Genetics

scooby: Modeling multi-modal genomic profiles from DNA sequence at single-cell resolution

Understanding how regulatory DNA elements shape gene expression across individual cells is a fundamental challenge in genomics. Joint RNA-seq and epigenomic profiling provides opportunities to build unifying models of gene regulation capturing sequence determinants across steps of gene expression. However, current models, developed primarily for bulk omics data, fail to capture the cellular hetero...

Synteny-aware functional annotation of bacteriophage genomes with Phynteny

Accurate genome annotation is fundamental to decoding viral diversity and understanding bacteriophage biology; yet, the majority of bacteriophage genes remain functionally uncharacterised. Bacteriophage genomes often exhibit conserved gene order, or synteny, that reflects underlying constraints in genome architecture and expression. Here, we present Phynteny, a genome-scale, deep learning framewor...

Replacement of a single residue in an antibody completely abolishes cognate antigen binding, as predicted by theoretical methods

Structural insights into the interaction between antibodies and antigens at the atomic level are pivotal for understanding the molecular mechanisms of...

Decoding Breast Cancer Heterogeneity via Multi-Omics Integration and Language Model-Based Interpretation

We present a novel pipeline combining Multi-Omics Factor Analysis (MOFA) and fine-tuned Large Language Models (LLMs) to predict breast cancer subtypes...

Investigating the performance of foundation models on human 3’UTR sequences

Foundation models, such as DNABERT and Nucleotide Transformer have recently shaped a new direction in DNA research. Trained in an unsupervised manner ...

Expanding the DNA Motif Lexicon of the Transcriptional Regulatory Code

Transcriptional regulatory sequences in metazoans contain intricate combinations of transcription factor (TF) motifs. Stereospecific arrangements of s...

scHDeepInsight: A Hierarchical Deep Learning Framework for Precise Immune Cell Annotation in Single-Cell RNA-seq Data

Immune cell classification from single-cell RNA sequencing (scRNA-seq) presents significant challenges due to complex hierarchical relationships among...

Allostery is a widespread cause of loss-of-function variant pathogenicity

Allosteric communication between non-contacting sites in proteins plays a fundamental role in biological regulation and drug action. While allosteric ...

A scalable computational framework for predicting gene expression from candidate cis-regulatory elements

Deciphering the relationships between cis-regulatory elements (CREs) and target gene expression has been a long-standing unsolved problem in molecular...

LeGO-Teknik reveals that the neurogenesis pathway is a clone-specific hallmark of brain metastasis in breast cancer

Breast cancer exhibits substantial inter- and intra-patient heterogeneity. Yet the molecular features underlying this diversity and their roles in tum...

AbAgym: a well-curated dataset for the mutational analysis of antibody-antigen complexes

With monoclonal antibodies becoming one of the largest classes of biopharmaceuticals, it is important to have curated data to train computational mode...

Individual differences in learning and decision-making: the role of COMT Val158Met polymorphism in transitive inference

Understanding the ordinal relationships between items requires constructing a rank order supporting decision-making between options. This process depe...

Rapid and Reproducible Multimodal Biological Foundation Model Development with AIDO.ModelGenerator

Foundation models (FMs) for DNA, RNA, proteins, cells, and tissues have begun to close long-standing performance gaps in biological prediction tasks, ...

Inferring the landscapes of mutation and recombination in the common marmoset (Callithrix jacchus) in the presence of twinning and hematopoietic chimerism

The common marmoset is an important model in biomedical and clinical research, particularly for the study of age-related, neurodegenerative, and neuro...

Machine Learning Resolves Functional Phenotypes and Therapeutic Responses in KCNQ2 Developmental Epileptic Encephalopathy iPSC Models

Pathogenic KCNQ2 variants are associated with developmental and epileptic encephalopathy (KCNQ2-DEE), a devastating disorder characterized by neonatal...

Learning sequence-function relationships with scalable, interpretable Gaussian processes

Understanding the relationship between biological sequences, such as DNA, RNA or protein sequences, and their resulting phenotypes is one of the centr...

Pretraining Improves Prediction of Genomic Datasets Across Species

Recent studies suggest that deep neural network models trained on thousands of human genomic datasets can accurately predict genomic features, includi...

Accurate detection and quantification of single-base m6A RNA modification using nanopore signals with multi-view deep learning

N6-methyladenosine (m6A) is a crucial epitranscriptomic mark. While Nanopore Direct RNA Sequencing (DRS) enables transcriptome-wide detection, most ex...

Deep Learning of Functional Perturbations from Condensate Morphology

Biomolecular condensates compartmentalize the interior of living cells to spatiotemporally organize complex functions, yet linking molecular interacti...

E2-Regulated Transcriptome Complexity Revealed by Long-Read Direct RNA Sequencing: From Isoform Discovery to Truncated Proteins

Estrogen receptor alpha (ERα)-positive (ER+) breast cancers are driven by 17β-estradiol (E2) binding to ERα, which transcriptionally regulates downstr...