Analyzing and comparing genetic material across different species or populations to identify similarities, differences, and evolutionary relationships.
Studying genetic material recovered directly from environmental samples, such as soil, water, or microbiomes, to understand microbial communities.
Analyzing RNA sequences to assess gene expression, alternative splicing, and other transcriptomic features.
Analyzing genetic data from cancer patients to identify mutations, biomarkers, and therapeutic targets.
Using machine learning algorithms to predict and design effective drug molecules, improving the drug discovery process.
Designing peptides for therapeutic applications, including identifying novel drug candidates.
Using machine learning to predict interactions between proteins, essential for understanding cellular processes.
Analyzing Next-Generation Sequencing (NGS) data for a wide range of applications, including whole-genome sequencing, exome sequencing, and targeted sequencing.
Additional genomic and bioinformatics services, tailored to specific client needs.