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The authors investigate the ability of machine learning models to developing new drug-like molecules by learning desired chemical properties versus simply generating molecules that similar to those in the training set.

Major Depressive Disorder (MDD), and Post-Traumatic Stress Disorder (PTSD) are two of the fastest growing comorbid diseases in the world. Using publicly available datasets from the National Institute for Biotechnology Information (NCBI), Ravi and Lee conducted a differential gene expression analysis using 184 blood samples from either control individuals or individuals with comorbid MDD and PTSD. As a result, the authors identified 253 highly differentially-expressed genes, with enrichment for proteins in the gene ontology group 'Ribosomal Pathway'. These genes may be used as blood-based biomarkers for susceptibility to MDD or PTSD, and to tailor treatments within a personalized medicine regime.

In this study, the authors investigate the demographic indicators for voter shift between the 2016 and 2020 presidential elections based on demographic data put through a K-nearest neighbors classification algorithm and Principal Component Analysis.