Here, we propose a novel method, named PreDR (Predict Drug Repositioning), to integrate chemical structures, target proteins, and side-effects to infer new diseases for existing drugs by uncovering the potential associations between drugs and diseases.

2013年11月11日 · Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases.

Target prediction for an input compound can be executed at the Target-Prediction site. The ATC-Tree offers a browsable overview over all ATC categories and codes from the WHO, including a ChEMBL mapping and linking for all contained small molecule drugs. Information to data filtering and training sets can be found on the statistics page.

2017年1月17日 · PreDR (Wang et al., 2013) utilizes kernel fusion to integrate chemical similarity, target protein similarity, side effect similarity and disease similarity information of known drug–disease pairs, then SVM is trained to predict novel drug–disease associations. TL-HGBI constructs a triple-layer heterogeneous network which incorporates drug ...

2013年12月13日 · Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize...

2013年11月11日 · Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases.

I'm Predrag and this site is my playground. I mostly play around with compilers and query systems, most recently for finding and preventing bugs across system boundaries and in library semantic versioning. I tend to post shorter content on my Twitter. Some of …

2022年10月28日 · Wang et al. [22] proposed a framework, called PreDR, for drug repositioning, which calculated the similarity between drug-disease pairs through the constructed kernel function, and then trained a support vector machine with the defined kernel to find the novel effects between drugs and diseases.

2013年11月11日 · Here, we propose a new method for drug repositioning, PreDR (Predict Drug Repositioning), to integrate molecular structure, molecular activity, and phenotype data. Specifically, we characterize drug by profiling in chemical structure, target protein, and side-effects space, and define a kernel function to correlate drugs with diseases.

We design a novel algorithm, named PreDR, to predict drug repositioning by associating known drugs with potential disease labels based on kernel fusion of heterogenous data sources.