the Prediction of Human-BioMed research international · 2020Article
- Transcriptomic Profiling of Mouse Brain During Acute and Chronic Infections byFrontiers in microbiology · 2020Article
- Computational identification of protein-protein interactions in model plant proteomes.Scientific reports · 2019Article
- Interface-Based Structural Prediction of Novel Host-Pathogen Interactions.Methods in molecular biology (Clifton, N.J.) · 2019Article
- A Bipartite Network Module-Based Project to Predict Pathogen-Host Association.Frontiers in genetics · 2019Article
Corrections and comments
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Authors and funding
7 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe rapid growth of protein-protein interaction (PPI) data has led to the emergence of PPI network analysis. Despite advances in high-throughput techniques, the interactomes of several model organisms are still far from complete. Therefore, it is desirable to expand these interactomes with ortholog-based and other methods.
resultsOrthologous pairs of 18 eukaryotic species were expanded and merged with experimental PPI datasets. The contributions of interologs from each species were evaluated. The expanded orthologous pairs enable the inference of interologs for various species. For example, more than 32,000 human interactions can be predicted. The same dataset has also been applied to the prediction of host-pathogen interactions. PPIs between P. falciparum calmodulin and several H. sapiens proteins are predicted, and these interactions may contribute to the maintenance of host cell Ca2+ concentration. Using comparisons with Bayesian and structure-based approaches, interactions between putative HSP40 homologs of P. falciparum and the H. sapiens TNF receptor associated factor family are revealed, suggesting a role for these interactions in the interference of the human immune response to P. falciparum.
conclusionThe PPI datasets are available from POINT http://point.bioinformatics.tw/ and POINeT http://poinet.bioinformatics.tw/. Further development of methods to predict host-pathogen interactions should incorporate multiple approaches in order to improve sensitivity, and should facilitate the identification of targets for drug discovery and design.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.