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Amelia Villegas-Morcillo

Showing results (1-10 of 7) with videos related to

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Briefings in Bioinformatics|April 20, 2022
An analysis of protein language model embeddings for fold predictionAmelia Villegas-Morcillo, Angel M Gomez, Victoria Sanchez
BMC Bioinformatics|October 13, 2021
FoldHSphere: deep hyperspherical embeddings for protein fold recognitionAmelia Villegas-Morcillo, Victoria Sanchez, Angel M Gomez
Bioinformatics (Oxford, England)|December 10, 2022
ManyFold: an efficient and flexible library for training and validating protein folding modelsAmelia Villegas-Morcillo, Louis Robinson, Arthur Flajolet, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics|August 6, 2020
Protein Fold Recognition From Sequences Using Convolutional and Recurrent Neural NetworksAmelia Villegas-Morcillo, Angel M Gomez, Juan A Morales-Cordovilla, et al.
Journal of Cheminformatics|December 2, 2025
All-atom protein sequence design using discrete diffusion modelsAmelia Villegas-Morcillo, Gijs J Admiraal, Marcel J T Reinders, et al.
Bioinformatics (Oxford, England)|August 16, 2020
Unsupervised protein embeddings outperform hand-crafted sequence and structure features at predicting molecular functionAmelia Villegas-Morcillo, Stavros Makrodimitris, Roeland C H J van Ham, et al.
Biorxiv : the Preprint Server for Biology|May 18, 2026
On the state of protein function prediction: a report on the fourth CAFA challengeRashika Ramola, M Clara De Paolis Kaluza, Damiano Piovesan, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Briefings in Bioinformatics|April 20, 2022
An analysis of protein language model embeddings for fold predictionAmelia Villegas-Morcillo, Angel M Gomez, Victoria Sanchez
BMC Bioinformatics|October 13, 2021
FoldHSphere: deep hyperspherical embeddings for protein fold recognitionAmelia Villegas-Morcillo, Victoria Sanchez, Angel M Gomez
Bioinformatics (Oxford, England)|December 10, 2022
ManyFold: an efficient and flexible library for training and validating protein folding modelsAmelia Villegas-Morcillo, Louis Robinson, Arthur Flajolet, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics|August 6, 2020
Protein Fold Recognition From Sequences Using Convolutional and Recurrent Neural NetworksAmelia Villegas-Morcillo, Angel M Gomez, Juan A Morales-Cordovilla, et al.
Journal of Cheminformatics|December 2, 2025
All-atom protein sequence design using discrete diffusion modelsAmelia Villegas-Morcillo, Gijs J Admiraal, Marcel J T Reinders, et al.
Bioinformatics (Oxford, England)|August 16, 2020
Unsupervised protein embeddings outperform hand-crafted sequence and structure features at predicting molecular functionAmelia Villegas-Morcillo, Stavros Makrodimitris, Roeland C H J van Ham, et al.
Biorxiv : the Preprint Server for Biology|May 18, 2026
On the state of protein function prediction: a report on the fourth CAFA challengeRashika Ramola, M Clara De Paolis Kaluza, Damiano Piovesan, et al.
Pageof 1