Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review

Mouhamadou Djima Baranon; Patrick Guge Oloo Weke; Judicael Alladatin; Boni Maxime Ale; Amos Kipkorir Langat

doi:doi:10.11648/j.acm.20241304.11

Research Article |

| Peer-Reviewed

Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review

Mouhamadou Djima Baranon^*

, Patrick Guge Oloo Weke

, Judicael Alladatin

, Boni Maxime Ale

, Amos Kipkorir Langat

Published in Applied and Computational Mathematics (Volume 13, Issue 4)

Received: 20 April 2024 Accepted: 6 May 2024 Published: 5 July 2024

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Abstract

The application of Hidden Markov Models (HMMs) in the study of genetic and neurological disorders has shown significant potential in advancing our understanding and treatment of these conditions. This review assesses 77 papers selected from a pool of 1,105 records to evaluate the use of HMMs in disease research. After the exclusion of duplicate and irrelevant records, the papers were analyzed for their focus on HMM applications and regional representation. A notable deficiency was identified in research across regions such as Africa, South America, and Oceania, emphasizing the need for more diverse and inclusive studies in these areas. Additionally, many studies did not adequately address the role of genetic mutations in the onset and progression of these diseases, revealing a critical research gap that warrants further investigation. Future research efforts should prioritize the examination of mutations to deepen our understanding of how these changes impact the development and progression of genetic and neurological disorders. By addressing these gaps, the scientific community can facilitate the development of more effective and personalized treatments, ultimately enhancing health outcomes on a global scale. Overall, this review highlights the importance of HMMs in this area of research and underscores the necessity of broadening the scope of future studies to include a wider variety of geographical regions and a more comprehensive investigation of genetic mutations.

Published in	Applied and Computational Mathematics (Volume 13, Issue 4)
DOI	10.11648/j.acm.20241304.11
Page(s)	69-82
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Hidden Markov Model, Genetic Disorders, Neurological Disorders, Mutations, Healthcare

References

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Baranon, M. D., Weke, P. G. O., Alladatin, J., Ale, B. M., Langat, A. K. (2024). Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review. Applied and Computational Mathematics, 13(4), 69-82. https://doi.org/10.11648/j.acm.20241304.11

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Baranon, M. D.; Weke, P. G. O.; Alladatin, J.; Ale, B. M.; Langat, A. K. Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review. Appl. Comput. Math. 2024, 13(4), 69-82. doi: 10.11648/j.acm.20241304.11

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Baranon MD, Weke PGO, Alladatin J, Ale BM, Langat AK. Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review. Appl Comput Math. 2024;13(4):69-82. doi: 10.11648/j.acm.20241304.11

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@article{10.11648/j.acm.20241304.11,
  author = {Mouhamadou Djima Baranon and Patrick Guge Oloo Weke and Judicael Alladatin and Boni Maxime Ale and Amos Kipkorir Langat},
  title = {Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review},
  journal = {Applied and Computational Mathematics},
  volume = {13},
  number = {4},
  pages = {69-82},
  doi = {10.11648/j.acm.20241304.11},
  url = {https://doi.org/10.11648/j.acm.20241304.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acm.20241304.11},
  abstract = {The application of Hidden Markov Models (HMMs) in the study of genetic and neurological disorders has shown significant potential in advancing our understanding and treatment of these conditions. This review assesses 77 papers selected from a pool of 1,105 records to evaluate the use of HMMs in disease research. After the exclusion of duplicate and irrelevant records, the papers were analyzed for their focus on HMM applications and regional representation. A notable deficiency was identified in research across regions such as Africa, South America, and Oceania, emphasizing the need for more diverse and inclusive studies in these areas. Additionally, many studies did not adequately address the role of genetic mutations in the onset and progression of these diseases, revealing a critical research gap that warrants further investigation. Future research efforts should prioritize the examination of mutations to deepen our understanding of how these changes impact the development and progression of genetic and neurological disorders. By addressing these gaps, the scientific community can facilitate the development of more effective and personalized treatments, ultimately enhancing health outcomes on a global scale. Overall, this review highlights the importance of HMMs in this area of research and underscores the necessity of broadening the scope of future studies to include a wider variety of geographical regions and a more comprehensive investigation of genetic mutations.},
 year = {2024}
}

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Mouhamadou Djima Baranon

Department of Mathematics and Statistics, Pan African University Institute for Basic Sciences, Technology, and Innovation (PAUSTI), Nairobi, Kenya; Ecole Nationale de Statistique, de Planification et de Demographie (ENSPD), Universite de Parakou, Parakou, Benin

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http://orcid.org/0009-0005-7783-653X
Patrick Guge Oloo Weke

Ecole Nationale de Statistique, de Planification et de Demographie (ENSPD), Universite de Parakou, Parakou, Benin

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http://orcid.org/0000-0002-6283-4567
Judicael Alladatin

School of Mathematics, University of Nairobi, Nairobi, Kenya; Faculte des Sciences de l’Education, Universite de Montreal, Montreal, Canada

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http://orcid.org/0000-0001-7230-9953
Boni Maxime Ale

Department of Education, Consortium Siabanni Pour la Formation, la Recherche et le Developpement (Consortium SFR-D), Abomey-Calavi, Benin; Institute of Tropical and Infectious Diseases, University of Nairobi, Nairobi, Kenya; Strathmore University Business School, Strathmore University, Nairobi, Kenya; Department of Health Research, Holo Global Health Research Institute, Nairobi, Kenya; Department of Health Research, Health Data Acumen, Nairobi, Kenya; College of Health Sciences, MOI University, Nairobi, Kenya

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http://orcid.org/0000-0002-8449-3310
Amos Kipkorir Langat

Department of Mathematics and Statistics, Pan African University Institute for Basic Sciences, Technology, and Innovation (PAUSTI), Nairobi, Kenya

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http://orcid.org/0000-0002-7813-6835

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APA Style

Baranon, M. D., Weke, P. G. O., Alladatin, J., Ale, B. M., Langat, A. K. (2024). Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review. Applied and Computational Mathematics, 13(4), 69-82. https://doi.org/10.11648/j.acm.20241304.11

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ACS Style

Baranon, M. D.; Weke, P. G. O.; Alladatin, J.; Ale, B. M.; Langat, A. K. Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review. Appl. Comput. Math. 2024, 13(4), 69-82. doi: 10.11648/j.acm.20241304.11

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AMA Style

Baranon MD, Weke PGO, Alladatin J, Ale BM, Langat AK. Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review. Appl Comput Math. 2024;13(4):69-82. doi: 10.11648/j.acm.20241304.11

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@article{10.11648/j.acm.20241304.11,
  author = {Mouhamadou Djima Baranon and Patrick Guge Oloo Weke and Judicael Alladatin and Boni Maxime Ale and Amos Kipkorir Langat},
  title = {Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review},
  journal = {Applied and Computational Mathematics},
  volume = {13},
  number = {4},
  pages = {69-82},
  doi = {10.11648/j.acm.20241304.11},
  url = {https://doi.org/10.11648/j.acm.20241304.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acm.20241304.11},
  abstract = {The application of Hidden Markov Models (HMMs) in the study of genetic and neurological disorders has shown significant potential in advancing our understanding and treatment of these conditions. This review assesses 77 papers selected from a pool of 1,105 records to evaluate the use of HMMs in disease research. After the exclusion of duplicate and irrelevant records, the papers were analyzed for their focus on HMM applications and regional representation. A notable deficiency was identified in research across regions such as Africa, South America, and Oceania, emphasizing the need for more diverse and inclusive studies in these areas. Additionally, many studies did not adequately address the role of genetic mutations in the onset and progression of these diseases, revealing a critical research gap that warrants further investigation. Future research efforts should prioritize the examination of mutations to deepen our understanding of how these changes impact the development and progression of genetic and neurological disorders. By addressing these gaps, the scientific community can facilitate the development of more effective and personalized treatments, ultimately enhancing health outcomes on a global scale. Overall, this review highlights the importance of HMMs in this area of research and underscores the necessity of broadening the scope of future studies to include a wider variety of geographical regions and a more comprehensive investigation of genetic mutations.},
 year = {2024}
}

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TY  - JOUR
T1  - Exploring Hidden Markov Models in the Context of Genetic Disorders, and Related Conditions: A Systematic Review
AU  - Mouhamadou Djima Baranon
AU  - Patrick Guge Oloo Weke
AU  - Judicael Alladatin
AU  - Boni Maxime Ale
AU  - Amos Kipkorir Langat
Y1  - 2024/07/05
PY  - 2024
N1  - https://doi.org/10.11648/j.acm.20241304.11
DO  - 10.11648/j.acm.20241304.11
T2  - Applied and Computational Mathematics
JF  - Applied and Computational Mathematics
JO  - Applied and Computational Mathematics
SP  - 69
EP  - 82
PB  - Science Publishing Group
SN  - 2328-5613
UR  - https://doi.org/10.11648/j.acm.20241304.11
AB  - The application of Hidden Markov Models (HMMs) in the study of genetic and neurological disorders has shown significant potential in advancing our understanding and treatment of these conditions. This review assesses 77 papers selected from a pool of 1,105 records to evaluate the use of HMMs in disease research. After the exclusion of duplicate and irrelevant records, the papers were analyzed for their focus on HMM applications and regional representation. A notable deficiency was identified in research across regions such as Africa, South America, and Oceania, emphasizing the need for more diverse and inclusive studies in these areas. Additionally, many studies did not adequately address the role of genetic mutations in the onset and progression of these diseases, revealing a critical research gap that warrants further investigation. Future research efforts should prioritize the examination of mutations to deepen our understanding of how these changes impact the development and progression of genetic and neurological disorders. By addressing these gaps, the scientific community can facilitate the development of more effective and personalized treatments, ultimately enhancing health outcomes on a global scale. Overall, this review highlights the importance of HMMs in this area of research and underscores the necessity of broadening the scope of future studies to include a wider variety of geographical regions and a more comprehensive investigation of genetic mutations.
VL  - 13
IS  - 4
ER  -

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