Automated Machine Learning Strategies to Damage Identification of Neurofibromatosis Mutations

Number of the records: 1

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SYSNO	0556734
Title	Automated Machine Learning Strategies to Damage Identification of Neurofibromatosis Mutations
Author(s)	Orjuela-Cañón, A. D. (CO) Figueroa-Garcia, J.C. (CO) Neruda, Roman (UIVT-O)_{SAI, RID, ORCID}
Source Title	Proceedings of 20th IEEE International Conference on Machine Learning and Applications ICMLA 2021. S. 1341-1344. - Piscataway : IEEE, 2021 / Wani M. A. ; Sethi I. ; Shi W. ; Qu G. ; Raicu D. S. ; Jin R.
Conference	ICMLA 2021: IEEE International Conference on Machine Learning and Applications /20./, 13.12.2021 - 16.12.2021, Pasadena / Virtual
Document Type	Konferenční příspěvek (zahraniční konf.)
Institutional support	UIVT-O - RVO:67985807
Language	eng
Country	US
Keywords	automatic machine learning * protein sequence * neurofibromatosis * amino-acids
Cooperating institutions	Universidad del Rosario, Bogota (Colombia) Universidad Distrital Francisco José de Caldas, Bogota (Colombia)
URL	http://dx.doi.org/10.1109/ICMLA52953.2021.00217
Permanent Link	http://hdl.handle.net/11104/0330895

Number of the records: 1