Predicting adverse drug reactions of two‐drug combinations using structural and transcriptomic drug representations to train an artificial neural network

S Shankar, I Bhandari, DT Okou… - Chemical Biology & …, 2021 - Wiley Online Library
Adverse drug reactions (ADRs) are pharmacological events triggered by drug interactions
with various sources of origin including drug–drug interactions. While there are many …

Combined graph/relational database management system for calculated chemical reaction pathway data

T Gimadiev, R Nugmanov, D Batyrshin… - Journal of Chemical …, 2021 - ACS Publications
Presently, quantum chemical calculations are widely used to generate extensive data sets
for machine learning applications; however, generally, these sets only include information …

Predicting clinical trial outcomes using drug bioactivities through graph database integration and machine learning

V Murali, YP Muralidhar, C Königs… - Chemical Biology & …, 2022 - Wiley Online Library
The ability to estimate the probability of a drug to receive approval in clinical trials provides
natural advantages to optimizing pharmaceutical research workflows. Success rates of …

Predicting clinical trial outcomes using drug bioactivities through graph database integration and machine learning

P Athri, V Murali, PY Muralidhar, C Königs, M Nair… - 2022 - chemrxiv.org
The ability to estimate the probability of a drug to receive approval in clinical trials provides
natural advantages to optimizing pharmaceutical research workflows. Success rates of …

[PDF][PDF] Design of a Chemical Graph Database to Query on an Atom-Specific Level

S Drenth - researchgate.net
Most molecule-oriented databases allow many different queries. Eg, for the leading
biomolecular database PubChem, molecules can be queried on the molecule name, its …