BMC bioinformatics
Apr 12, 2022
BACKGROUND: In research on new drug discovery, the traditional wet experiment has a long period. Predicting drug-target interaction (DTI) in silico can greatly narrow the scope of search of candidate medications. Excellent algorithm model may be more...
Current opinion in biotechnology
Apr 9, 2022
Machine learning (ML) is revolutionizing our ability to understand and predict the complex relationships between protein sequence, structure, and function. Predictive sequence-function models are enabling protein engineers to efficiently search the s...
PLoS computational biology
Apr 6, 2022
With the great advancements in experimental data, computational power and learning algorithms, artificial intelligence (AI) based drug design has begun to gain momentum recently. AI-based drug design has great promise to revolutionize pharmaceutical ...
Journal of chemical information and modeling
Apr 5, 2022
The lead optimization phase of drug discovery refines an initial hit molecule for desired properties, especially potency. Synthesis and experimental testing of the small perturbations during this refinement can be quite costly and time-consuming. Rel...
Scientific reports
Apr 1, 2022
Accurate identification of drug-targets in human body has great significance for designing novel drugs. Compared with traditional experimental methods, prediction of drug-targets via machine learning algorithms has enhanced the attention of many rese...
Nature communications
Apr 1, 2022
Deep Learning (DL) has recently enabled unprecedented advances in one of the grand challenges in computational biology: the half-century-old problem of protein structure prediction. In this paper we discuss recent advances, limitations, and future pe...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 1, 2022
Predicting the interaction between a compound and a target is crucial for rapid drug repurposing. Deep learning has been successfully applied in drug-target affinity (DTA)problem. However, previous deep learning-based methods ignore modeling the dire...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 1, 2022
In recent years, cancer patients survival prediction holds important significance for worldwide health problems, and has gained many researchers attention in medical information communities. Cancer patients survival prediction can be seen the classif...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 1, 2022
Identifying protein subcellular locations is an important topic in protein function prediction. Interacting proteins may share similar locations. Thus, it is imperative to infer protein subcellular locations by taking protein-protein interactions (PP...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 1, 2022
Biomedical interaction networks have incredible potential to be useful in the prediction of biologically meaningful interactions, identification of network biomarkers of disease, and the discovery of putative drug targets. Recently, graph neural netw...