The front page of AI-driven biology
Thursday, October 15, 2026Thu, Oct 15
Updated 6:32 PM PT
The FDA has approved Elevar Therapeutics' targeted therapy Lyrfigtu for the treatment of bile duct cancer, also known as cholangiocarcinoma.
Acadia Pharmaceuticals said its Phase 2 Radiant trial evaluating remlifanserin in patients with Alzheimer's psychosis missed its primary endpoint with a p-value of 0.0603.
Merck announced that its experimental therapy met the primary endpoint in a mid- to late-stage trial evaluating adult patients with vascular eye disease affecting the retina.
Researchers have developed UpTCR, a progressive transfer-learning model designed to predict whether T-cell receptors will bind specific peptide targets presented by human leukocyte antigen molecules.
Researchers designed DePass, a graph learning framework that combines paired single-cell and spatial multi-omics data using an iterative denoising process.
Researchers developed a machine-learning method that generates target preference maps to estimate protein binding compatibility directly from native crystal structures.
Researchers created CMAC, a machine-learning framework that estimates the absolute developmental age of heart muscle cells (cardiomyocytes) from single-cell RNA-sequencing data.
DualTopoDDI is a dual-topology graph neural network designed to predict adverse drug-drug interactions and identify the underlying chemical groups responsible.
Researchers introduced ColBERT-PPI, a computational framework that pairs protein-protein partner retrieval with residue-level binding-site mapping using structure-aware multi-vector representations.
A team developed Cell-Lens, a training-free framework that structures single-cell data into typed blocks containing paired measurements and marker programs rather than simple ranked gene lists.
Researchers built an autonomous language-model agent that carries out hit-to-lead molecular optimization by combining literature retrieval, molecular property estimators, docking simulations, and iterative feedback from previously scored analogs.
CAMP-14-3-3 is a computational framework that predicts binding sites on 14-3-3 proteins, which regulate cellular signaling by docking to phosphorylated serine and threonine residues.
A team led by Tsinghua University introduced MicroGlot, a genomic language model pretrained on 378.3 billion nucleotides across 99,700 microbial species.
Researchers built an open resource of 2,986 metaphase fluorescence microscopy image sets with manual annotations to automate the measurement of extrachromosomal DNA, which are circular DNA fragments that drive tumor diversity and drug resistance.
A machine-learning model called PanPhage combines gene content from both bacteria and bacteriophages to predict whether a given virus can kill clinical strains of Escherichia coli.
Researchers trained a transformer neural network named ASOFormer on more than 170,000 antisense oligonucleotide target pairs to predict gene knockdown efficiency directly from RNA sequence, secondary structure, and synthetic chemical modifications.
Researchers have built Cerebra-Epistasis, a computational tool that combines single-sequence 3D protein structure prediction with an epistasis model to forecast how combinations of multiple mutations alter protein function.
Computational biologists paired elastic network models, which treat connected parts of a protein like tiny springs, with simplified Brownian dynamics simulations to map protein flexibility at a fraction of standard computing costs.
Researchers built ProFinder, a computational tool designed to identify reliable constitutive promoters, the DNA control switches that keep genes switched on, in unstudied bacterial species.
Researchers have developed Brain Landscape In Situ Crosslinking Mass Spectrometry, or BLIS-XL-MS, to profile proteome-wide protein conformational shifts and complex remodeling directly in intact brain tissue.
A computational workflow predicts how effectively bacterial beta-lactamase resistance enzymes degrade carbapenem antibiotics using only the enzyme's sequence as input.
Researchers have developed PepSpace, a computational platform that pairs coarse-grained molecular dynamics simulations with a genetic algorithm to design peptide binders from scratch.
Researchers fine-tuned large language models on a small clinical corpus to create Dementia Language Models that generate realistic narratives reflecting cognitive impairment.
Archival duodenal biopsies classified as having no pathologic abnormality show significant clinical and gene expression variations depending on whether a child has inflammatory disease elsewhere in the digestive tract.