This paper introduces GLORIA, a novel framework for aligning and fusing histopathology, mRNA expression, and magnetic resonance imaging data for glioma grading and survival prediction.

The paper introduces CORE, a contrastive evidence organization method, which significantly improves the accuracy of LLM-based predictions of gene expression changes following cellular perturbations by…

Loom is a system for analyzing spatial transcriptomics data through detailed pseudo-temporal exploration, cross-sample comparisons, and investigation of spatiotemporal biological mechanisms.

The paper introduces ProtStructQA, an executable benchmark that tests protein structural reasoning by requiring language models to generate measurable 3D coordinates, revealing a capability-dependent…

A multimodal Mixture-of-Experts framework was developed for asthma detection using vocal biomarkers and clinical data, achieving better performance than unimodal and bimodal approaches.

The paper introduces Ryze, an automated system that synthesizes evidence-enriched Question-Answering (QA) pairs from raw biomedical papers, resulting in a specialized VLM (BioVLM-8B) that significantl…

This paper derives bounds on the probability of incorrect clustering of noisy short sequences using statistically optimal rules, focusing on DNA storage decoders.

The paper introduces AMix-2, a novel protein-text foundation model that unifies protein understanding and sequence design by embedding both modalities in a shared token space, achieving state-of-the-a…

The paper proposes GC-MoE, a novel framework that uses a Mixture-of-Experts approach guided by genomics to accurately predict cell-type-specific gene expression for individual cells from histopatholog…

BIRDNet is a novel, sparse, and interpretable deep neural network that encodes Boolean implication knowledge mined directly from tabular data, achieving performance comparable to dense models while dr…

The paper introduces retraining-free frameworks (Meow2X and TRNE) that mechanistically localize and suppress toxicity within language models by analyzing activation differences, achieving safety impro…

This paper presents the first application of thermodynamic computing to mRNA codon optimization in pharmaceutical R&D, achieving significant energy savings compared to conventional GPUs.

The paper introduces Influence-Guided Symbolic Regression (IGSR), a novel framework that uses granular influence scores to guide LLMs in efficiently searching for and discovering complex mathematical…

The authors introduce Structured PubMed, a comprehensive corpus of section-labeled biomedical abstracts compiled from the complete PubMed database.

CodeCytos is a novel coding-based reasoning agent framework that enables dynamic, programmable interaction with spatial molecular imaging data, significantly improving the automation and customization…

The paper proposes a novel framework that enables multiple institutions to jointly train a synthetic genomic data generator without revealing their raw data, thereby facilitating large-scale, privacy-…

AutoSynthesis is an end-to-end multi-agent system for automated meta-analysis in evidence synthesis, including search strategy formulation, literature retrieval, screening, eligibility assessment, sta…