Alex Bisberg

TL;DR: The HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks, used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model to score networks.

TL;DR: It is found that patients that are classified as resistant to therapy are harder to predict than responsive patients across the 31 models submitted to the AML-OPC, and which signaling proteins were useful in predicting patient therapeutic response are identified.

TL;DR: This work proposes SCOPE, a framework that uses grid search cross-validation to select optimal parameters for Elo based on accuracy, calibration, or log loss and demonstrates comparable performance to other more complex, state-of-the-art methods.

TL;DR: This work develops a framework to reveal the patterns of generosity in such social environments and provides empirical evidence of social contagion and contagious generosity and finds that players who experience generosity first-hand or even observe other players conduct generous acts become more generous themselves in the future.

TL;DR: Biowheel enables researchers to quickly detect data outliers, evaluate data consistency, and discover mixed trends, and opens the door to easier, faster and better high-dimensional data interpretation for biomedical professionals with and without programming training.