Projects
1 Pairwise alignment Link to heading
A*PA Link to heading
A pairwise aligner based on A*, in collaboration with Pesho Ivanov. A*PA uses A* with new heuristics to speed up global pairwise alignment. A*PA2 is much faster by using a DP-based method.
- Code, slides
- A*PA paper: PDF, bioRxiv, Bioinformatics (supplement separate)
- A*PA2 paper: PDF, (outdated) bioRxiv, WABI/LIPIcs
- Talk at CWI: 60 min recording, but unfortunately it does not show the blackboard well.
- Blogposts
- Pairwise alignment history
- Computational volumes
- A*PA2, the blogpost version of the paper.
- Local doubling, an idea that didn’t make it into the final paper.
PA-Bench Link to heading
PA-Bench is a benchmarking framework for pairwise aligners, in collaboration with Daniel Liu.
2 Minimizers Link to heading
Open-closed mod-minimizer Link to heading
A minimizer scheme with near-optimal density when \(k\gg w\) and good density when \(k<w\), in collaboration with Giulio Ermanno Pibiri and Daniel Liu.
- Blogpost, Rust code, C++ code
- WABI24 Paper: PDF, bioRxiv, WABI/LIPIcs, slides
- Extended paper: The open-closed mod-minimizer: PDF, bioRxiv
Density lower bound Link to heading
A near-tight lower bound for the density of forward sampling schemes, in collaboration with Bryce Kille.
- Blogpost, slides
- Paper: PDF, bioRxiv, Bioinformatics
- Code: minimizer implementations, ILP & analysis
Practical schemes for small \(k\) Link to heading
While the mod-minimizer is practical and near-optimal for large \(k\), the best schemes for small \(k\) are somewhat slow to compute. Here the goal is to develop a simple and near-optimal schemes.
3 High throughput bioinformatics Link to heading
PTRHash Link to heading
Fast and small minimal perfect hash function:
Fast random minimizers Link to heading
A 10x faster implementation of random minimizers.
- Blogpost, code,
- 90min invited talk at Johns Hopkins going over the post above, with the last 15min on low density minimizers.
One Billion Row Challenge Link to heading
While not bioinformatics, this is a popular post: