... Attribution License 4.0 (CC BY) . antimicrobial peptides autophagy cell penetrating peptide machine learning microbiome During the history of drug development, scientists have explored the use of small molecules (e.g., penicillin, metformine), large-size molecules (e.g., antibodies, vaccines...

...Wei Liu; Wei Ma; Na Bai; Chunyan Li; Kuangpin Liu; Jinwei Yang; Sijia Zhang; Kewei Zhu; Qiang Zhou; Hua Liu; Jianhui Guo; Liyan Li Embolic stroke (ES) is characterized by high morbidity and mortality. Its mortality predictors remain unclear. The present study aimed to use machine learning (ML...

... © 2021 The Author(s). 2021 This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY) . cervical cancer differentially expressed genes machine learning...

...Kaichun Li; Qiaoyun Wang; Yanyan Lu; Xiaorong Pan; Long Liu; Shiyu Cheng; Bingxiang Wu; Zongchang Song; Wei Gao Background: The aim of the present study was to confirm the role of Brachyury in breast cancer and to verify whether four types of machine learning models can use Brachyury expression...

... health and economic systems, with an urgency for available therapeutic options. In this scenario, as drug repurposing and discovery remains a challenge, computer-aided drug design (CADD) approaches, including machine learning (ML) techniques, can be useful tools to the design and discovery of novel...

... Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed in the DAVID dataset. Using machine learning, the optimal diagnostic mRNA biomarkers for CC were identified. We used qRT-PCR and Human Protein Atlas (HPA) database to exhibit the differences in gene and protein levels...