AIMC Topic: Drug Interactions
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Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME.
Database : the journal of biological databases and curation
Sep 16, 2015
Today's large, public databases of protein-small molecule interaction data are creating important new opportunities for data mining and integration. At the same time, new graphical user interface-based workflow tools offer facile alternatives to cust...
Learning the Structure of Biomedical Relationships from Unstructured Text.
PLoS computational biology
Jul 28, 2015
The published biomedical research literature encompasses most of our understanding of how drugs interact with gene products to produce physiological responses (phenotypes). Unfortunately, this information is distributed throughout the unstructured te...
Gene Ontology and KEGG Pathway Enrichment Analysis of a Drug Target-Based Classification System.
PloS one
May 7, 2015
Drug-target interaction (DTI) is a key aspect in pharmaceutical research. With the ever-increasing new drug data resources, computational approaches have emerged as powerful and labor-saving tools in predicting new DTIs. However, so far, most of thes...
Toward a complete dataset of drug-drug interaction information from publicly available sources.
Journal of biomedical informatics
Apr 24, 2015
Although potential drug-drug interactions (PDDIs) are a significant source of preventable drug-related harm, there is currently no single complete source of PDDI information. In the current study, all publically available sources of PDDI information ...
Extracting drug-drug interactions from literature using a rich feature-based linear kernel approach.
Journal of biomedical informatics
Mar 19, 2015
Identifying unknown drug interactions is of great benefit in the early detection of adverse drug reactions. Despite existence of several resources for drug-drug interaction (DDI) information, the wealth of such information is buried in a body of unst...
Functional evaluation of out-of-the-box text-mining tools for data-mining tasks.
Journal of the American Medical Informatics Association : JAMIA
Oct 21, 2014
OBJECTIVE: The trade-off between the speed and simplicity of dictionary-based term recognition and the richer linguistic information provided by more advanced natural language processing (NLP) is an area of active discussion in clinical informatics. ...
Modeling analgesic drug interactions using support vector regression: a new approach to isobolographic analysis.
Journal of pharmacological and toxicological methods
Sep 28, 2014
BACKGROUND: Modeling drug interactions is important for illustrating combined drug actions and for predicting the pharmacological and/or toxicological effects that can be obtained using combined drug therapy.
SMVSNN: An Intelligent Framework for Anticancer Drug-Drug Interaction Prediction Utilizing Spiking Multi-view Siamese Neural Networks.
Journal of chemical information and modeling
Jun 9, 2025
The study of synergistic drug combinations is vital in cancer treatment, enhancing efficacy, reducing resistance, and minimizing side effects through complementary drug actions. Drug-drug interaction (DDI) analysis offers essential theoretical suppor...
Drug-Drug interactions and special considerations in breast cancer patients treated with CDK4/6 inhibitors: A comprehensive review.
Cancer treatment reviews
Jun 1, 2025
Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) have reshaped the treatment paradigm of hormone receptor positive (HR + )/HER2-negative breast cancer in both adjuvant and metastatic settings. However, their metabolism via the cytochrome P450 (CYP3A4...
Fuzzy-DDI: A robust fuzzy logic query model for complex drug-drug interaction prediction.
Artificial intelligence in medicine
Jun 1, 2025
Drug-drug interactions (DDI) refer to the compound effects that occur when patients take multiple drugs simultaneously, which may reduce the drug efficacy and even harm the patient's health. Therefore, DDI prediction is significant for drug developme...
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