Home ›
Entities
› academia
› Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms
Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms
Research article (BMC Chemistry, 2024) · cited 30× · AI/ML
Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms
Summary
Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms is a scholarly article[1].
Key Facts
Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms. Retrieved May 24, 2026, from https://4ort.xyz/entity/exploring-the-role-of-topological-descriptors-to-predict-physicochemical-properties-of-anti-hiv-drugs-by-using-supervise
MLA“Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/exploring-the-role-of-topological-descriptors-to-predict-physicochemical-properties-of-anti-hiv-drugs-by-using-supervise.
BibTeX@misc{4ortxyz_exploring-the-role-of-topological-descriptors-to-predict-physicochemical-properties-of-anti-hiv-drugs-by-using-supervise_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms}}, year = {2026}, url = {https://4ort.xyz/entity/exploring-the-role-of-topological-descriptors-to-predict-physicochemical-properties-of-anti-hiv-drugs-by-using-supervise}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms — https://4ort.xyz/entity/exploring-the-role-of-topological-descriptors-to-predict-physicochemical-properties-of-anti-hiv-drugs-by-using-supervise (retrieved 2026-05-24)