A5051632368- Computational Drug Discovery Methods
- Machine Learning in Bioinformatics
- Metabolomics and Mass Spectrometry Studies
- Machine Learning in Materials Science
- Microbial Metabolic Engineering and Bioproduction
- Bioinformatics and Genomic Networks
- Protein Structure and Dynamics
- Biosimilars and Bioanalytical Methods
- Crystallization and Solubility Studies
- Gut microbiota and health
- Biomedical Text Mining and Ontologies
- Pharmacogenetics and Drug Metabolism
- Crystallography and molecular interactions
- Tuberculosis Research and Epidemiology
Northwestern Polytechnical University
2022-2025
Abstract Motivation During lead compound optimization, it is crucial to identify pathways where a drug-like metabolized. Recently, machine learning-based methods have achieved inspiring progress predict potential metabolic for compounds. However, they neglect the knowledge that are dependent on each other. Moreover, inadequate elucidate why compounds participate in specific pathways. Results To address these issues, we propose novel Multi-Label Graph Learning framework of Metabolic Pathway...
Many drugs can be metabolized by human microbes; the drug metabolites would significantly alter pharmacological effects and result in low therapeutic efficacy for patients. Hence, it is crucial to identify potential drug–microbe associations (DMAs) before administrations. Nevertheless, traditional DMA determination cannot applied a wide range due tremendous number of microbe species, high costs, fact that time-consuming. Thus, predicting possible DMAs computer technology an essential topic....
Computational modeling and identification of the enzyme turnover number k <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">cat</inf> are crucial for synthetic biology early-stage lead optimization. Therefore, accurate assessment enzyme-substrate pairs is essential. Considering wet-lab experiment time-consuming, laborious, expensive, in silico prediction an alternative choice. However, few computational methods have been developed to address this...