Article

Neighborhood-based Inference and Restricted Boltzmann Machine for microbe and drug associations prediction

2022-04-25

Abstract excerpt

Efficient identification of microbe-drug associations is critical for drug development and solving problem of antimicrobial resistance. Traditional wet-lab method requires a lot of money and labor in identifying potential microbe-drug associations. With development of machine learning and large amounts of biological data, computational methods become feasible. In this paper, we proposed a computational model of Ne...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: f6df0cf1-91d1-5f38-929e-c8956c195013
DOI: 10.21203/rs.3.rs-1579671/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Neighborhood-based Inference and Restricted Boltzmann Machine for microbe and drug associations predictionDOI 10.21203/rs.3.rs-1579671/v1Read

Analysis of protein-ligand interactions of SARS-CoV-2 against selective drug using deep neural networksSemantic proximity Read

MDMD: a computational model for predicting drug-related microbes based on the aggregated metapaths from a heterogeneous networkSemantic proximity Read

MDAD: A Special Resource for Microbe-Drug AssociationsSemantic proximity Read

DPDDI:a Deep Predictor for Drug-Drug InteractionsSemantic proximity Read

Deep-belief network for predicting potential miRNA-disease associations.Semantic proximity Read

Interpretable Drug Response Prediction through Molecule Structure-aware and Knowledge-Guided Visible Neural NetworkSemantic proximity Read

Profiling Molecular Simulations of SARS-CoV-2 Main Protease (Mpro) Binding to Repurposed Drugs Using Neural Network Force FieldsSemantic proximity Read

Research on Drug-Drug Interaction Prediction Using Capsule Neural Network Based on Self-Attention MechanismSemantic proximity Read

Exploration of Dark Chemical Genomics Space via Portal Learning: Applied to Targeting the Undruggable Genome and COVID-19 Anti-Infective PolypharmacologySemantic proximity Read

DeepLPI: a novel deep learning-based model for protein-ligand interaction prediction for drug repurposingSemantic proximity Read

A multi-scale pipeline linking drug transcriptomics with pharmacokinetics predicts in vivo interactions of tuberculosis drugsSemantic proximity Read

Discovering the mechanism of action of drugs with a sparse explainable network.Semantic proximity Read