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Articles 1 - 4 of 4
Full-Text Articles in Pharmacy and Pharmaceutical Sciences
De Novo Prediction Of Drug–Target Interactions Using Laplacian Regularized Schatten P-Norm Minimization, Gaoyan Wu, Mengyun Yang, Yaohang Li, Jianxin Wang
De Novo Prediction Of Drug–Target Interactions Using Laplacian Regularized Schatten P-Norm Minimization, Gaoyan Wu, Mengyun Yang, Yaohang Li, Jianxin Wang
Computer Science Faculty Publications
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 p-norm minimization (LRSpNM), to predict potential target proteins for novel drugs and potential drugs for …
A Semiparametric Modeling Approach For Analyzing Clinical Biomarkers Restricted To Limits Of Detection, Sandipan Dutta, Susan Halabi
A Semiparametric Modeling Approach For Analyzing Clinical Biomarkers Restricted To Limits Of Detection, Sandipan Dutta, Susan Halabi
Mathematics & Statistics Faculty Publications
Before biomarkers can be used in clinical trials or patients' management, the laboratory assays that measure their levels have to go through development and analytical validation. One of the most critical performance metrics for validation of any assay is related to the minimum amount of values that can be detected and any value below this limit is referred to as below the limit of detection (LOD). Most of the existing approaches that model such biomarkers, restricted by LOD, are parametric in nature. These parametric models, however, heavily depend on the distributional assumptions, and can result in loss of precision under …
Drug Repositioning Based On Bounded Nuclear Norm Regularization, Mengyun Yang, Huimin Lao, Yaohang Li, Jianxin Wang
Drug Repositioning Based On Bounded Nuclear Norm Regularization, Mengyun Yang, Huimin Lao, Yaohang Li, Jianxin Wang
Computer Science Faculty Publications
Motivation: Computational drug repositioning is a cost-effective strategy to identify novel indications for existing drugs. Drug repositioning is often modeled as a recommendation system problem. Taking advantage of the known drug–disease associations, the objective of the recommendation system is to identify new treatments by filling out the unknown entries in the drug–disease association matrix, which is known as matrix completion. Underpinned by the fact that common molecular pathways contribute to many different diseases, the recommendation system assumes that the underlying latent factors determining drug–disease associations are highly correlated. In other words, the drug–disease matrix to be completed is low-rank. Accordingly, …
Wake Me When It's Over- Bacterial Toxin-Antitoxin Proteins And Induced Dormancy, Nathan P. Coussens, Dayle A. Daines
Wake Me When It's Over- Bacterial Toxin-Antitoxin Proteins And Induced Dormancy, Nathan P. Coussens, Dayle A. Daines
Biological Sciences Faculty Publications
Toxin-antitoxin systems are encoded by bacteria and archaea to enable an immediate response to environmental stresses, including antibiotics and the host immune response. During normal conditions, the antitoxin components prevent toxins from interfering with metabolism and arresting growth; however, toxin activation enables microbes to remain dormant through unfavorable conditions that might continue over millions of years. Intense investigations have revealed a multitude of mechanisms for both regulation and activation of toxin-antitoxin systems, which are abundant in pathogenic microorganisms. This minireview provides an overview of the current knowledge regarding type II toxin-antitoxin systems along with their clinical and environmental implications.