Drug–target interaction prediction using unifying of graph regularized nuclear norm with bilinear factorization

Drug–target interaction prediction using unifying of graph regularized nuclear norm with bilinear factorization

Background: Wet-lab experiments for identification of interactions between drugs and target proteins are time-consuming, costly and labor-intensive. The use of computational prediction of drug–target interactions (DTIs), which is one of the significant points in drug discovery, has been considered b...

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Bibliographic Details
Main Authors: Abbasi, Z. (Author), Mobarakeh, M.I (Author), Pirgazi, J. (Author), Sorkhi, A.G (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
algorithm
Algorithms
Computational prediction
Computational predictions
drug
drug development
Drug Development
Drug discovery
Drug Discovery
Drug interactions
Drug–target interaction
Drug-target interactions
Factorization
Forecasting
Interaction prediction
Lab. experiment
Labour-intensive
Low-rank interaction
Pharmaceutical Preparations
protein
Proteins
Search spaces
Significant points
Singular value decomposition
Target proteins
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