Results 171 to 180 of about 1,625,834 (280)
Foundation Protein Language Models for Influenza A Virus T-Cell Epitope Prediction: A Transformer-Based Viroinformatics Framework. [PDF]
Bukhari SNH, Ogudo KA.
europepmc +1 more source
Immunoinformatics approach of epitope prediction for SARS-CoV-2. [PDF]
Awad N +4 more
europepmc +1 more source
Data mining methods for conformational B-cell epitope prediction
University of Technology Sydney. Faculty of Engineering and Information Technology.NO FULL TEXT AVAILABLE. This thesis contains 3rd party copyright material. The hardcopy may be available for consultation at the UTS Library.NO FULL TEXT AVAILABLE.
Ren, Jing
core
This study identifies ARHGAP5, in addition to the frequently mutated ARHGAP35, as significantly mutated in endometrial cancer. Mutations in both genes co‐occur and are associated with their correlated downregulation. Functional CRISPR studies show that both paralogs regulate similar pathways, including actin cytoskeleton organization.
Mathilde Pinault +12 more
wiley +1 more source
Evolutionary analysis and immunoinformatic-based epitope prediction of dengue virus serotype 2 strains from Sri Lanka. [PDF]
Gunawardane DS +4 more
europepmc +1 more source
Immunogenic epitope prediction to create a universal influenza vaccine. [PDF]
Mintaev RR +3 more
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Time‐resolved X‐ray solution scattering captures how proteins change shape in real time under near‐native conditions. This article presents a practical workflow for light‐triggered TR‐XSS experiments, from data collection to structural refinement. Using a calcium‐transporting membrane protein as an example, the approach can be broadly applied to study ...
Fatemeh Sabzian‐Molaei +3 more
wiley +1 more source
PEPNet: a two-stage point cloud framework with hierarchical embedding and antigen-antibody interaction modeling for epitope prediction. [PDF]
Chen J, Zhang G, Xu Z, Zhang Q.
europepmc +1 more source
Comprehending B-Cell Epitope Prediction to Develop Vaccines and Immunodiagnostics. [PDF]
Caoili SEC.
europepmc +1 more source
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
wiley +1 more source

