Looking at Cerebellar Malformations through Text-Mined Interactomes of Mice and Humans

WE HAVE GENERATED AND MADE PUBLICLY AVAILABLE TWO VERY LARGE NETWORKS OF MOLECULAR INTERACTIONS: 49,493 mouse-specific and 52,518 human-specific interactions. These networks were generated through automated analysis of 368,331 full-text research articles and 8,039,972 article abstracts from the PubMed database, using the GeneWays system. Our networks cover a wide spectrum of molecular interactions, such as bind, phosphorylate, glycosylate, and activate; 207 of these interaction types occur more than 1,000 times in our unfiltered, multi-species data set. Because mouse and human genes are linked through an orthological relationship, human and mouse networks are amenable to straightforward, joint computational analysis. Using our newly generated networks and known associations between mouse genes and cerebellar malformation phenotypes, we predicted a number of new associations between genes and five cerebellar phenotypes (small cerebellum, absent cerebellum, cerebellar degeneration, abnormal foliation, and abnormal vermis). Using a battery of statistical tests, we showed that genes that are associated with cerebellar phenotypes tend to form compact network clusters. Further, we observed that cerebellar malformation phenotypes tend to be associated with highly connected genes. This tendency was stronger for developmental phenotypes and weaker for cerebellar degeneration

Biomechanics of Locomotion during Ground Translation Perturbations Dataset

The currently published data set includes the data used in the Leestma et al., Journal of Experimental Biology (2023) paper. Additional data that we collected that was not used in this paper will be added at a future date after we conclude data processing. For more information about the contents of the current data set and what will be added in the future, please see the included README file.Supplemental data for the manuscript: J. K. Leestma, P. R. Golyski, C. R. Smith, G. S. Sawicki, and A. J. Young, “Linking whole-body angular momentum and step placement during perturbed walking”, Journal of Experimental Biology. https://doi.org/10.1242/jeb.244760The purpose of this data set is to enable the investigation of human balance and recovery strategies during perturbed walking. We performed a study where participants walked while being exposed to ground translation perturbations. We varied the magnitude, direction, and onset time of these perturbations while collecting various biomechanical outcome metrics.National Science Foundation Graduate Research Fellowship Award #1324585, National Science Foundation Research Traineeship Award #1545287, Georgia Tech Petit Undergraduate Research Scholars Progra