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Published on: February 23, 2024
De Novo Prediction of Drug-Target Interactions Using Laplacian Regularized Schatten -Norm Minimization
Gaoyan Wu1, Mengyun Yang2, Yaohang Li3
1The Hunan Provincial Key Lab of Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China.
Abstract:
In pharmaceutical sciences, a crucial step of the drug discovery is the identification of drug-target interactions (DTIs). However, only a small portion of the DTIs have been experimentally validated. Moreover, it is an extremely laborious, expensive, and time-consuming procedure to capture new interactions between drugs and targets through traditional biochemical experiments. Therefore, designing computational methods for predicting potential interactions to guide the experimental verification is of practical significance, especially for de novo situation. In this article, we propose a new algorithm, namely Laplacian regularized Schatten
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