deepBreaks identifies and prioritizes genotype–phenotype associations using machine learning
Scientific Reports
November 2025
Research & Development
Advancing the
science of genomics
Our research team pushes the boundaries of genomic AI, developing novel language models and analytical techniques.
Publications
resLens: Genomic Language Models to Enhance Antibiotic Resistance Gene Detection
bioRxiv
July 2025
seqLens: optimizing language models for genomic predictions
bioRxiv
March 2025
Molecular epidemiology of pregnancy using omics data: advances, success stories, and challenges
Journal of Translational Medicine
January 2024
Omics correlation for efficient network construction
Nature Computational Science
April 2023
Metabolite, protein, and tissue dysfunction associated with COVID-19 disease severity
Scientific Reports
July 2022
Differential expression of single-cell RNA-seq data using Tweedie models
Statistics in Medicine
June 2022
Epidemiological associations with genomic variation in SARS-CoV-2
Scientific Reports
November 2021
Omics community detection using multi-resolution clustering
Bioinformatics
October 2021
Research focus areas
Genomic Language Models
Developing transformer-based models for DNA sequence understanding and analysis.
Metagenomics
Advanced methods for analyzing complex microbial communities and environmental samples.
Antibiotic resistance
Applying genomic language models to study antibiotic resistance genes and their functional associations with drugs.
Microbiome research
Understanding the role of microbial communities in health and disease.
Clinical diagnostics
Translating genomic insights into actionable clinical applications.
AI agents
Intelligent systems that combine LLMs with domain-specific genomic knowledge.