ArticleMolecular diversity2022
Anti-Ebola: an initiative to predict Ebola virus inhibitors through machine learning.
Article in Molecular diversity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Machine learning-driven drug repurposing and computational validation for Nipah virus.Molecular diversity · 2026Article
- Artificial Intelligence in Pharmaceutical Care:Saudi medical journal · 2026Review
- Advancing Antiviral Design: Integrating Natural Products, Computation and Targeted Delivery.Chemical biology & drug design · 2026Review
- Anti-EBV: Artificial intelligence driven predictive modeling for repurposing drugs as potential antivirals against Epstein-Barr virus.Computational and structural biotechnology journal · 2025Article
- Advancements in Viral Genomics: Gated Recurrent Unit Modeling of SARS-CoV-2, SARS, MERS, and Ebola viruses.Revista da Sociedade Brasileira de Medicina Tropical · 2025Article
- i-DENV: development of QSAR based regression models for predicting inhibitors targeting non-structural (NS) proteins of dengue virus.Frontiers in pharmacology · 2025Article
- Screening for Potential Antiviral Compounds from Cyanobacterial Secondary Metabolites Using Machine Learning.Marine drugs · 2024Article
- Article
- Cheminformatics-Based Study Identifies Potential Ebola VP40 Inhibitors.International journal of molecular sciences · 2023Article
- Artificial Intelligence, Machine Learning, and Big Data for Ebola Virus Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2023Article
- Computational Study on Potential Novel Anti-Ebola Virus Protein VP35 Natural Compounds.Biomedicines · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Ebola virus is a deadly pathogen responsible for a frequent series of outbreaks since 1976. Despite various efforts from researchers worldwide, its mortality and fatality are quite high. For antiviral drug discovery, the computational efforts are considered highly useful. Therefore, we have developed an 'anti-Ebola' web server, through quantitative structure-activity relationship information of available molecules with experimental anti-Ebola activities. Three hundred and five unique anti-Ebola compounds with their respective IC
Indexed as
Identifiers
What Socratic 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 Socratic graph.