Prescriptions

Extracting drug-enzyme relation from literature as evidence for drug drug interaction.

BACKGROUND: Information about drug-drug interactions (DDIs) is crucial for computational applications such as pharmacovigilance and drug repurposing. However, existing sources of DDIs have the problems of low coverage, low accuracy and low agreement. One common type of DDIs is related to the mechanism of drug metabolism: a DDI relation may be caused by different interactions (e.g., substrate, inhi...

Vaccine and Drug Ontology Studies (VDOS 2014).

The "Vaccine and Drug Ontology Studies" (VDOS) international workshop series focuses on vaccine- and drug-related ontology modeling and applications. Drugs and vaccines have been critical to prevent and treat human and animal diseases. Work in both (drugs and vaccines) areas is closely related - from preclinical research and development to manufacturing, clinical trials, government approval and re...

Evaluation of a machine learning capability for a clinical decision support system to enhance antimicrobial stewardship programs.

OBJECTIVE: Antimicrobial stewardship programs have been shown to limit the inappropriate use of antimicrobials. Hospitals are increasingly relying on ...

Vision-Based Pose Estimation for Robot-Mediated Hand Telerehabilitation.

Vision-based Pose Estimation (VPE) represents a non-invasive solution to allow a smooth and natural interaction between a human user and a robotic sys...

Network-based in silico drug efficacy screening.

The increasing cost of drug development together with a significant drop in the number of new drug approvals raises the need for innovative approaches...

Drug-Drug Interaction Extraction via Convolutional Neural Networks.

Drug-drug interaction (DDI) extraction as a typical relation extraction task in natural language processing (NLP) has always attracted great attention...

Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique.

Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least...

Drug repositioning for non-small cell lung cancer by using machine learning algorithms and topological graph theory.

BACKGROUND: Non-small cell lung cancer (NSCLC) is one of the leading causes of death globally, and research into NSCLC has been accumulating steadily ...

An Expanded Analysis of Pharmacogenetics Determinants of Efavirenz Response that Includes 3'-UTR Single Nucleotide Polymorphisms among Black South African HIV/AIDS Patients.

INTRODUCTION: Efavirenz (EFV) is a non-nucleoside reverse transcriptase inhibitor prescribed as part of first-line highly active antiretroviral therap...

Predicting Drug-Target Interactions With Multi-Information Fusion.

Identifying potential associations between drugs and targets is a critical prerequisite for modern drug discovery and repurposing. However, predicting...

Progesterone supplementation during the time of pregnancy recognition after artificial insemination improves conception rates in high-producing dairy cows.

This study examines the possible effects of progesterone (P4) supplementation during the time of pregnancy recognition, from Days 15 to 17 post-artifi...

Predicting Long Noncoding RNA and Protein Interactions Using Heterogeneous Network Model.

Recent study shows that long noncoding RNAs (lncRNAs) are participating in diverse biological processes and complex diseases. However, at present the ...

Prediction of Synergism from Chemical-Genetic Interactions by Machine Learning.

The structure of genetic interaction networks predicts that, analogous to synthetic lethal interactions between non-essential genes, combinations of c...

An unsupervised learning method to identify reference intervals from a clinical database.

Reference intervals are critical for the interpretation of laboratory results. The development of reference intervals using traditional methods is tim...

Automated evaluation of protein binding affinity of anti-inflammatory choline based ionic liquids.

In this work, an automated system for the study of the interaction of drugs with human serum albumin (HSA) was developed. The methodology was based on...

Extraction of Protein-Protein Interaction from Scientific Articles by Predicting Dominant Keywords.

For the automatic extraction of protein-protein interaction information from scientific articles, a machine learning approach is useful. The classifie...

Towards Extracting Supporting Information About Predicted Protein-Protein Interactions.

One of the goals of relation extraction is to identify protein-protein interactions (PPIs) in biomedical literature. Current systems are capturing bin...

PRIdictor: Protein-RNA Interaction predictor.

Several computational methods have been developed to predict RNA-binding sites in protein, but its inverse problem (i.e., predicting protein-binding s...

Learning Predictive Interactions Using Information Gain and Bayesian Network Scoring.

BACKGROUND: The problems of correlation and classification are long-standing in the fields of statistics and machine learning, and techniques have bee...

Predictive modeling of structured electronic health records for adverse drug event detection.

BACKGROUND: The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilit...