ArticleBioinformatics (Oxford, England)2017
TRI_tool: a web-tool for prediction of protein-protein interactions in human transcriptional regulation.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
9 citing papers in PubMed, 17 citations in OpenAlex.
- HVIface: sequence-based deep learning for decoding human-virus protein-protein interfaces.Frontiers in bioinformatics · 2026Article
- The novel CFTR haplotype E583G/F508del in CFTR-related disorder.Molecular biology reports · 2024Article
- HormoNet: a deep learning approach for hormone-drug interaction prediction.BMC bioinformatics · 2024Article
- MKL/SRF and Bcl6 mutual transcriptional repression safeguards the fate and positioning of neocortical progenitor cells mediated by RhoA.Science advances · 2023Article
- Assessing the pathogenicity ofFrontiers in oncology · 2022Article
- ProteinPrompt: a webserver for predicting protein-protein interactions.Bioinformatics advances · 2022Article
- Large-Scale Protein Interactions Prediction by Multiple Evidence Analysis Associated With an In-Silico Curation Strategy.Frontiers in bioinformatics · 2021Article
- Regulation of signal transducer and activator of transcription 3 activation by dual-specificity phosphatase 3.BMB reports · 2020Article
- Protein-protein interaction prediction using a hybrid feature representation and a stacked generalization scheme.BMC bioinformatics · 2019Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
The TRI_tool, a sequence-based web tool for prediction of protein interactions in the human transcriptional regulation, is intended for biomedical investigators who work on understanding the regulation of gene expression. It has an improved predictive performance due to the training on updated, human specific, experimentally validated datasets. The TRI_tool is designed to test up to 100 potential interactions with no time delay and to report both probabilities and binarized predictions. AVAILABILITY AND IMPLEMENTATION: http://www.vin.bg.ac.rs/180/tools/tfpred.php CONTACT: vladaper@vinca.rs; nevenav@vinca.rsSupplementary information: Supplementary data are available at Bioinformatics online.
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What OpenQuestion holds
Registered trials
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.