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- research-articleJuly 2024
In-silico screening and identification of glycomimetic as potential human sodium-glucose co-transporter 2 inhibitor
Computational Biology and Chemistry (COBC), Volume 110, Issue Chttps://doi.org/10.1016/j.compbiolchem.2024.108074AbstractSodium-glucose co-transporter 2 (SGLT2) is one of the important targets against type II diabetes mellitus. A typical SGLT2 inhibitor acts by inhibiting glucose reabsorption, thus lowering the blood glucose level. Unlike SGLT1, SGLT2 is ...
Graphical AbstractDisplay Omitted
Highlights- SGLT2, crucial for type II diabetes and key target in drug design.
- Present work used ligand-based and structure-based methods for compound discovery.
- 3D-QSAR screens 10 thousand compounds; docking studies performed for inhibitors.
- research-articleMarch 2023
A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative
- Elena Casiraghi,
- ,
- Rachel Wong,
- Margaret Hall,
- Ben Coleman,
- Marco Notaro,
- Michael D. Evans,
- Jena S. Tronieri,
- Hannah Blau,
- Bryan Laraway,
- Tiffany J. Callahan,
- Lauren E. Chan,
- Carolyn T. Bramante,
- John B. Buse,
- Richard A. Moffitt,
- Til Stürmer,
- Steven G. Johnson,
- Yu Raymond Shao,
- Justin Reese,
- Peter N. Robinson,
- Alberto Paccanaro,
- Giorgio Valentini,
- Jared D. Huling,
- Kenneth J. Wilkins
Journal of Biomedical Informatics (JOBI), Volume 139, Issue Chttps://doi.org/10.1016/j.jbi.2023.104295Graphical abstractDisplay Omitted
AbstractHealthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients’ predictors and outcomes of interest. However, these datasets often suffer from missing values in a high ...
- research-articleMay 2022
Predicting pharmacotherapeutic outcomes for type 2 diabetes: An evaluation of three approaches to leveraging electronic health record data from multiple sources
- Shinji Tarumi,
- Wataru Takeuchi,
- Rong Qi,
- Xia Ning,
- Laura Ruppert,
- Hideyuki Ban,
- Daniel H. Robertson,
- Titus Schleyer,
- Kensaku Kawamoto
Journal of Biomedical Informatics (JOBI), Volume 129, Issue Chttps://doi.org/10.1016/j.jbi.2022.104001Graphical abstractDisplay Omitted
Highlights- Three methods for building predictive models from multicenter electronic health record data are compared for clinical decision support in type 2 diabetes ...
Electronic health record (EHR) data are increasingly used to develop prediction models to support clinical care, including the care of patients with common chronic conditions. A key challenge for individual healthcare systems in ...