Our research group develops bioinformatics methods for analyzing molecular high-throughput data in the context of diabetes research. We address computational challenges arising from large-scale and heterogeneous data, integrating multi-omics and clinical datasets to improve our understanding of metabolic dysfunctions and their relationship with cardiovascular diseases. We develop pangenome-based approaches to study disease-related genetic variations, particularly in complex loci relevant to diabetes. Our work also extends to modeling epigenetic gene regulation and investigating structural genomic variations to reconstruct mutation histories.
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- ml_helpers Public
codialab/ml_helpers’s past year of commit activity - HySim Public
Simulation pipeline simulating short single cell (10x Chromium) and long bulk (PacBio) reads from the same data
codialab/HySim’s past year of commit activity - trim-graph Public
Simple tool to remove segments and links from GFA files that are not covered by paths
codialab/trim-graph’s past year of commit activity - GFAffix Public
GFAffix identifies walk-preserving shared affixes in variation graphs and collapses them into a non-redundant graph structure.
codialab/GFAffix’s past year of commit activity - .github Public
codialab/.github’s past year of commit activity
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