Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Detecting and quantifying overparametrization in RNA language models with REDIAL

While RNA language models (LMs) have served as foundation models (FMs) to advanced structural predic...

Transferable Transcriptional Topic Modeling Traces Medulloblastoma Subtypes to Distinct Cerebellar Developmental States

Single-cell transcriptomics transformed our understanding of cellular heterogeneity, yet cross-datas...

Virtual screening and zebrafish phenotype-based evaluation argues against repurposing 4-phenylbutyrate for STXBP1-relateddisorders

Syntaxin-binding protein 1 (STXBP1) mutations lead to severe epilepsy, intellectual disability, deve...

Machine Learning Analysis to Define Cell Lineage in Leiomyosarcoma

Introduction Cellular differentiation and lineage commitment are known to be associated with differe...

Integrative Genomic, Single-Cell, and Functional Profiling of the CD48-CD244 Axis and NK-Cell Dysfunction in Multiple Myeloma

Multiple myeloma (MM) orchestrates immune evasion by subverting natural killer (NK) cell function. C...

pyTrance finds co-localizing RNAs in subcellular spatial transcriptomics data

Regulation of RNA subcellular localization is crucial for cellular functions in health and disease. ...

FiberLM: A Transformer-Based Model for Mouse Brain Diffusion MRI Tractography Guided by Viral Tracer Data

Diffusion MRI (dMRI) tractography provides a non-invasive method for mapping whole-brain structural ...

Complex-Valued Phase-Coherent Transformer

Complex-valued Transformers have largely inherited softmax attention from real-valued architectures....

AssayBench: An Assay-Level Virtual Cell Benchmark for LLMs and Agents

Recent advances in machine learning and large-scale biological data collections have revived the pro...

MISP-Bench: Decomposing User-Provided False Priors into Answer, Rationale, and Guard Effects

Large language models in clinical and educational settings routinely receive user-provided context c...

Interpretable neural networks prioritize cancer driver genes from genome-wide dependency landscapes

Identifying cancer driver genes and their therapeutic impact remains a core challenge in computation...

Integrative taxonomy using traits and genomic data for Species Delimitation with Deep learning

Recognizing species boundaries in complex speciation scenarios, including those involving gene flow ...

Entropy Sorting Feature Selection: information-theoretic gene set identification improves single-cell RNA sequencing data interpretability

Single-cell RNA sequencing (scRNA-seq) has transformed our ability to resolve cellular heterogeneity...

UPhAIR: A Hybrid Pipeline for Generating Understandable Post-hoc AI Reports in Glioma IDH Mutation Status Prediction

Clinical adoption of machine learning (ML) in medical imaging is limited by the lack of interpretabi...

BRIDGE: A Multi-organ Histo-ST Foundation Model Enables Virtual Spatial Transcriptomics for Enhanced Few-shot Cancer Diagnosis

Recent studies have explored generating virtual spatial transcriptomics (ST) profiles from histologi...

Cumulative-Goodness Free-Riding in Forward-Forward Networks: Real, Repairable, but Not Accuracy-Dominant

Forward-Forward (FF) training allows each layer to learn from a local goodness criterion. In cumulat...

DINORANKCLIP: DINOv3 Distillation and Injection for Vision-Language Pretraining with High-Order Ranking Consistency

Contrastive language-image pretraining (CLIP) suffers from two structural weaknesses: the symmetric ...

Bridging genomes and peptidomes: hybrid sequencing reveals conserved bioactive peptides in crustaceans

Endogenous peptides are critical regulators of signaling and immunity but remain difficult to charac...

Metastatic Site Prediction in Breast Cancer using Kirchhoff's Law and Omics Knowledge Graph

Predicting the anatomical site of metastasis from a primary tumour remains an unsolved problem in br...

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