Joint exome and metabolome analysis in individuals with dyslexia: Evidence for associated dysregulations of olfactory perception and autoimmune functions.

Dyslexia is a learning disability that negatively affects reading, writing, and spelling development at the word level in 5%-9% of children. The phenotype is variable and complex, involving several potential cognitive and physical concomitants such as sensory dysregulation and immunodeficiencies. The biological pathogenesis is not well-understood.

A data-fusion approach to identifying developmental dyslexia from multi-omics datasets.

This exploratory study tested and validated the use of data fusion and machine learning techniques to probe high-throughput omics and clinical data with a goal of exploring the etiology of developmental dyslexia. Developmental dyslexia is the leading learning disability in school aged children affecting roughly 5-10% of the US population. The complex biological and neurological phenotype of this life altering disability complicates its diagnosis.

Conspecific Identity Determines Interactive Space Area in Zebrafish Shoal.

Sex ratio of shoals has been shown to influence shoaling behavior in many fishes. This study tests whether the conspecific identity influences shoal performance (shoal area, interactive distances, distance traveled, and thigmotaxis) of zebrafish () via group tracking. We conducted a two-dimensional analysis of shoals with different sex ratios (male only, female only, male rich, and female rich) of a five-membered shoal.

Developing a machine learning model to identify protein-protein interaction hotspots to facilitate drug discovery.

Throughout the history of drug discovery, an enzymatic-based approach for identifying new drug molecules has been primarily utilized. Recently, protein-protein interfaces that can be disrupted to identify small molecules that could be viable targets for certain diseases, such as cancer and the human immunodeficiency virus, have been identified. Existing studies computationally identify hotspots on these interfaces, with most models attaining accuracies of ~70%.