Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Generative AI in the Advancement of Viral Therapeutics for Predicting and Targeting Immune-Evasive SARS-CoV-2 Mutations.

IEEE journal of biomedical and health informatics - 1 Nov 2024

Bist Prem Singh, Tayara Hilal, Chong Kil To

Abstract excerpt

The emergence of immune-evasive mutations in the SARS-CoV-2 spike protein is consistently challenging existing vaccines and therapies, making precise prediction of their escape potential a critical imperative. Artificial Intelligence(AI) holds great promise for deciphering the intricate language of protein. Here, we employed a Generative Adversarial Network to decipher the hidden escape pathways within the spike...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Artificial Intelligence
Share to Computational Biology

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to COVID-19

Share to COVID-19 diagnosis using AI

Share to Mutation

Share to SARS-CoV-2

Share to SARS-CoV-2 and COVID-19 Research

Share to Spike Glycoprotein, Coronavirus

Source

Identifiers

PMID: 39042543
DOI: 10.1109/JBHI.2024.3432649

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Generative AI in the Advancement of Viral Therapeutics for Predicting and Targeting Immune-Evasive SARS-CoV-2 Mutations.PMID 39042543Read ↗

Deep generative design of neutralizing nanobodies against SARS-CoV-2 variantsSemantic proximity Read ↗

Unveiling Viral Escape Mechanisms With Machine Learning: A Transformative Approach to Mutation Analysis for SARS-CoV-2 and Beyond.Semantic proximity Read ↗

SARITA: a large language model for generating the S1 subunit of the SARS-CoV-2 spike protein.Semantic proximity Read ↗

SARITA: A Large Language Model for Generating the S1 Subunit of the SARS-CoV-2 Spike ProteinSemantic proximity Read ↗

MutaGAN: A sequence-to-sequence GAN framework to predict mutations of evolving protein populationsSemantic proximity Read ↗

Bio-informed Protein Sequence Generation for Multi-class Virus Mutation PredictionSemantic proximity Read ↗

Synthetic coevolution reveals adaptive mutational trajectories of neutralizing antibodies and SARS-CoV-2.Semantic proximity Read ↗

PandoraGAN: Generating antiviral peptides using Generative Adversarial NetworkSemantic proximity Read ↗

From Prediction to Synthesis: Generative AI Architectures and Digital Twins for the Future of Vaccines and Immuno-OncologySemantic proximity Read ↗

A Contrastive Learning Framework for Efficient Viral Escape Prediction.Semantic proximity Read ↗

High-fidelity in silico generation and augmentation of TCR repertoire data using generative adversarial networksSemantic proximity Read ↗

GDA-Pred: Generative AI-Driven Data Augmentation for Improved Prediction of IL-6 and IL-13 Inducing PeptidesSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.