Latest AI and machine learning research in autism for healthcare professionals.
Accurately capturing genetic ancestry is critical for ensuring reproducibility and fairness in genomic studies and downstream health research. This study aims to address the prediction of ancestry from genetic data using deep learning, with a focus on generalizability across datasets with diverse populations and on explainability to improve model transparency. We adapt the Diet Network, a deep lea...
Since Alzheimer’s disease (AD) is a heterogeneous disease, different subtypes may have distinct biological, genetic, and clinical characteristics, requiring tailored interventions. While several proposed subtypes of AD exist, there is still no clear consensus on a definitive classification. By leveraging complementary AI approaches, including supervised and unsupervised learning, within a recursiv...
The genetic tractability, well-mapped circuitry, and diverse behavioral repertoire of the nematode C. elegans make it an ideal model for physiological...
Although developmental language delays affect approximately 10% of children in the general population, the neurodevelopmental mechanisms that support ...
Ensemble of multiple genomic prediction models have grown in popularity due to consistent prediction performance improvements in crop breeding. Howeve...
Advancements in whole genome sequencing have increased the number of variants of uncertain significance (VUS) identified in patient genomes. This has ...
Recent genome-wide association studies (GWAS) have effectively linked genetic variants to quantitative traits derived from time-series cardiac magneti...
Plant phenotyping systematically quantifies plant traits such as growth, morphology, physiology, or yield, assessing genetic and environmental influen...
Overfishing has severely depleted marine populations worldwide, including within protected areas. Illegal and unreported fishing are major contributor...
Studies of human sociability indicate stronger social affinity in matched-neurotype dyads (e.g., two individuals with autism or two without) compared ...
The human claustrum is a bilateral, thin, irregularly shaped gray matter structure located between the striatum and insula. While previous research de...
In eukaryotes, most genes produce multiple transcript isoforms that diversify the transcriptome and proteome, serving as a key mechanism of functional...
Automated detection of complex animal behavior remains a challenge in neuroscience. Developments in computer vision have greatly advanced automated be...
VCFs are the most widely used data format for encoding genetic variation. By design, standard VCFs do not include data from sites where all individual...
The liver’s microenvironment consists of interconnected vascular, biliary, and neural networks that regulate homeostasis and disease progression. Howe...
In the past decades, a wide suite of design tools for biological systems have been developed, but using these to create biotechnologies that achieve r...
The development of prediction models for phenotypes as functions of genetics and environmental inputs is a long-standing challenge in genetics and pla...
Disease-associated genetic variants occur extensively in noncoding regions like promoters, but current methods focus primarily on single nucleotide va...
Transcriptional regulation is mediated by enhancers, yet how genetic perturbations alter enhancer activity and gene expression remains poorly understo...
Polygenic Risk Scores (PRS) are emerging tools for predicting an individual’s genetic risk for complex diseases. However, their usefulness in clinical...