<p>Using machine learning to explore the genetics of tobacco addiction: A study of an African American population</p>

Ibrahima Diallo; Ines  Abdeljaoued-Tej; Emna Harigua; Christian Happi; Alia Benkahla

doi:10.7490/f1000research.1120005.1

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Diallo I, Abdeljaoued-Tej I, Harigua E et al. Using machine learning to explore the genetics of tobacco addiction: A study of an African American population [version 1; not peer reviewed]. F1000Research 2024, 13:1389 (poster) (https://doi.org/10.7490/f1000research.1120005.1)

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Using machine learning to explore the genetics of tobacco addiction: A study of an African American population

Ibrahima Diallo¹, Ines Abdeljaoued-Tej², Emna Harigua³, Christian Happi⁴, Alia Benkahla²

Published 19 Nov 2024 (https://doi.org/10.7490/f1000research.1120005.1)

Author Affiliations

¹ Genomics, African Center of Excellence for Genomics of Infectious Diseases, Ede, Osun State, Nigeria
² Laboratory of BioInformatic, bioMathematic and bioStatistic, Institut Pasteur de Tunis, Tunis, Tunisia
³ Laboratory of Molecular Epidemiology and Experimental Pathology, Institut Pasteur de Tunis, Tunis, Tunisia
⁴ Director, African Center of Excellence for Genomics of Infectious Diseases, Ede, Osun State, Nigeria

Copyright © 2024 Diallo I et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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CITE

Published 19 Nov 2024

Using machine learning to explore the genetics of tobacco addiction: A study of an African American population
[version 1; not peer reviewed]

Ibrahima Diallo¹, Ines Abdeljaoued-Tej², Emna Harigua³, Christian Happi⁴, Alia Benkahla²

Author Affiliations

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Bioinformatics and Computational Biology Conference (BBCC) 2024

Abstract

Competing Interests

No competing interests were disclosed

Keywords

SNP, Genomics, Bioinformatics, Machine Learning, Nicotine

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