Prediction of drug–target interactions from multi-molecular network based on deep walk embedding model

ZH Chen, ZH You, ZH Guo, HC Yi, GX Luo… - … in Bioengineering and …, 2020 - frontiersin.org
Predicting drug–target interactions (DTIs) is crucial in innovative drug discovery, drug
repositioning and other fields. However, there are many shortcomings for predicting DTIs …

Homoharringtonine exerts anti-tumor effects in hepatocellular carcinoma through activation of the hippo pathway

H Wang, R Wang, D Huang, S Li, B Gao… - Frontiers in …, 2021 - frontiersin.org
Hepatocellular carcinoma (HCC) is the most prevalent subtype of liver cancer with a
mortality rate of approximately 3–6/100,000 and is the third leading cause of cancer-related …

Using predicate and provenance information from a knowledge graph for drug efficacy screening

WJ Vlietstra, R Vos, AM Sijbers… - Journal of biomedical …, 2018 - Springer
Background Biomedical knowledge graphs have become important tools to computationally
analyse the comprehensive body of biomedical knowledge. They represent knowledge as …

Systematic interrogation of diverse Omic data reveals interpretable, robust, and generalizable transcriptomic features of clinically successful therapeutic targets

AD Rouillard, MR Hurle, P Agarwal - PLoS Computational Biology, 2018 - journals.plos.org
Target selection is the first and pivotal step in drug discovery. An incorrect choice may not
manifest itself for many years after hundreds of millions of research dollars have been spent …

Predicting intervention approval in clinical trials through multi-document summarization

G Katsimpras, G Paliouras - arXiv preprint arXiv:2204.00290, 2022 - arxiv.org
Clinical trials offer a fundamental opportunity to discover new treatments and advance the
medical knowledge. However, the uncertainty of the outcome of a trial can lead to …

Antimetastatic lung cancer therapy using alkaloid Piperlongumine noncovalently bound to С60 fullerene

I Horak, T Skaterna, S Lugovskyi, I Krysiuk… - Journal of Drug Delivery …, 2024 - Elsevier
A novel nanoformulation, C 60 fullerene loaded with a plant alkaloid Piperlongumine (PL)
molecules (C 60-PL nanocomplex), as a potential drug for the treatment of highly metastatic …

Perturbation-theory machine learning (PTML) multilabel model of the CheMBL dataset of preclinical assays for antisarcoma compounds

A Cabrera-Andrade, A Lopez-Cortes, CR Munteanu… - ACS …, 2020 - ACS Publications
Sarcomas are a group of malignant neoplasms of connective tissue with a different etiology
than carcinomas. The efforts to discover new drugs with antisarcoma activity have generated …

Evaluating and improving annotation tools for medical forms

YC Lin, V Christen, A Groß, SD Cardoso… - Data Integration in the …, 2017 - Springer
The annotation of entities with concepts from standardized terminologies and ontologies is
of high importance in the life sciences to enhance semantic interoperability, information …

Daphnane-Type Diterpenes from Stelleropsis tianschanica and Their Antitumor Activity

X He, X Abulizi, X Li, G Ma, Z Sun, H Wei, X Xu, L Shi… - Molecules, 2022 - mdpi.com
Four new daphnane-type diterpenes named tianchaterpenes CF (1–4) and six known ones
were isolated from Stelleropsis tianschanica. Their structures were elucidated based on …

Predicting clinically promising therapeutic hypotheses using tensor factorization

J Yao, MR Hurle, MR Nelson, P Agarwal - BMC bioinformatics, 2019 - Springer
Background Determining which target to pursue is a challenging and error-prone first step in
developing a therapeutic treatment for a disease, where missteps are potentially very costly …