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Fabian C Spoendlin

Showing results (1-10 of 8) with videos related to

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Methods in Molecular Biology (Clifton, N.J.)|July 2, 2025
Structure-Based Epitope Profiling with the Structural Profiling of Antibodies to Cluster by Epitope 2 (SPACE2) AlgorithmFabian C Spoendlin, Charlotte M Deane
Current Opinion in Structural Biology|January 25, 2025
Challenges and compromises: Predicting unbound antibody structures with deep learningAlexander Greenshields-Watson, Odysseas Vavourakis, Fabian C Spoendlin, et al.
Frontiers in Molecular Biosciences|October 4, 2023
Improved computational epitope profiling using structural models identifies a broader diversity of antibodies that bind to the same epitopeFabian C Spoendlin, Brennan Abanades, Matthew I J Raybould, et al.
Cancer Research|January 15, 2025
Correction: Mathematical Model-Driven Deep Learning Enables Personalized Adaptive TherapyKit Gallagher, Maximilian A R Strobl, Derek S Park, et al.
Cancer Research|April 3, 2024
Mathematical Model-Driven Deep Learning Enables Personalized Adaptive TherapyKit Gallagher, Maximilian A R Strobl, Derek S Park, et al.
Communications Biology|May 20, 2026
ANARCII enables alignment-free antigen receptor numbering using a generalised language modelAlexander Greenshields-Watson, Parth Agarwal, Sarah A Robinson, et al.
Nature Machine Intelligence|October 27, 2025
Predicting the conformational flexibility of antibody and T cell receptor complementarity-determining regionsFabian C Spoendlin, Monica L Fernández-Quintero, Sai S R Raghavan, et al.
Structure (London, England : 1993)|September 27, 2024
Assessing AF2's ability to predict structural ensembles of proteinsJakob R Riccabona, Fabian C Spoendlin, Anna-Lena M Fischer, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Methods in Molecular Biology (Clifton, N.J.)|July 2, 2025
Structure-Based Epitope Profiling with the Structural Profiling of Antibodies to Cluster by Epitope 2 (SPACE2) AlgorithmFabian C Spoendlin, Charlotte M Deane
Current Opinion in Structural Biology|January 25, 2025
Challenges and compromises: Predicting unbound antibody structures with deep learningAlexander Greenshields-Watson, Odysseas Vavourakis, Fabian C Spoendlin, et al.
Frontiers in Molecular Biosciences|October 4, 2023
Improved computational epitope profiling using structural models identifies a broader diversity of antibodies that bind to the same epitopeFabian C Spoendlin, Brennan Abanades, Matthew I J Raybould, et al.
Cancer Research|January 15, 2025
Correction: Mathematical Model-Driven Deep Learning Enables Personalized Adaptive TherapyKit Gallagher, Maximilian A R Strobl, Derek S Park, et al.
Cancer Research|April 3, 2024
Mathematical Model-Driven Deep Learning Enables Personalized Adaptive TherapyKit Gallagher, Maximilian A R Strobl, Derek S Park, et al.
Communications Biology|May 20, 2026
ANARCII enables alignment-free antigen receptor numbering using a generalised language modelAlexander Greenshields-Watson, Parth Agarwal, Sarah A Robinson, et al.
Nature Machine Intelligence|October 27, 2025
Predicting the conformational flexibility of antibody and T cell receptor complementarity-determining regionsFabian C Spoendlin, Monica L Fernández-Quintero, Sai S R Raghavan, et al.
Structure (London, England : 1993)|September 27, 2024
Assessing AF2's ability to predict structural ensembles of proteinsJakob R Riccabona, Fabian C Spoendlin, Anna-Lena M Fischer, et al.
Pageof 1