Genetics

Structured Multimodal Deep Learning improves Genomic Prediction in Future Environments

The development of prediction models for phenotypes as functions of genetics and environmental inputs is a long-standing challenge in genetics and plant breeding. Deep neural networks form a promising approach to this task, due to their capacity to approximate nonlinear biological processes. Despite initial expectations, recent studies have found deep neural networks under-performing in comparison...

Non-Invasive Diagnostic Evaluation of Urinary Exosomal Let-7c Cluster Expression in Bladder Cancer Using Machine Learning Approaches

Bladder cancer (BCa) diagnosis typically relies on invasive cystoscopy, which is effective but costly and uncomfortable. Urinary microRNAs (miRNAs), especially exosomal ones, are promising non-invasive biomarkers due to their stability in biological fluids and disease specificity. However, challenges such as population variability, methodological inconsistencies and normalization issues hinder the...

DELPHAI, AI Agent for Predicting Drug Response and Resistance

Patient-derived organoids preserve critical tumor features and drug sensitivity patterns that mirror patient clinical responses, enabling single-cell ...

Learning the native-like codons with a 5’UTR and RNA secondary structure aided species-informed transformer model

Efficient protein expression across heterologous hosts remains a major challenge in synthetic biology, largely due to species-specific differences in ...

A Benchmark of Evo2 Genomic AI Models for Efficient and Practical Deployment

The rapid advancement of DNA foundation language models has brought about a transformative shift in genomics, allowing for the deciphering of intricat...

Illuminating the Virosphere’s Dark Matter using Hierarchical Deep Learning

Systematic discovery of novel viruses is essential for pandemic preparedness, understanding tumor-associated viruses, developing viral delivery system...

CNN-based learning of single-cell transcriptomes reveals a blood-detectable multi-cancer signature of brain metastasis

Brain metastasis (BrM) is a serious complication of advanced cancers and remains difficult to predict before clinical symptoms appear. To investigate ...

Uncovering the Mechanistic Landscape of Regulatory DNA with Deep Learning

The regulatory genome encodes the logic that governs gene expression, enabling cells to respond to developmental, environmental, and evolutionary cues...

Target-site Dynamics and Alternative Polyadenylation Explain Large Share of Apparent MicroRNA Differential Expression

MicroRNA (miRNA) abundance reflects a dynamic balance between biogenesis, target engagement and decay, yet differential expression (DE) analyses typic...

Expansion of DNA-Encoded Library Hits Using Generative Chemistry and Ultra-Large Compound Catalogs

DNA-encoded libraries (DELs) are powerful tools for initial hit identification, yet the combinatorial chemistries and building block choices used in t...

Building an ‘epigenetic clock’: Utilizing whole genome DNA methylation patterns to predict age in haddock, Melanogrammus aeglefinus

Age-based population models are a gold standard approach to estimate stock size and sustainable catch recommendations for effective fisheries manageme...

A Genomic Language Model for Zero-Shot Prediction of Promoter Variant Effects

Disease-associated genetic variants occur extensively in noncoding regions like promoters, but current methods focus primarily on single nucleotide va...

A deep learning approach for rational affinity maturation of anti-VEGF nanobodies

Nanobodies offer several advantages over conventional antibodies due to their lower immunogenicity, enhanced stability, and superior tissue penetratio...

Generative modeling for RNA splicing prediction and design

Alternative splicing (AS) of pre-mRNA plays a crucial role in tissue-specific gene regulation, with disease implications due to splicing defects. Pred...

TRANCERs: Engineering enhancers into autonomous tissue-specific expression cassettes

The process by which a foreign gene is introduced into a cell and translated into a functional protein is referred to as transgene expression. Underst...

Dynamically Assembling Biological Intelligence to Predict Novel Cellular Phenotypes

In this work, we introduce Bio-AMLM (Biological Adaptive Modular Learning Model), a new framework designed to address out-of-distribution (OOD) genera...

PathQC: Determining Molecular and Physical Integrity of Tissues from Histopathological Slides

Quantifying tissue molecular and physical integrity is essential for biobank development. However, current assessment methods either involve destructi...

FFixR: A Machine Learning Framework for Accurate Somatic Mutation Calling from FFPE RNA-Seq Data in Cancer

Formalin-fixed paraffin-embedded (FFPE) tissues are widely used in clinical and research settings, yet their use for detecting somatic mutations from ...

DeepVul: A Multi-Task Transformer Model for Joint Prediction of Gene Essentiality and Drug Response

Despite their potential, current precision oncology approaches benefit only a small fraction of patients due to their limited focus on actionable geno...

Predicting enhancer-gene links from single-cell multi-omics data by integrating prior Hi-C information

Enhancers play an important role in transcriptional regulation by modulating gene expression from distal genomic locations. Although single-cell ATAC ...