Spartan Daily, January 23, 1946

Volume 34, Issue 38https://scholarworks.sjsu.edu/spartandaily/3695/thumbnail.jp

Using EuGeneCiD and EuGeneCiM computational tools for synthetic biology

Synthetic biology often relies on the design of genetic circuits, utilizing ‘‘bio parts’’ (modular DNA pieces) to accomplish desired responses to external stimuli. While such designs are usually intuited, detailed here is a computational approach to synthetic biology design and modeling using optimization-based tools named Eukaryotic Genetic Circuit Design and Modeling. These allow for designing and subsequent screening of genetic circuits to increase the chances of in vivo success and contribute to the development of an application development pipeline. For complete details on the use and execution of this protocol, please refer to Schroeder, Baber, and Saha (2021)

Spartan Daily, May 31, 1968

Volume 55, Issue 136https://scholarworks.sjsu.edu/spartandaily/5135/thumbnail.jp

Diagnostic biomarkers identification of arthritis in Type 2 diabetic patients, using Artificial Intelligence classification techniques applied in Real World Data database based in GEO microarrays

Ddatabases and repositories, including microarray data, are important sources of information that can be exploited to understand biological processes that in some cases could be initially identified as unrelated, such are diabetes and arthritis. The use of Machine Learning approaches is essential to extract patterns that could help to identify biological reasons to link phenotypes unrelated. During this project, a set of diabetes samples obtained from the GEO database were analysed to compare patients with and without arthritis. The analysis was developed to identify common/uncommon patterns to help us determine biological factors associated to suffer arthritis by diabetic patients. The classifiers obtained in a 10-fold cross-validation optimized for balanced accuracy > 80% were IL-18, TNFRSF1A, SPP1, CXCL8 and IL-10; which the novel potential of the SPP1 protein as a new biomarker was highlighted due to its lack of previous reports in the scientific literature