MetaLLM : residue-wise metal ion prediction using deep transformer model

Shishir, Fairuz Shadmani, Sarker, Bishnu, Rahman, Farzana and Shomaji, Sumaiya (2023) MetaLLM : residue-wise metal ion prediction using deep transformer model. In: 10th International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2023); 12-14 Jul 2023, Meloneras, Gran Canaria, Spain. ISSN (print) 0302-9743

Downloads Metadata

Full text available as:

Official URL:	https://doi.org/10.1007/978-3-031-34960-7_4
Item Type:	Conference or Workshop Item (Paper)
Event Title:	10th International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO 2023)
Additional Information:	Published in: Rojas, Ignacio, Valenzuela, Olga, Rojas Ruiz, Fernando, Herrera, Luis Javier and Ortuño, Francisco (eds.) (2023) Bioinformatics and Biomedical Engineering : 10th International Work-Conference, IWBBIO 2023, Meloneras, Gran Canaria, Spain, July 12–14, 2023, Proceedings, Part II. Cham, Switzerland : Springer. pp. 42-55. (Lecture Notes in Computer Science, vol. 13920) Series ISSN (print) 0302-9743 Series ISSN (online) 1611-3349 ISBN (print) 9783031349591 ISBN (online) 9783031349607.
Research Area:	Research Areas > Computer science and informatics
Faculty, School or Research Centre:	Faculty of Science, Engineering and Computing Faculty of Science, Engineering and Computing > School of Computer Science and Mathematics
Date Deposited:	20 Jul 2023 09:31
Last Modified:	29 Jun 2024 02:05
DOI:	https://doi.org/10.1007/978-3-031-34960-7_4
URI:	https://eprints.kingston.ac.uk/id/eprint/54222

Actions (Repository Editors)

Item Control Page