Rob and his work are unique gifts for our field. I'm glad our paths crossed!
This is now published in Genome Research (doi.org/10.1101/gr.2...). Thank you everyone for your feedback and also the anonymous reviewers who helped to greatly improve the paper. I hope this becomes a useful resource for the community.
Really proud of @ale-campa.bsky.social for his amazing contributions to the Fulgor ⚡ index! I'm very excited for what's next 🙂 CC @robp.bsky.social @zaminiqbal.bsky.social
C++ code is here github.com/jermp/sshash and also available via Bioconda bioconda.github.io/recipes/ssha.... Rust code is here instead github.com/COMBINE-lab/... (thank you again @robp.bsky.social!)
🔍 New paper in Bioinformatics Advances: "Kaminari: A frugal colored index for approximate k-mer queries"
Read it here: https://doi.org/10.1093/bioadv/vbag120
Authors include: @yhhshb.bsky.social, @yoann.bsky.social, @robp.bsky.social, @pierrepeterlongo.bsky.social, @jermp.bsky.social
Wow! What a tool: half million downloads from Bioconda - Congrats @robp.bsky.social and Combine-Lab! 👏 Happy to see SSHash plugged here.
I made this sculpture (clay and acrylic paints) for my mother’s birthday present 🎂 Artistic expression has always been part of my life, besides science.
📖 🧬 SSHash is a compressed, associative, exact, and weighted dictionary for k-mers. - jermp/sshash
📢 We are thrilled to announce the keynote speakers for #RECOMB2026:
🧬 Sara Mostafavi
🧬 Manolis Kellis
🧬 Paul Medvedev
🧬 Alexandros Stamatakis
Join us in Thessaloniki for inspiring talks from leaders in computational biology.
Accepted to ISMB'26. Revised paper is here: jermp.github.io/assets/pdf/p.... I'd like to thank @robp.bsky.social once again and all the received feedback from the reviewers. To me, ISMB has had the highest quality review process over the past few years!
Randomness is a powerful tool in the design and analysis of algorithms and data structures for nucleotide sequence data. Nucleotide sequences are not themselves random but are often randomized using hash functions. Despite their widespread use in genomics, there is no comprehensive review of the types of hash functions used and their various applications. In this survey intended for bioinformatic methods developers, we divide hash functions into four categories: scattering hash functions, permutations, minimum perfect hash functions, and locality-sensitive hash functions. For each category, we provide examples of both general-use hash functions that have been applied in nucleotide sequence analysis and hash functions that have been designed specifically for nucleotide sequence analysis. We highlight their salient properties, commonalities, differences, and application areas.
