Genetics

Robust Random Forests for Genomic Prediction: Challenges and Remedies

Data contamination, from recording errors to extreme outliers, can compromise statistical models by biasing predictions, inflating prediction errors, and, in severe cases, destabilizing performance in high-dimensional settings. Although contamination can affect responses and covariates, we focus on response contamination and evaluate Random Forests through simulation. Using a synthetic animal-bree...

De novo design of RNA pseudoknots with deep learning

RNA design has been hindered by the limited accuracy of 3D structure prediction. Here, we show that intricate RNA structures can be generated with current deep learning tools through accurate de novo design of pseudoknot secondary structures. In an Eterna competition involving 57 pseudoknots, generative AI methods matched experienced human designers in solving most blind challenges, evaluated by s...

Generalist large language models complement tailor-made predictors for tumor genomics interpretation

General-purpose large language models (LLMs) are trained on large corpora to acquire broad knowledge, but whether LLMs can replace, or augment, task-s...

Seizure-Semiology-Suite (S3): A Clinically Multimodal Dataset, Benchmark, and Models for Seizure Semiology Understanding

While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in general video understanding, their capacity to interpret in...

Rethinking Token Reduction for Diffusion Models via Output-Similarity-Awareness

Diffusion Transformers (DiTs) achieve superior image generation quality but suffer from quadratic computational complexity relative to token count. Wh...

Q-PhotoNAS: Hybrid Quantum Neural Architecture Search Framework on Photonic Devices

Photonic quantum computing is a promising platform for scalable quantum machine learning, but designing effective hybrid architectures remains challen...

VEELA: A Clinically-Constrained Benchmark for Liver Vessel Segmentation in Computed Tomography Angiography

Accurate segmentation of hepatic and portal vessels in contrast-enhanced computed tomography angiography (CTA) remains challenging due to complex vasc...

Rethinking Noise-Robust Training for Frozen Vision Foundation Models: A Cross-Dataset Benchmark with a Case Study of Small-Loss Failure

Frozen Vision Foundation Models (VFMs) with lightweight classification heads are increasingly used in medical imaging because they offer efficient and...

Artificial intelligence-driven precision medicine identifies prognostic WNT pathway alterations in AA colorectal cancer patients treated with FOLFOX

Background: African Americans (AA) experience disproportionate burden of colorectal cancer (CRC). Dysregulation of the Wingless-related integration si...

scDeepVariant: A population-informed deep learning framework for germline variant calling in scRNA-seq

Single-cell RNA sequencing (scRNA-seq) provides unprecedented resolution of cellular heterogeneity while also capturing information on germline geneti...

AI-assisted improvement of Aspergillus oryzae β-galactosidase using an Ensemble of Protein Language Models

{beta}-galactosidases (BGs) are essential enzymes widely used in the food industry, particularly in the production of lactose-free products. Among the...

BioRAG-DRAG: A Multimodal Biological Retrieval Layer for Local-First Biomedical Agents

Biomedical agents need reliable access to heterogeneous evidence: literature text, gene and pathway records, protein sequences, DNA/cDNA sequences, an...

geneML: Gene annotation across diverse fungal species using deep learning

Accurate gene prediction remains a major bottleneck in fungal genomics, where lineage diversity and alternative splicing challenge existing ab initio ...

DeepBioGS: a hybrid framework for integrating crop growth modelling with genomic prediction through neural networks

Ensuring global food security under rapid climate change demands accelerated genetic gain and breeding strategies that address complex Genotype-by-Env...

Non-invasive Transcriptomic Cell Profiling of the Human Endometrium with Generative Deep Learning

Background Delineating the cellular origins of extracellular vesicles (EVs) enables the detection of clinically relevant changes in dynamic and comple...

Clonal haematopoiesis without identified genetic drivers: insights from analyses of 407,512 individuals

Clonal haematopoiesis (CH) becomes ubiquitous as humans age. The role of somatic driver mutations in its development has been studied widely, but litt...

CharacTERT: A machine learning tool for classifying hTERT missense variants

Missense mutations in TERT, the gene encoding the human telomerase catalytic subunit hTERT, are associated with Telomere Biology Disorders (TBDs). Exp...

Prediction of Transcription Factor DNA Binding Affinity with High-Throughput Kd Measurements and Deep Learning

Transcription factors (TFs) regulate gene expression through specific interactions with genomic DNA. While TF binding motifs from public databases des...

Comprehensive interaction profiling and machine learning prediction of bacteriophage infectivity across clinically diverse Pseudomonas aeruginosa

The rise of antibiotic-resistant bacterial infections has driven renewed interest in bacteriophage therapy, where viruses that specifically kill bacte...

Assessing the Generalizability of Machine Learning and Physics-Based Methods with DNA-Encoded Libraries

Predicting protein-ligand binding is a central challenge in computational drug discovery, and while machine learning (ML) and co-folding methods have ...