Genetics

CosMAP: Contrastive Manifold Approximation and Projection for Dimensionality Reduction of Omics and Genealogical Data

Omics datasets, particularly single-cell RNA sequencing data, are high-dimensional, sparse, noisy, and dominated by zero values, making faithful low-dimensional representation challenging. Existing dimensionality-reduction methods may distort local neighbourhoods, global organization, or the cohesion of meaningful populations, with similar limitations arising in genealogical data. We introduce Con...

SafeCap: Improving LVLM Safety with Image Captioning Reinforcement Learning

Large vision-language models (LVLMs) remain vulnerable to jailbreak attacks that exploit visual inputs to bypass safety alignment inherited from their language backbones. We propose SafeCap, a reinforcement-learning framework that aligns LVLMs through learned self-captioning. SafeCap trains a policy model to first generate a safety-relevant image caption and then produce a final answer; the captio...

Multi-Level Evidence Aggregation for Robust Facial Phenotype Retrieval in Rare Genetic Disorder Prioritization

AI-assisted facial phenotyping supports rare genetic disorder prioritization by retrieving visually similar diagnosed cases from facial image referenc...

Uncertainty-Aware Deep Learning for Genomics Applications: Insights from an Empirical Study

Deep learning models have emerged as the standard computational tool for a wide range of applications in genomics. Yet, uncertainty quantification (UQ...

DiffSafeMerge: Mitigating Backdoor Inheritance in Diffusion Model Merging

Unconditional diffusion checkpoint merging assumes benign sources, yet a compromised public checkpoint can transfer a dormant backdoor while clean gen...

PET/CT Radiogenomic Mutation Prediction in Non-Small Cell Lung Cancer Using Multi-Label Learning

Lung cancer remains one of the leading causes of cancer- related mortality worldwide. Although targeted therapies have improved outcomes for patients ...

LookAgain: Closed-Loop GUI Grounding with Visually Grounded Reflection

Recent graphical user interface (GUI) grounders have significantly advanced single-shot accuracy on standard benchmarks, yet their performance degrade...

Learning Deep Modality-Shared Self-Expressiveness for Image Clustering with Textual Information

Leveraging textual information for image clustering has emerged as a promising direction, largely owing to the powerful representations learned by Vis...

Decoding Phenotypes: A Framework for Fusing Genomic Language Models and Neuroimaging

Neuroimaging and genetic testing are two important clinical references for nervous system diseases, offering complementary diagnostic information. How...

Idea Search: Guiding Tree Search with Ideas to Explore Diverse Scientific Methods

Tree Search-based test-time scaling of LLMs is a powerful tool for automated scientific coding. However, pure Tree Search sometimes struggles with sys...

CRISMER: A transformer-based Interpretable Deep Learning Approach for Genome-wide CRISPR Cas-9 Off-Target Prediction and Optimization

CRISPR-Cas9 gene editing holds transformative promise for genetic therapies, but is hindered by off-target effects that undermine its precision and sa...

Explainable machine learning relates histological to genomic pathology

Background & Aims: Haematoxylin and eosin (H&E) staining remains the diagnostic gold standard for solid cancers, including hepatocellular carcinoma, a...

Assessing Computational Models for Pharmacogenomic Variant Interpretation

Accurately predicting the effects of pharmacogenomic variants is essential for the development of personalized therapeutic strategies, as genetic vari...

Uncovering High-Order Epistatic Interactions in GWAS via a Machine Learning-Based Feature Engineering Framework

Background: Genome wide association studies (GWAS) often fail to identify higher-order epistatic interactions that contribute to complex inheritance p...

De novo transformer modeling improves recovery of genetic cell types from sparse single-cell RNA sequencing

Single-cell RNA sequencing (scRNA-seq) simultaneously provides gene-expression profiles and genetic variants from individual cells, creating an opport...

REFCON: Reference-free and robust copy number inference in single-cell tumor transcriptomes

Single-cell RNA sequencing (scRNA-seq) is widely used to infer copy number profiles from tumor cells. Existing methods build on a reference-based norm...

SLIM: A small linear model with STRING embeddings for single-cell genetic perturbation prediction

Predicting cellular responses to genetic perturbations is central to understanding gene function and prioritizing therapeutic targets, but experimenta...

Programmable Allosteric DNAzyme Coupled with CRISPR/Cas12a System for Multiplexed and Sensitive Detection of Extracellular Vesicle Derived MicroRNAs

Extracellular vesicle (EV)-derived microRNAs serve as important biomarkers for cancer diagnosis, yet their accurate detection remains limited by insuf...

Nup153 regulates neuronal responsiveness through HDAC1-mediated epigenetic modulation

Neural activity-dependent gene regulation is central to the development of neural networks and neuronal plasticity. Induction of activity-dependent ge...

PGViS: Personal Genome Variant interpretation Score for lung cancer genomes

Inherited lung cancer risk arises from both protein-coding and non-coding germline variants, but the functional non-coding component is largely unchar...