ArticleMolecular diversity2014
LBVS: an online platform for ligand-based virtual screening using publicly accessible databases.
Article in Molecular diversity, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed.
- The Evolution of Machine Learning in Medicinal Chemistry: A Comprehensive Bibliometric Analysis.Current neuropharmacology · 2026Review
- Article
- DenovoProfiling: A webserver forComputational and structural biotechnology journal · 2022Article
- DeepScreening: a deep learning-based screening web server for accelerating drug discovery.Database : the journal of biological databases and curation · 2019Article
- AlzhCPI: A knowledge base for predicting chemical-protein interactions towards Alzheimer's disease.PloS one · 2017Article
- Adapting Document Similarity Measures for Ligand-Based Virtual Screening.Molecules (Basel, Switzerland) · 2016Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abundant data on compound bioactivity and publicly accessible chemical databases increase opportunities for ligand-based drug discovery. In order to make full use of the data, an online platform for ligand-based virtual screening (LBVS) using publicly accessible databases has been developed. LBVS adopts Bayesian learning approach to create virtual screening models because of its noise tolerance, speed, and efficiency in extracting knowledge from data. LBVS currently includes data derived from BindingDB and ChEMBL. Three validation approaches have been employed to evaluate the virtual screening models created from LBVS. The tenfold cross validation results of twenty different LBVS models demonstrate that LBVS achieves an average AUC value of 0.86. Our internal and external testing results indicate that LBVS is predictive for lead identifications. LBVS can be publicly accessed at http://rcdd.sysu.edu.cn/lbvs.
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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.