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The last talk of #WABI25 😲! Jannik Schestag presents "Average-Tree Phylogenetic Diversity of Networks".

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Last session of #WABI25 kicks off with "Which Phylogenetic Networks are Level-k Networks with Additional Arcs? Structure and Algorithms" presented by Takatora Suzuki.

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Mateo Gray tells us about the latest and greatest in RNA energy minimization in "Spark: sparsified hierarchical energy minimization of RNA pseudoknots" #WABI25!

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First talk of the last day of #WABI25 "Identifying Breakpoint Median Genomes: A Branching Algorithm Approach" presented by Arash Jamshidpey!

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"Graph-Based Extension of Partial Atom Maps: Theoretical Uniqueness and Practical Algorithms" being presented by Marcos E. González Laffitte at #WABI25. A topic quite different from many of the others in the conference, but nonetheless very interesting!

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John Bridgers is presenting "Improved Algorithms for Bi-partition Function Computation", continuing our theme of cancer phylogenomics at #WABI25.

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Daniel Feng presenting "Dolphyin: A Combinatorial Algorithm for Identifying 1-Dollo Phylogenies in Cancer" as the second talk of the afternoon session at #WABI25

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"Mutational signature refitting on sparse pan-cancer data" being presented by Gal Gilad at #WABI25!

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Ryosuke Yamano tells us about "Linear-space Subquadratic-time String Alignment Algorithm for Arbitrary Scoring Matrices" - his first publication and first conference talk! #WABI25

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"Approximability of Longest Run Subsequence and Complementary Minimization Problems" being presented by Eiji Miyano at #WABI25

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Now we are hearing about "Sequence similarity estimation by random subsequence sketching" from Ke Chen at #WABI25

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Our second remote talk of #WABI25, "Design of Worst-Case-Optimal Spaced Seeds", being presented by Jens Zentgraf!

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Wow, fantastic room: haven't seen so many screen for a single presentation at a CS conference! ☺️ @ale-campa.bsky.social has been doing some amazing development on the Fulgor index. Soon enough, more exciting news. Stay tuned! ⚡ 🧬 #WABI25

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A solution to the indexing dilemma in large pangenomes, by Parsa Eskandar from UCSC: Lossless Pangenome Indexing Using Tag Arrays", offering a practical indexing layer to develop scalable aligners and downstream graph-based tools
www.biorxiv.org/content/10.1...
#wabi25

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Last talk of the day (before posters) "Lossless Pangenome Indexing Using Tag Arrays" presented by Parsa Eskandar! #WABI25

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My collaborator (whom I just met in person today) and @jermp.bsky.social's student, @ale-campa.bsky.social presenting "Fast pseudoalignment queries on compressed colored de Bruijn graphs"! #WABI25

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"K-mer-based estimators of the substitution rate of repetitive sequences" presented by Haonan Wu at #WABI25!

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"Estimation of substitution and indel rates via k-mer statistics" presented by Mahmudur Rahman Hera at #WABI25, estimate mutations, deletion and insertion rates from k-mers!

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"Human readable compression of GFA paths using grammar-based code" being presented by Peter Heringer at #WABI25

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Daniel Gibney tells us about "Haplotype-aware long-read error correction" #WABI25

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Ali Ghaffaari introduces "DiVerG: A Scalable Distance Index for Validation of Paires-End Alignments in Sequence Graphs" #WABI25

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Anchor-based merging requires a common sequence (red) present in each partition. Multi-MUMs are merged by identifying overlaps between partition-specific matches in the anchor coordinate space, and a uniqueness threshold determines if a MUM is still unique in each partition after truncation. (B) String-based merging enables computation of multi-MUMs between partitions without a common sequence. An example tree (left) is shown, highlighting the use case where partial multi-MUMs specific to internal nodes (starred) can be computed by merging subclade- based partitions up a tree. (right) MUM overlaps are computed by running Mumemto on the MUM sequences, and the uniqueness threshold array ensures overlaps remain unique across the merged dataset. (C) An example Burrows-Wheeler Transform (BWT), matrix (BWM), and Longest Common Prefix (LCP) array, with sequence IDs for each suffix shown (ID). A non-maximal unique match (UM) is shown, and the uniqueness threshold for this match is found using the flanking LCP values. (D) A partial multi-MUM (in blue) is found in all-but-one sequence (excluded in red). Using two anchor sequences (red and orange), all-but-one partial MUMs can be computed using an augmented anchor-based merging method.

