Multi-scaled self-attention for drug–target interaction prediction based on multi-granularity representation

Yuni Zeng; Xiangru Chen; Dezhong Peng; Lijun Zhang; Haixiao Huang

doi:10.1186/s12859-022-04857-x

ScienceGate Book Chapters

JOURNAL ARTICLE

Multi-scaled self-attention for drug–target interaction prediction based on multi-granularity representation

Yuni Zeng Xiangru Chen Dezhong Peng Lijun Zhang Haixiao Huang

Year: 2022 Journal: BMC Bioinformatics Vol: 23 (1)Pages: 314-314 Publisher: BioMed Central

DOI: 10.1186/s12859-022-04857-x

Get Full-Text PDF Get Analytical Report

Keywords:

Granularity Representation (politics) Computer science Drug Computational biology DNA microarray Data mining Theoretical computer science Artificial intelligence Biology Genetics Programming language Pharmacology

Metrics

Cited By

1.84

FWCI (Field Weighted Citation Impact)

Refs

0.79

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Computational Drug Discovery Methods

Physical Sciences → Computer Science → Computational Theory and Mathematics

Machine Learning in Materials Science

Physical Sciences → Materials Science → Materials Chemistry

Protein Structure and Dynamics

Life Sciences → Biochemistry, Genetics and Molecular Biology → Molecular Biology

Multi-scaled self-attention for drug–target interaction prediction based on multi-granularity representation

Metrics

Citation History

Topics

Related Documents

MultiGranDTI: an explainable multi-granularity representation framework for drug-target interaction prediction

Prediction of Drug-Target Interaction Based on Multi-Head Self-Attention

Multi-view self-attention for interpretable drug–target interaction prediction

Drug-Target Interaction Prediction Using Multi-Head Self-Attention and Graph Attention Network

Dynamic Multi-Granularity Translation System: DAG-Structured Multi-Granularity Representation and Self-Attention