ArticleScientific reports2021
Random forest classification for predicting lifespan-extending chemical compounds.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
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- Collagen disorder architecture features are associated with clinical, molecular, genetic factors and survival outcomes in colon cancer.NPJ precision oncology · 2025Article
- Digital Alchemy: The Rise of Machine and Deep Learning in Small-Molecule Drug Discovery.International journal of molecular sciences · 2025Review
- Role of artificial intelligence in revolutionizing drug discovery.Fundamental research · 2025Review
- Artificial intelligence in antidiabetic drug discovery: The advances in QSAR and the prediction of α-glucosidase inhibitors.Computational and structural biotechnology journal · 2024Review
- Identification of angiogenesis-related genes and molecular subtypes for psoriasis based on random forest algorithm.Clinical and experimental immunology · 2024Article
- Transfer learning for a foundational chemistry model.Chemical science · 2024Article
- Deconvoluting low yield from weak potency in direct-to-biology workflows with machine learning.RSC medicinal chemistry · 2024Article
- The Experimentalist's Guide to Machine Learning for Small Molecule Design.ACS applied bio materials · 2024Review
- Predictive Minisci late stage functionalization with transfer learning.Nature communications · 2024Article
- Distinct soluble immune checkpoint profiles characterize COVID-19 severity, mortality and SARS-CoV-2 variant infections.Frontiers in immunology · 2024Article
- ChatGPT Chemistry Assistant for Text Mining and the Prediction of MOF Synthesis.Journal of the American Chemical Society · 2023Article
- Article
- Discovery of senolytics using machine learning.Nature communications · 2023Article
- The landscape of aging.Science China. Life sciences · 2022Review
- Identification of Novel Arachidonic Acid 15-Lipoxygenase Inhibitors Based on the Bayesian Classifier Model and Computer-Aided High-Throughput Virtual Screening.Pharmaceuticals (Basel, Switzerland) · 2022Article
- Controlling astrocyte-mediated synaptic pruning signals for schizophrenia drug repurposing with deep graph networks.PLoS computational biology · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ageing is a major risk factor for many conditions including cancer, cardiovascular and neurodegenerative diseases. Pharmaceutical interventions that slow down ageing and delay the onset of age-related diseases are a growing research area. The aim of this study was to build a machine learning model based on the data of the DrugAge database to predict whether a chemical compound will extend the lifespan of Caenorhabditis elegans. Five predictive models were built using the random forest algorithm with molecular fingerprints and/or molecular descriptors as features. The best performing classifier, built using molecular descriptors, achieved an area under the curve score (AUC) of 0.815 for classifying the compounds in the test set. The features of the model were ranked using the Gini importance measure of the random forest algorithm. The top 30 features included descriptors related to atom and bond counts, topological and partial charge properties. The model was applied to predict the class of compounds in an external database, consisting of 1738 small-molecules. The chemical compounds of the screening database with a predictive probability of ≥ 0.80 for increasing the lifespan of Caenorhabditis elegans were broadly separated into (1) flavonoids, (2) fatty acids and conjugates, and (3) organooxygen compounds.
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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.