E-LIB Suche - Ergebnisse für: Villegas-Morcillo, Amelia

1

Guiding Diffusion Models for Antibody Sequence and Structur..:

Villegas-Morcillo, Amelia ; Weber, Jana M. ; Reinders, Marcel J. T.
PRX Life. 2 (2024) 3 - p. , 2024

Link: https://doi.org/10.1103/..

2

An analysis of protein language model embeddings for fold p..:

Villegas-Morcillo, Amelia ; Gomez, Angel M ; Sanchez, Victoria
Briefings in Bioinformatics. 23 (2022) 3 - p. , 2022

Link: https://doi.org/10.1093/..

3

ManyFold: an efficient and flexible library for training an..:

Villegas-Morcillo, Amelia ; Robinson, Louis ; Flajolet, Arthur..
Bioinformatics. 39 (2022) 1 - p. , 2022

Link: https://doi.org/10.1093/..

4

Protein Fold Recognition From Sequences Using Convolutional..:

Villegas-Morcillo, Amelia ; Gomez, Angel M. ; Morales-Cordovilla, Juan A..
IEEE/ACM Transactions on Computational Biology and Bioinformatics. 18 (2021) 6 - p. 2848-2854 , 2021

Link: https://doi.org/10.1109/..

5

FoldHSphere: deep hyperspherical embeddings for protein fol..:

Villegas-Morcillo, Amelia ; Sanchez, Victoria ; Gomez, Angel M.
BMC Bioinformatics. 22 (2021) 1 - p. , 2021

Link: https://doi.org/10.1186/..

6

Unsupervised protein embeddings outperform hand-crafted seq..:

Villegas-Morcillo, Amelia ; Makrodimitris, Stavros ; van Ham, Roeland C H J...
Bioinformatics. 37 (2020) 2 - p. 162-170 , 2020

Link: https://doi.org/10.1093/..

7

Fusion of Classical Digital Signal Processing and Deep Lear..:

Gomez, Angel ; Sánchez, Victoria E ; Peinado, Antonio...
https://vbn.aau.dk/da/publications/43460efd-b590-4926-8989-f90fba857b4e. , 2022

Link: https://vbn.aau.dk/da/pu..

8

FoldHSphere: deep hyperspherical embeddings for protein fol..:

Amelia Villegas-Morcillo ; Victoria Sanchez ; Angel M. Gomez
https://doi.org/10.1186/s12859-021-04419-7. , 2021

Link: https://doi.org/10.1186/..

9

Additional file 1 of FoldHSphere: deep hyperspherical embed..:

Amelia Villegas-Morcillo (11554955) ; Victoria Sanchez (5328773) ; Angel M. Gomez (11554958)
https://figshare.com/articles/journal_contribution/Additional_file_1_of_FoldHSphere_deep_hyperspherical_embeddings_for_protein_fold_recognition/16800161. , 2021

Link: https://doi.org/10.6084/..

10

ManyFold: An efficient and flexible library for training an..:

Villegas Morcillo, Amelia Otilia ; Robinson, Louis ; Flajolet, Arthur.
https://hdl.handle.net/10481/88789. , 2023

Link: https://hdl.handle.net/1..

11

Automatic identification of the protein fold type using rep..:

Villegas Morcillo, Amelia Otilia
Villegas Morcillo, Amelia Otilia. Automatic identification of the protein fold type using representations from the amino acid sequence and deep learning techniques. Granada: Universidad de Granada, 2023. [https://hdl.handle.net/10481/79636]. , 2023

Link: https://hdl.handle.net/1..

12

Fusion of Classical Digital Signal Processing and Deep Lear..:

Gómez García, Ángel Manuel ; Sánchez Calle, Victoria Eugenia ; Peinado Herreros, Antonio Miguel...
https://hdl.handle.net/10481/80608. , 2022

Link: https://hdl.handle.net/1..

13

An Analysis of Protein Language Model Embeddings for Fold P..:

Villegas Morcillo, Amelia Otilia ; Gómez García, Ángel Manuel ; Sánchez Calle, Victoria Eugenia
Published version: Amelia Villegas-Morcillo, Angel M Gomez, Victoria Sanchez, An analysis of protein language model embeddings for fold prediction, Briefings in Bioinformatics, Volume 23, Issue 3, May 2022, bbac142, [https://doi.org/10.1093/bib/bbac142]. , 2022

Link: https://hdl.handle.net/1..

14

Protein Fold Recognition from Sequences using Convolutional..:

Villegas Morcillo, Amelia Otilia ; Gómez García, Ángel Manuel ; Morales Cordovilla, Juan Andrés.
http://hdl.handle.net/10481/72712. , 2021

Link: http://hdl.handle.net/10..

15

FoldHSphere: deep hyperspherical embeddings for protein fol..:

Villegas Morcillo, Amelia Otilia ; Sánchez Calle, Victoria Eugenia ; Gómez García, Ángel Manuel
http://hdl.handle.net/10481/71171. , 2021

Link: http://hdl.handle.net/10..