COVID-19

BAGEL: Protein Engineering via Exploration of an Energy Landscape

Despite recent breakthroughs in deep learning methods for protein design, existing computational pipelines remain rigid, highly specific, and ill-suited for tasks requiring non-differentiable or multi-objective design goals. In this report, we introduce BAGEL, a modular, open-source framework for programmable protein engineering, enabling flexible exploration of sequence space through model-agnost...

Deep Evolutionary Fitness Inference for Variant Nomination from Directed Evolution

Iterative screening techniques, such as directed evolution, enable high-throughput affinity maturation to optimize binders to molecular interfaces. However, the decision problem of selecting variants from rich, evolved populations to enter low-throughput follow-up methods remains a significant bottleneck. Here, we present evolutionary fitness inference (EVFI) and DeepEVFI, two machine learning met...

Delta Marches to autonomously learn histopathology rules by generative latent space traversals

Deep learning (DL) has excelled in tissue image classification, presenting opportunities to discover biological behaviors escaping visual inspection. ...

PHbinder and PSGM: A Cascaded Framework for Epitope Prediction and HLA-I Allele Identification

The presentation of antigens by Human Leukocyte Antigen class I (HLA-I) molecules is a cornerstone of adaptive immunity. Although existing prediction ...

Classifier-guided Deep Oscillatory Neural Networks (cDONN) for capturing both Neural Dynamics and Behavior simultaneously

Generating EEG signals alongside behavioural actions introduces substantial biological complexity, akin to an abstract model that mimics rich oscillat...

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...

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 ...

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...

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...

Deep generative modeling reveals maturation-linked pairing signatures in human antibodies

Understanding how antibody heavy and light chains pair is critical for decoding immune repertoire architecture and designing therapeutic antibodies. H...

Microdroplet screening rapidly profiles a biocatalyst to enable its AI-assisted engineering

Engineering enzymes for increased efficiency is key to enabling sustainable, ‘green’ biocatalytic production processes in the chemical and pharmaceuti...

An improved deep learning model for immunogenic B epitope prediction

The recognition of B epitopes by B cells of the immune system initiates an immune response that leads to the production of antibodies to combat bacter...

MoCETSE: A mixture-of-convolutional experts and transformer-based model for predicting Gram-negative bacterial secreted effectors

Identifying effector proteins of Gram-negative bacterial secretion systems is crucial for understanding their pathogenic mechanisms and guiding antimi...

Inference of germinal center evolutionary dynamics via simulation-based deep learning

B cells and the antibodies they produce are vital to health and survival, motivating research on the details of the mutational and evolutionary proces...

Integrated histopathologic modeling of detailed tumor subtypes and actionable biomarkers

Accurate cancer subtyping with accompanying molecular characterization is critical for precision oncology. While machine learning approaches have been...

EpiPred: A gene-specific machine learning model for classifying missense variants in the epilepsy-related gene STXBP1

Missense variants in the STXBP1 gene are a frequent cause of early-onset developmental and epileptic encephalopathies and related neurodevelopmental d...

DynaRepo: The repository of macromolecular conformational dynamics

Proteins, RNA, and DNA are central to virtually all cellular processes, often assembling into macro-molecular complexes to perform their functions. Wh...

Variant effect prediction with reliability estimation across priority viruses

Viruses pose a significant threat to global health due to their rapid evolution, adaptability, and increasing potential for cross-species transmission...

Advancing Luciferase Activity and Stability beyond Directed Evolution and Rational Design through Expert Guided Deep Learning

Engineered luciferases have transformed biological imaging and sensing, yet optimizing NanoLuc luciferase (NLuc) remains challenging due to the inhere...

Enhancing Missense Variant Classification in Predicted Intrinsically Disordered Regions

The accurate classification of missense variants is a fundamental challenge in genomics, particularly for those within intrinsically disordered region...