Genetics

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

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Vector2Variant: Discovery of Genetic Associations from ML Derived Representations without Phenotype Engineering

Genome-wide association studies (GWAS) have transformed our understanding of human biology, but are ...

Generative Modeling of Complex-Valued Brain MRI Data

Objective. Standard Magnetic Resonance Imaging (MRI) reconstruction pipelines discard phase informat...

U-Probe: universal agentic probe design for imaging-based spatial-omics

Probe design for fluorescence in situ hybridization (FISH) underpins spatial transcriptomics, three-...

EVEE: Interpretable variant effect prediction from genomic foundation model embeddings

Predicting the clinical significance of genetic variants remains a central challenge in genomic medi...

From Pixels to Nucleotides: End-to-End Token-Based Video Compression for DNA Storage

DNA-based storage has emerged as a promising approach to the global data crisis, offering molecular-...

TFBindFormer: A Cross-Attention Transformer for Transcription Factor-DNA Binding Prediction

Transcription factors (TFs) are central regulators of gene expression, and their selective recogniti...

Integrating computational chemistry and machine learning to predict KRAS mutation-induced resistance

Mutation-induced drug resistance is a major contributor to the failure of targeted cancer therapies,...

Domain-Specific Latent Representations Improve the Fidelity of Diffusion-Based Medical Image Super-Resolution

Latent diffusion models for medical image super-resolution universally inherit variational autoencod...

T2I-BiasBench: A Multi-Metric Framework for Auditing Demographic and Cultural Bias in Text-to-Image Models

Text-to-image (T2I) generative models achieve impressive visual fidelity but inherit and amplify dem...

Interpretable DNA Sequence Classification via Dynamic Feature Generation in Decision Trees

The analysis of DNA sequences has become critical in numerous fields, from evolutionary biology to u...

Evolutionary-scale protein language models uncover beneficial variants in a Sorghum bicolor diversity panel

Quantitative genetic approaches such as genome-wide association studies and genomic prediction are w...

TB-Bench: A Systematic Benchmark of Machine Learning and Deep Learning Methods for Second-Line TB Drug Resistance Prediction

Drug-resistant tuberculosis (TB), characterized by prolonged treatment regimens and suboptimal treat...

Pipette: Encoding scientific literature into an executable Skill Graph for multi-agent bioinformatics

The cost of genomic sequencing has fallen by several orders of magnitude, yet data analysis remains ...

CRIS: A Centralized Resource for High-Quality RNA Structure and Interaction Data in the AI Era

As interest in RNA-based therapeutics expands, there is a growing demand for RNA structure elucidati...

EvoLen: Evolution-Guided Tokenization for DNA Language Model

Tokens serve as the basic units of representation in DNA language models (DNALMs), yet their design ...

Plug-and-Play Logit Fusion for Heterogeneous Pathology Foundation Models

Pathology foundation models (FMs) have become central to computational histopathology, offering stro...

Introducing Echo Networks for Computational Neuroevolution

For applications on the extreme edge, minimal networks of only a few dozen artificial neurons for ev...

The Mechanistic Invariance Test: Genomic Language Models Fail to Learn Positional Regulatory Logic

Genomic language models (gLMs) have transformed computational biology, achieving state-of-the-art pe...

ECLIPSE: A Composable Pipeline for Predicting ecDNA Formation, Evolution, and Therapeutic Vulnerabilities in Cancer

Extrachromosomal DNA (ecDNA) represents one of the most pressing challenges in cancer biology: circu...

Transcriptomic Models for Immunotherapy Response Prediction Show Limited Cross-cohort Generalisability

Immune checkpoint inhibitors (ICIs) have transformed cancer therapy; yet substantial proportion of p...

HumANDiff: Articulated Noise Diffusion for Motion-Consistent Human Video Generation

Despite tremendous recent progress in human video generation, generative video diffusion models stil...

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