Genetics

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

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Molecular Translators as a Computational Primitive for Biomarker Discovery: Learnability Gains Under Conserved Information Ceilings

Virtual molecular mapping systems such as MISO and GigaTIME introduce a potentially transformative p...

Hybrid CNN and Multi-Head Attention Model for Analyzing Epigenetic Mechanisms and Gene Expression Across Fungal Phylogenetic Distances

Understanding gene expression is crucial for optimizing biological processes in bioeconomic processe...

DEFault++: Automated Fault Detection, Categorization, and Diagnosis for Transformer Architectures

Transformer models are widely deployed in critical AI applications, yet faults in their attention me...

Advancing ab initio genome annotation with OrionGeno

The rapid expansion of eukaryotic genome sequencing has created an urgent demand for scalable and ac...

Scalable machine learning improves resistance prediction and identifies novel determinants in Mycobacterium tuberculosis

Multidrug-resistant and extensively drug-resistant Mycobacterium tuberculosis (MTB) represents a gro...

KAYRA: A Microservice Architecture for AI-Assisted Karyotyping with Cloud and On-Premise Deployment

We present KAYRA, an end-to-end karyotyping system that operates inside the operational constraints ...

Hyper Input Convex Neural Networks for Shape Constrained Learning and Optimal Transport

We introduce Hyper Input Convex Neural Networks (HyCNNs), a novel neural network architecture design...

A Multi-modal LLM-Knowledge Fusion Framework for Predicting Single-cell Genetic Perturbation Effects

Understanding cellular responses to genetic perturbations is fundamental for drug discovery, yet exp...

Accurate ab initio gene prediction in eukaryotes with Tiberius in multiple clades

Eukaryotic genome annotation is currently bottlenecked by limitations in the generality, scalability...

Learning dynamics of unsupervised deep learning reveal epoch-specific genetic architectures of brain morphology

Representation learning is an emerging paradigm for deriving phenotypes from complex measurements (e...

Generative design of sequence specific DNA binding proteins

De novo protein design has advanced rapidly in recent years, yet the programmable recognition of spe...

UshEffect-3D: Structure-informed Classification of USH2A Missense Variants for Inherited Retinal Disease

Variants of uncertain significance (VUS) in USH2A represent a critical interpretive challenge in inh...

HyperMap: An Efficient Framework for Transferring Perturbation Responses Across Diverse Biological Contexts

Recent perturbation atlases profile transcriptional responses to thousands of targeted perturbations...

PathMoG: A Pathway-Centric Modular Graph Neural Network for Multi-Omics Survival Prediction

Cancer survival prediction from multi-omics data remains challenging because prognostic signals are ...

MIMIC: A Generative Multimodal Foundation Model for Biomolecules

Biological function emerges from coupled constraints across sequence, structure, regulation, evoluti...

Aycromo: An Open-Source Platform for Automatic Chromosome Detection in Metaphase Images Based on Deep Learning

Chromosome analysis is a fundamental step in the diagnosis of genetic diseases, but the manual karyo...

A machine learning approach to infer DNase1L3 activity from plasma cell-free DNA fragmentomics

DNase1L3 is an endonuclease that fragments DNA during apoptosis and digests DNA from microparticles ...

A Modular Framework for Automated Segmentation and Analysis of AFM Imaging of Chromatin Organization

Chromatin organization underlies essential genome functions, but its nanoscale organization remains ...

GlioVision: A Multi-Modal MRI Framework for Non-Invasive Glioma Molecular Biomarkers Prediction

Gliomas are aggressive primary brain tumors that necessitate critical molecular biomarker prediction...

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