EventsMOL2NET'22, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 8th ed.
Event submissions
Published
with-doi10.3390/mol2net-08-13821
This submission belongs to the session 01. CHEMBIO.INFO-08: Cheminfo., Chemom., Comput. Chem. & Bioinfo., Congress München, GR-Cambridge, UK-Ch. Hill, USA, 2022. of the event MOL2NET'22, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 8th ed.
Published date
06 Dec, 2022
Academic Editor
author-avatarHumbert G. Díaz
Citation
Yoan Martínez López, Yanaima Jauriga Ortiz, Ansel Rodríguez González, Juan A. Castillo Garit, Gerardo M. Casanola-Martin, Julio Madera Quintana, Predicting Blood-Brain Barrier Passage using AWV and Machine Learning, in Proceedings of MOL2NET'22, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 8th ed., 1 January–15 January 2023, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-08-13821
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Predicting Blood-Brain Barrier Passage using AWV and Machine Learning

Yoan Martínez López 1
Yanaima Jauriga Ortiz 1
image
Ansel Rodríguez González 2
Juan A. Castillo Garit 3
Gerardo M. Casanola-Martin 4
Julio Madera Quintana 1
1. Department of Computer Sciences, Faculty of Informatics, Camagüey University
2. Unidad de Transferencia Tecnológica, Centro de Investigación Científica y de Educación Superior de Ensenada
3. Unidad de Toxicología Experimental, Universidad de Ciencias Médicas de Villa Clara
4. Department of Coatings and Polymeric Materials, North Dakota State University
Abstract
Keywords
blood-brain barrier
machine learning
atomic weighted vector
MD-LOVIs
Manuscript
BBB-AWV-ML(mol2net).pdf
Poster
BBB-AWV-ML(mol2net).pdf
BBB-AWV-ML(mol2net).pdf