AI Medical Compendium Topic

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Databases, Pharmaceutical

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Improved drug response prediction by drug target data integration via network-based profiling.

Briefings in bioinformatics
Drug response prediction (DRP) is important for precision medicine to predict how a patient would react to a drug before administration. Existing studies take the cell line transcriptome data, and the chemical structure of drugs as input and predict ...

De novo generation of dual-target ligands using adversarial training and reinforcement learning.

Briefings in bioinformatics
Artificial intelligence, such as deep generative methods, represents a promising solution to de novo design of molecules with the desired properties. However, generating new molecules with biological activities toward two specific targets remains an ...

Deep learning for drug-drug interaction extraction from the literature: a review.

Briefings in bioinformatics
Drug-drug interactions (DDIs) are crucial for drug research and pharmacovigilance. These interactions may cause adverse drug effects that threaten public health and patient safety. Therefore, the DDIs extraction from biomedical literature has been wi...

Using Supervised Learning Methods to Develop a List of Prescription Medications of Greatest Concern during Pregnancy.

Maternal and child health journal
INTRODUCTION: Women and healthcare providers lack adequate information on medication safety during pregnancy. While resources describing fetal risk are available, information is provided in multiple locations, often with subjective assessments of ava...

Ensembled machine learning framework for drug sensitivity prediction.

IET systems biology
Drug sensitivity prediction is one of the critical tasks involved in drug designing and discovery. Recently several online databases and consortiums have contributed to providing open access to pharmacogenomic data. These databases have helped in dev...

The reactome pathway knowledgebase.

Nucleic acids research
The Reactome Knowledgebase (https://reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network of molecular transformations in a single consistent data mo...

Drug knowledge bases and their applications in biomedical informatics research.

Briefings in bioinformatics
Recent advances in biomedical research have generated a large volume of drug-related data. To effectively handle this flood of data, many initiatives have been taken to help researchers make good use of them. As the results of these initiatives, many...

Predicting drug synergy for precision medicine using network biology and machine learning.

Journal of bioinformatics and computational biology
Identification of effective drug combinations for patients is an expensive and time-consuming procedure, especially for experiments. To accelerate the synergistic drug discovery process, we present a new classification model to identify more effecti...

Facilitating prediction of adverse drug reactions by using knowledge graphs and multi-label learning models.

Briefings in bioinformatics
Timely identification of adverse drug reactions (ADRs) is highly important in the domains of public health and pharmacology. Early discovery of potential ADRs can limit their effect on patient lives and also make drug development pipelines more robus...

canSAR: update to the cancer translational research and drug discovery knowledgebase.

Nucleic acids research
canSAR (http://cansar.icr.ac.uk) is a public, freely available, integrative translational research and drug discovery knowlegebase. canSAR informs researchers to help solve key bottlenecks in cancer translation and drug discovery. It integrates genom...