Anchor-based merging requires a common sequence (red) present in each partition. Multi-MUMs are merged by identifying overlaps between partition-specific matches in the anchor coordinate space, and a uniqueness threshold determines if a MUM is still unique in each partition after truncation. (B) String-based merging enables computation of multi-MUMs between partitions without a common sequence. An example tree (left) is shown, highlighting the use case where partial multi-MUMs specific to internal nodes (starred) can be computed by merging subclade- based partitions up a tree. (right) MUM overlaps are computed by running Mumemto on the MUM sequences, and the uniqueness threshold array ensures overlaps remain unique across the merged dataset. (C) An example Burrows-Wheeler Transform (BWT), matrix (BWM), and Longest Common Prefix (LCP) array, with sequence IDs for each suffix shown (ID). A non-maximal unique match (UM) is shown, and the uniqueness threshold for this match is found using the flanking LCP values. (D) A partial multi-MUM (in blue) is found in all-but-one sequence (excluded in red). Using two anchor sequences (red and orange), all-but-one partial MUMs can be computed using an augmented anchor-based merging method.

Post image (A) Phylogeny of geographically diverse A. thaliana accessions (Lian et al. 2024), with broad geographical regions colored. Internal nodes are labeled with the coverage of partial multi-MUMs across the leaves of each node. Internal node partial MUMs are computed by merging subtree-based partitions progressively up the phylogeny. (B) Global multi-MUM synteny across the full dataset shown in blue (with inversions in green). Global MUMs are computed by merging all partitions together (representing the root node). Additionally, three geographically distinct subgroups are highlighted and partition-specific multi-MUMs (in purple, with inversions in pink) reveal local structural variation in centromeric regions.

(A) Phylogeny of geographically diverse A. thaliana accessions (Lian et al. 2024), with broad geographical regions colored. Internal nodes are labeled with the coverage of partial multi-MUMs across the leaves of each node. Internal node partial MUMs are computed by merging subtree-based partitions progressively up the phylogeny. (B) Global multi-MUM synteny across the full dataset shown in blue (with inversions in green). Global MUMs are computed by merging all partitions together (representing the root node). Additionally, three geographically distinct subgroups are highlighted and partition-specific multi-MUMs (in purple, with inversions in pink) reveal local structural variation in centromeric regions.

Great talk by Vikram @vikramshivakumar.bsky.social on studying pangenomes and synteny visualization in #WABI25
Github: github.com/vikshiv/mume...
First paper: genomebiology.biomedcentral.com/articles/10....
Second: www.biorxiv.org/content/10.1... #WABI2025

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Vikram Shivakumar telling us about "Partitioned Multi-MUM finding for scalable pangenomics" #WABI25! So many kinds of matches!

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#WABI25 Ahsan Sanaullah discussing "An Efficient Data Structure and Algorithm for Long-Match Query in Run-Length Compressed BWT".

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#WABI25 wheeler graph and related videos and resources from Ben!

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#WABI25 HAS KICKED OFF! @benlangmead.bsky.social is givening the opening keynote now wabiconf.github.io/2025/talks/t...

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WABI 2025 WABI Conference on Algorithms in Bioinformatics

The 25th iteration of the excellent Conference for Algorithms in Bioinformatics (WABI) starts tomorrow at UMD @umdscience.bsky.social at the Brendan Iribe Center. You can find details at the website wabiconf.github.io/2025/. We'll use the tag #WABI25 for the meeting!

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