murug030 [at] umn [dot] edu
gh/k8rthik · in/k8rthik
minneapolis
dr.active
Developed a regression model using RDKit and scikit-learn's random forest to predict binding affinity (MAE) from SMILES string and target name with 70% accuracy. Subsequently implemented a Graph Neural Network to increase arruracy by 15%. Used Gradio to deploy interactive demo to web.
[demo] [code]BioScrolls
Fine-tuned BioBERT and relation extraction techniques to mine multilingual biomedical literature for neurological gene-disease-drug associations, building a time-indexed knowledge graph with key metrics such as entity frequency, relationship confidence, and trend analysis over time.
[demo] [code]dr.optimus
Developed a drug optimization pipeline using Deep Q-Networks (DQN), where the agent modifies molecular structures represented as graphs using a Graph Neural Network (GNN)-based environment; evaluated optimization success using QED (Quantitative Estimate of Drug-likeness), binding affinity scores from docking simulations (e.g., AutoDock), and toxicity predictions generated by pre-trained classification models.
[demo] [code]nothing here yet. soon.
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