Latest AI and machine learning research in genetics for healthcare professionals.
Background & Methods: The multifaceted physical nature of heritable cognitive impairment in dementia presents significant challenges for traditional linear frameworks attempting to model synergistic risk. While various loci are identified as contributing to neurocognitive disparities, the emergent phenotypic expression and associated predictive value relative to standard clinical baselines require...
Most disorders caused by a deficiency or excess of one gene product lack targeted therapies. Since these disorders can be modeled with a gene overexpression, knockout, or knockdown, drugs that oppose the transcriptomic effects of such perturbations may be promising therapeutic candidates. RNA-Sequencing (RNA-Seq) studies can fuel this drug-prioritization, but their labels, written in plain languag...
The rapid evolution of image generation has produced numerous within-family variants, making source-model attribution of suspect images increasingly i...
Longitudinal tumor measurements, dropout information, and genetic covariates provide complementary information about treatment response, but integrati...
Next-generation sequencing technologies, including RNA-sequencing, provide genome-wide measurements of gene expression and enable broad explorations o...
Polyploidy, or whole genome duplication, reshapes genomes through biased gene loss and regulatory rewiring, yet the drivers of biased fractionation am...
Primary tumor biopsy in retinoblastoma carries an unacceptable risk of extraocular dissemination. As a result, children treated with eye-sparing appro...
Glycosylation is a fundamental process regulating cellular function, tissue organization, and disease progression. However, comprehensive glycan profi...
DNA language models (DNALMs) aim to learn representations of genomic sequence for variant interpretation, regulatory prediction, and sequence design. ...
Objective. To develop and validate a cell free DNA (cfDNA) fragmentomic classifier for the early prediction of spontaneous preterm birth (PTB) using r...
Since the early adoption of metagenomics (the culture-free sequencing of microbial community genomes) in 2011, sequence data has increased over 500-fo...
Medical Vision-Language Models (VLMs) exhibit strong zero-shot performance, yet their effectiveness still declines on out-of-distribution (OOD) data d...
Recurrent somatic mutations reveal cancer drivers, but in whole genomes many non-coding hotspots are passengers generated by localized mutational proc...
Genomic DNA is wrapped around core histones to form nucleosomes, which are organized in cells from euchromatin to heterochromatin with distinct genome...
The acceleration of automated scientific discovery has been fundamentally bottlenecked by the epistemic gap between the semantic reasoning of large la...
While whole genome sequencing captures millions of single nucleotide polymorphisms (SNPs) and hyperspectral imaging (HSI) enables non destructive plan...
Structural variants are a major source of genomic variation and contribute to human disease and evolution through diverse mechanisms, yet their functi...
The push toward large language models for biology (BioLM) has created a need for training corpora that can endow models with a genuine understanding o...
Geroscience clinical trials need biomarker surrogate endpoints for healthspan. Leading candidates are omics-based composites developed from machine le...
Compact tissue-specific promoters are highly desirable for gene therapy because viral vectors possess limited packaging capacity. However, existing pr...