Network medicine is an emerging area of research dealing with molecular and genetic
interactions, network biomarkers of disease, and therapeutic target discovery. Large-scale …

Heterogeneity is a pervasive feature of cancer, and understanding the sources and
regulatory mechanisms underlying heterogeneity could provide key insights to help improve …

Gene set enrichment is a mainstay of functional genomics, but it relies on gene function
databases that are incomplete. Here we evaluate five large language models (LLMs) for …

Millions of Americans are affected by rare diseases, many of which have poor survival rates.
However, the small market size of individual rare diseases, combined with the time and …

Motivation Clustering patient omic data is integral to develo** precision medicine because
it allows the identification of disease subtypes. A current major challenge is the integration …

Single cell technologies are rapidly generating large amounts of data that enables us to
understand biological systems at single-cell resolution. However, joint analysis of datasets …

The GNAS R201 gain-of-function mutation is the single most frequent cancer-causing
mutation across all heterotrimeric G proteins, driving oncogenesis in various low …

Background Cancer is a somatic evolutionary disease and adenocarcinomas of the stomach
and gastroesophageal junction (GC) may serve as a two-dimensional model of cancer …

The complex interactions in biological systems have been shown to affect the response to
single-targeted therapies which were initially developed under the “reductionist paradigm” of …

Thousands of genes are perturbed by cancer, and these disturbances can be seen in
transcriptome, methylation, somatic mutation, and copy number variation omics studies …