The discovery of superior molecular solutions through computational methods is critical for
innovative technologies and their role in addressing pressing resources, health, and …

Functional gene embeddings, numerical vectors capturing gene function, provide a
promising way to integrate functional gene information into machine learning models. These …

Motivation Genomic region sets summarize functional genomics data and define locations of
interest in the genome such as regulatory regions or transcription factor binding sites. The …

Since its establishment in 2015, the transcriptomics-based consensus molecular subtype
(CMS) classification has unified our understanding of colorectal cancer. Each of the four …

The vast and complex landscape of chemical space has traditionally been explored through
a combination of experimentation and knowledge-based computational approaches …

Gene marker extraction to evaluate risk in cancer can refine the diagnosis process and lead
to adapted therapies and better survival. These survival analyses can be done through …

Motivation: Genomic region sets summarize functional genomics data and define locations
of interest in the genome such as regulatory regions or transcription factor binding sites. The …