Home ›
Entities
› academia
› Predicting the anticancer activity of indole derivatives: A novel GP-tree-based QSAR model optimized by ALO with insights from molecular docking and decision-making methods
Predicting the anticancer activity of indole derivatives: A novel GP-tree-based QSAR model optimized by ALO with insights from molecular docking and decision-making methods
Research article (Computers in Biology and Medicine, 2025) · cited 11× · AI/ML
Predicting the anticancer activity of indole derivatives: A novel GP-tree-based QSAR model optimized by ALO with insights from molecular docking and decision-making methods
Summary
Predicting the anticancer activity of indole derivatives: A novel GP-tree-based QSAR model optimized by ALO with insights from molecular docking and decision-making methods is a scholarly article[1].
Key Facts
Predicting the anticancer activity of indole derivatives: A novel GP-tree-based QSAR model optimized by ALO with insights from molecular docking and decision-making methods'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). Predicting the anticancer activity of indole derivatives: A novel GP-tree-based QSAR model optimized by ALO with insights from molecular docking and decision-making methods. Retrieved May 24, 2026, from https://4ort.xyz/entity/predicting-the-anticancer-activity-of-indole-derivatives-a-novel-gp-tree-based-qsar-model-optimized-by-alo-with-insights
MLA“Predicting the anticancer activity of indole derivatives: A novel GP-tree-based QSAR model optimized by ALO with insights from molecular docking and decision-making methods.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/predicting-the-anticancer-activity-of-indole-derivatives-a-novel-gp-tree-based-qsar-model-optimized-by-alo-with-insights.
BibTeX@misc{4ortxyz_predicting-the-anticancer-activity-of-indole-derivatives-a-novel-gp-tree-based-qsar-model-optimized-by-alo-with-insights_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Predicting the anticancer activity of indole derivatives: A novel GP-tree-based QSAR model optimized by ALO with insights from molecular docking and decision-making methods}}, year = {2026}, url = {https://4ort.xyz/entity/predicting-the-anticancer-activity-of-indole-derivatives-a-novel-gp-tree-based-qsar-model-optimized-by-alo-with-insights}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Predicting the anticancer activity of indole derivatives: A novel GP-tree-based QSAR model optimized by ALO with insights from molecular docking and decision-making methods — https://4ort.xyz/entity/predicting-the-anticancer-activity-of-indole-derivatives-a-novel-gp-tree-based-qsar-model-optimized-by-alo-with-insights (retrieved 2026-05-24)
