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CSHL Meetings
@cshlmeetings.bsky.social
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CSHL meetings and conferences: Facilitating the latest ideas in the biological sciences since 1933.
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Reposted by CSHL Meetings
sinamajidian.bsky.social
Second's day concluded by fantastic talk by Cristina Martin Linares on "Minimal reconstruction of SpliceAI using distilled matryoshka sparse autoencoders"

They showed that matryoshka SAEs arxiv.org/abs/2503.17547 improves upon openSpliceAI elifesciences.org/reviewed-preprints/107454. #GI2025
https://arxiv.org/abs/2503.17547 Learning Multi-Level Features with Matryoshka Sparse Autoencoders
November 7, 2025 at 1:08 PM
Reposted by CSHL Meetings
sinamajidian.bsky.social
Nicola De Maio presented "Maximum likelihood phylogenetics at pandemic scales" and discussed the importance of scalable phylogenetics in genomic epidemiology. #GenomeInformatics #GI2025
MAPLE: nature.com/articles/s41588-023-01368-0
a, Left—Fasta representation of an individual SARS-CoV-2 genome consists of sample name followed by the entire ≈ 30 kbp genome sequence. Right—MAPLE format records only the differences between the genome under consideration and a reference; columns represent the variant character observed, the position along the genome and (when necessary) the number of consecutive positions for which the character is observed. b, Left—an example likelihood vector at an internal node of a phylogenetic tree (shown by the narrow blue arrow; only a small portion of the tree is shown); for simplicity, we show only ten genome positions. At each position (rows 1–10), each column contains the likelihood for a specific nucleotide. For rows 1–9, the likelihood is concentrated at only one nucleotide (highlighted in green), while for position 10, we show an example with more uncertainty. Right—MAPLE representation of these node likelihoods. Assuming that the reference sequence at the first nine positions matches the most likely nucleotides in the vector (ATTAAAGGT), then for positions 1–9, the likelihood of nonreference nucleotides is negligible and we represent the likelihoods with a single symbol (R). At position 10, due to non-negligible uncertainty, we explicitly calculate and store the four relative likelihoods. c, Examples of likelihood calculation steps in MAPLE. Red arrows represent the flow of information from the tips to the root of the tree. Left—if two child nodes are in reference state R for a region of the genome (here, positions 1–9), then MAPLE assumes that their parent is also in state R. Right—if at a genome position (here, position 10), two child nodes have likelihoods concentrated at different nucleotides, then for their parent, we explicitly calculate the relative likelihoods of all four nucleotides.
November 7, 2025 at 12:56 PM
Reposted by CSHL Meetings
sinamajidian.bsky.social
The first session is PANGENOMES #GI2025. Alexander Schönhuth is delivering the first talk on "Generating synthetic genotypes using diffusion models"
Paper: academic.oup.com/bioinformati...
Code: github.com/TheMody/Gene...
November 6, 2025 at 12:52 AM