AstraZeneca blames trial design after Phase 3 hypophosphatasia study misses endpoint
AstraZeneca attributed the failure of its Phase 3 HICKORY trial for efzimfotase alfa to an imbalanced adult subgroup.
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Vision foundation model adapted to trace cell membranes in noisy cryo-ET volumes
Researchers have adapted a video-segmentation foundation model, named ETSAM, to accurately map cell membranes within noisy 3D cryo-electron tomograms.
Deep learning extends live-cell super-resolution microscopy duration and speed
Researchers combined two deep-learning approaches to overcome light-induced damage and slow acquisition in RESOLFT super-resolution microscopy.
Preprints
Single-cell pipeline infers gene regulatory networks and cell types simultaneously
Computational biologists introduced NetMap, a software pipeline that jointly infers single-cell gene regulatory networks and clusters cell populations without needing pre-assigned cell annotations.
Protein language models map membrane interaction surfaces from sequence alone
Researchers developed CHORUS, a deep-learning method that identifies binding interfaces on membrane proteins directly from raw amino acid sequences without requiring three-dimensional structures or evolutionary alignments.
Common AI confidence scores fail to predict whether designed binders hit their targets
Computational binder screening frequently filters candidates by predicted interface confidence, but a benchmark of 196 nanobody loop designs targeting the cancer protein survivin found no correlation between confidence metrics and actual epitope contact (rho = +0.100).
Machine learning scores cell maturity from DNA methylation marks
EpiDiff uses machine learning on DNA methylation data to produce a continuous numerical score of cellular differentiation across single-cell, sorted, and bulk tissue samples.
Multi-stage reasoning model designs catalytic enzymes from chemical reactions
A team led by Scinetics introduced chain-of-structures, a framework that couples language reasoning with structural generative models to design enzymes directly from reaction specifications.
Generative model designs all-atom peptides directly inside binding pockets
Researchers at Tsinghua University built PeTFlow, a generative flow-matching model that designs binding peptides directly within three-dimensional protein pockets.
Tool shrinks microbiome protein databases using direct peptide predictions
FastaLake uses AlphaNovo de novo peptide predictions to retrieve complete microbial proteins from large catalogs, generating sample-specific search spaces that match or outperform traditional metagenomic databases.
Autonomous AI agents mine metagenomic data to discover new viral enzyme families
Researchers deployed autonomous instances of Claude Code to search 1.9 billion protein clusters for reverse transcriptases, identifying a new class of giant-virus enzymes dubbed array-associated RTs.
Protein design model combines ligand contacts and evolution to boost enzyme activity
A graph neural network called zPolaron designs functional proteins by modeling interactions between protein backbones and bound ligands alongside evolutionary patterns from ESM-2.
Neural network links cancer mutations directly to shifts in DNA chemical marks
A machine learning tool called unduliner uses long-read sequencing data to connect specific somatic mutations with local changes in DNA methylation patterns.
Benchmark overhaul shows simple algorithms beat deep learning in picking gene perturbation targets
A new evaluation framework named Cause-excluded Effect Evaluation exposes that previous single-cell target discovery benchmarks were inflated by data leakage and by leaking the target gene's own expression.
Updated AI model predicts full RNA transcripts and pinpoints disease-causing splicing errors
Researchers have introduced SpliceAI2, a deep learning model trained across multiple mammalian species that reconstructs full-length transcripts directly from DNA sequences.
Massive cellular screen maps half a million mutations across cancer signaling pathway
Scientists measured the functional impact of 186,676 protein variants across 17 enzymes in the RAS-MAPK signaling cascade, generating 503,099 total cellular readouts.
AI transfer model maps noncoding variant effects across developing human brain regions
Seal, a new transfer-learning framework, predicts spatiotemporal gene regulation and variant impacts across 26 brain regions, 30 cell types, and seven human developmental stages.
Single-cell droplet method tracks blood stem cell clones using DNA methylation
Researchers developed Droplet-MT, a microfluidic method that profiles the transcriptome and DNA methylation together across roughly 10,000 single cells per run.