Drug effect prediction using neural network
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Updated
Sep 14, 2020 - Python
Drug effect prediction using neural network
Gene and Primer Sequence Analysis for SARS-CoV-2, EGFR(Non Small Lung Cancer Cell), Influenza DNAs ### How can I check my Oligo primers to ensure there are no significant primer design issues? - The difference between melting temperatures (Tm) of the primers should be less than 5°C. - The GC content should be between 35-80% or equivalent to the …
LigEGFR: Spatial graph embedding and molecular descriptors assisted bioactivity prediction of ligand molecules for epidermal growth factor receptor on a cell line-based dataset
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ML-powered drug discovery pipeline for EGFR cancer target — ChEMBL data, Morgan fingerprints, Random Forest (92.31% accuracy), AutoDock Vina molecular docking & 3D visualization
Free clinical calculators and medical reference tools for healthcare professionals. 100+ evidence-based tools including eGFR, BMI, A1C, MELD, CHA₂DS₂-VASc, and more.
Structural bioinformatics analysis of the EGFR T790M drug-resistance mutation using BioPython, protein structure analysis, ligand interaction mapping, and mutation characterization.
Open-source medical calculator formulas and clinical scoring systems. Reference implementations for eGFR, BMI, MELD, CHA₂DS₂-VASc, A1C, and 100+ more. Used by mdtools.org.
Protein Design Competition
De novo computational design of tumor-selective pH-conditional (pH 6.5 vs 7.4), cross-species EGFR miniprotein binders for the Anthropic × Adaptyv 2026 Challenge.
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Mechanistic digital twin for Type 2 Diabetes → CKD, modeling renal decline through hyperfiltration dynamics, interpretable parameters, Bayesian inference, and AI.
My first RShiny-WebApp for different laboratory estimations and scores
EGFR target - potency and ADMET QSAR
임상 검사 수치·약동학 통합 계산 API
EGFRIndb
AI-assisted structure-based drug discovery workflow for EGFR T790M resistance mutation using molecular docking, interaction analysis, and lead prioritization.
Computational docking project of EGFR wildtype and clinically relevant mutants (L858R, T790M, Exon20ins) with first-, second-, and third-generation TKIs. Includes automated data fetching, preprocessing, docking with AutoDock Vina, and statistical analysis of binding affinities.
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