ArticleAdvances in neural information processing systems2024
Ultrafast classical phylogenetic method beats large protein language models on variant effect prediction.
Article in Advances in neural information processing systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Article
- Nested birth-death processes are competitive with parameter-heavy neural networks as time-dependent models of protein evolution.bioRxiv : the preprint server for biology · 2026Article
- Deep models of protein evolution in time generate realistic evolutionary trajectories and functional proteins.bioRxiv : the preprint server for biology · 2026Article
- Protein Language Models: Applications and Perspectives.Journal of proteome research · 2026Review
- ConvexML: Fast and Accurate Branch Length Estimation under Irreversible Mutation Models, Illustrated through Applications to CRISPR/Cas9-Based Lineage Tracing.Systematic biology · 2026Article
- ConvexML: Fast and accurate branch length estimation under irreversible mutation models, illustrated through applications to CRISPR/Cas9-based lineage tracing.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Amino acid substitution rate matrices are fundamental to statistical phylogenetics and evolutionary biology. Estimating them typically requires reconstructed trees for massive amounts of aligned proteins, which poses a major computational bottleneck. In this paper, we develop a near-linear time method to estimate these rate matrices from multiple sequence alignments (MSAs) alone, thereby speeding up computation by orders of magnitude. Our method relies on a near-linear time cherry reconstruction algorithm which we call
Identifiers
40487750PMC12143485What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.