Genetics

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

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Protein Diffusion Models as Statistical Potentials

Machine learning has driven rapid progress in protein structure prediction and design, but key challenges remain such as predicting protein structures when evolutionary information is unavailable, modeling full conformational landscapes, and capturing the thermodynamics of mutations and conformational changes. To address these problems we developed ProteinEBM, an Energy-Based Model of protein conf...

A novel NLP-based method and algorithm to discover RNA-binding protein (RBP) motifs, contexts, binding preferences, and interactions

RNA-binding proteins (RBPs) are essential modulators in the regulation of mRNA processing. The binding patterns, interactions, and functions of most RBPs are not well-characterized. Previous studies have shown that motif context is an important contributor to RBP binding specificity, but its precise role remains unclear. Despite recent computational advances to predict RBP binding, existing method...

GENET: AI-Powered Interactive Visualization Workflows to Explore Biomedical Entity Networks

Formulating hypotheses about gene-disease associations requires logical inference from prior data, followed by a laborious literature review. AI model...

Machine learning inference of natural product chemistry across biosynthetic gene cluster types

With ever-increasing volumes of sequencing data for biosynthetic gene clusters (BGCs), computational methods for the prediction of resulting secondary...

Temporal Perturbation Scanning: AI-Driven Deconstruction of Universal Biomolecular Recognition Mechanisms

Understanding the physicochemical principles governing intermolecular recognition remains a fundamental challenge across biochemistry, drug discovery,...

PlantCAD2: A Long-Context DNA Language Model for Cross-Species Functional Annotation in Angiosperms

Understanding how DNA sequence encodes biological function remains a fundamental challenge in biology. Flowering plants (angiosperms), the dominant te...

Viral Sentry AI (VirSentAI) - Automated Zoonotic Surveillance & Drug Repurposing Agent

Zoonotic viruses capable of jumping from animal reservoirs into human populations represent a persistent and unpredictable menace to global health. To...

SNooPy: a statistical framework for long-read metagenomic variant calling

Current long-read single-nucleotide variant callers were designed primarily for genomic data—particularly human genomes. While some have been used on ...

Successful Predictive Modeling of Pollen Fitness Phenotypes Is Enabled by Measures of Expression Specificity

The ability to predict phenotypes from genotypes in multicellular organisms remains limited despite rapid advances in genotyping and phenotyping metho...

Motion sequencing reveals hidden patterns of repetitive behavior in a mouse model of epilepsy

Epilepsy is the 4th most prevalent neurological condition with 50 million cases worldwide. Patients with epilepsy bare a disproportionate burden of co...

Comprehensive perturbation of transcription factors in human cardiomyocytes reveals the regulatory architecture of congenital heart disease

Over 100 genes have been implicated in congenital heart disease (CHD), yet the genetic basis for >50% of CHD remains unexplained. A key challenge is t...

CRISPR-based neuromorphic computing for solving regression and classification

The CRISPR-dCas9 system has emerged as a versatile platform for programmable gene regulation, offering unique advantages in modularity and orthogonali...

Genome-Level Hierarchical Attention Transformer with Multi-Head Attention Weighted Sum for Broad-Spectrum Antimicrobial Resistance Prediction and Discovery of Resistance-Related Genomic Contexts

Antimicrobial resistance is a growing global health concern, requiring reliable tools for predicting resistance across a wide range of bacteria and an...

Airborne Nanoplastics Perturb Mitochondrial Complex I via the ND6 Axis: Polymer-Specific Mitoepigenetic Remodeling Integrating Experimental, In Silico, and Machine Learning Analyses

Airborne nanoplastics constitute an emerging class of environmental contaminants, but their mitoepigenetic effects on human immune cells have not been...

Image-Based Profiling of Induced Trophoblast Stem Cells Identifies Signatures Associated with Sex, Schizophrenia Genomic Risk and Placental Stress

Schizophrenia (SCZ) is a neurodevelopmental disorder where both genetic and environmental risks converge during pregnancy. Recent studies have highlig...

Benchmarking Chemical, Genetic, and Cell Line Encodings for Cancer Perturbation Response Prediction

Estimating the response of tumor cells to specific perturbations is crucial for identifying effective treatments that selectively target cancer cells ...

Fine-Grained Structural Classification of Biosynthetic Gene Cluster-Encoded Products

Biosynthetic gene clusters (BGCs) are responsible the biosynthesis of many natural products, including a multitude of effective therapeutics and their...

Single-cell co-mapping reveals relationship between chromatin state and gene expression in early zebrafish development

Establishing a cell-type-specific chromatin landscape is crucial for the maintenance of cell identity during embryonic development. However, our knowl...

Discovery of Electron Hole-hopping Redox Mutations in Myoglobin by Deep Mutational Learning

In addition to storing molecular oxygen, myoglobin catalyzes peroxidase-like reactions involving high valency iron(IV)-oxo species that support oxidat...

A Context-Specific, Literature-Supported Framework for Validating Stress Response Models in Mammals

Computational models of stress responses can highlight candidate genes underlying physiological adaptation, but their utility depends on rigorous vali...

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