Role of Artificial Intelligence in Bioinformatics and Information Extraction Systems

Maram Y. Al-Safarini; Rania A. Baashirah

doi:10.31181/dmame8120251376

Authors

Maram Y. Al-Safarini Computer Science Department, Zarqa University, Jordan https://orcid.org/0000-0002-4899-4062
Rania A. Baashirah Software Engineering Department, University of Business & Technology https://orcid.org/0000-0001-6877-6698

DOI:

https://doi.org/10.31181/dmame8120251376

Keywords:

Artificial Intelligence, Information Extraction Systems, Bioinformatics.

Abstract

Artificial Intelligence (AI) is transforming numerous domains, including bioinformatics and information extraction systems, by advancing data processing capabilities, enhancing precision, and facilitating automation. The primary aim of this research is to examine the function of AI within the realms of bioinformatics and information extraction through a combination of quantitative and qualitative approaches. The quantitative component involved a sample of 152 participants, recognised as experts in bioinformatics and data science. The survey findings underscore the prevalent integration of AI in bioinformatics, particularly through the utilisation of reinforcement learning, neural networks, and natural language processing (NLP). Furthermore, AI substantially improves the analysis of biological data; however, it encounters challenges such as limited model interpretability and the lack of data standardisation. Notwithstanding these obstacles, AI-driven innovations in disease prognosis, personalised healthcare, and pharmaceutical development are anticipated to shape the future trajectory of bioinformatics. The qualitative findings, derived through thematic analysis encompassing core themes and sub-themes, reveal that AI significantly contributes to accelerating and refining information extraction processes. Technologies such as machine learning, NLP, and neural networks are instrumental in enhancing data processing efficiency. Nonetheless, issues such as inadequate data quality, elevated computational expenses, and the intricacy of AI models remain persistent. Looking ahead, AI is projected to integrate more effectively with big data infrastructures, enable real-time information extraction, and deliver increasingly tailored solutions. The study concludes with several policy recommendations to guide future implementation strategies.

Downloads

Download data is not yet available.

References

[1] Lewis, J., & Bartlett, A. (2013). Inscribing a discipline: Tensions in the field of bioinformatics. New Genetics and Society, 32(3), 243-263. https://doi.org/10.1080/14636778.2013.773172

[2] Zakarya, M., Rahman, I. U., Dilawar, N., & Sadaf, R. (2011). An integrative study on bioinformatics computing concepts, issues and problems. International Journal of Computer Science Issues (IJCSI), 8(6), 330. https://www.proquest.com/openview/13eb7a7dafc9c65ffa43bc9f09e96e7c/1?cbl=55228&pq-origsite=gscholar

[3] Kashyap, H., Ahmed, H. A., Hoque, N., Roy, S., & Bhattacharyya, D. K. (2015). Big data analytics in bioinformatics: A machine learning perspective. arXiv preprint arXiv:1506.05101. https://doi.org/10.48550/arXiv.1506.05101

[4] Can, T. (2014). Introduction to bioinformatics. miRNomics: MicroRNA biology and computational analysis, 51-71. https://doi.org/10.1007/978-1-62703-748-8_4

[5] Gauthier, J., Vincent, A. T., Charette, S. J., & Derome, N. (2019). A brief history of bioinformatics. Briefings in bioinformatics, 20(6), 1981-1996. https://doi.org/10.1093/bib/bby063

[6] Maojo, V., & Kulikowski, C. A. (2003). Bioinformatics and medical informatics: collaborations on the road to genomic medicine? Journal of the American Medical Informatics Association, 10(6), 515-522. https://doi.org/10.1197/jamia.M1305

[7] Lee, D., & Yoon, S. N. (2021). Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges. International journal of environmental research and public health, 18(1), 271. https://doi.org/10.3390/ijerph18010271

[8] Abbas Khan, M., Khan, H., Omer, M. F., Ullah, I., & Yasir, M. (2024). Impact of artificial intelligence on the global economy and technology advancements. In Artificial General Intelligence (AGI) Security: Smart Applications and Sustainable Technologies (pp. 147-180). Springer. https://doi.org/10.1007/978-981-97-3222-7_7

[9] Hossain, K. A. (2023). Analysis of present and future use ofartificial intelligence (ai) in line of fouth industrial revolution (4ir). Scientific Research Journal, 11, 1-50. http://dx.doi.org/10.31364/SCIRJ/v11.i8.2023.P0823954

[10] Oosthuizen, R. M. (2022). The fourth industrial revolution–smart technology, artificial intelligence, robotics and algorithms: Industrial psychologists in future workplaces. Frontiers in artificial intelligence, 5, 913168. https://doi.org/10.3389/frai.2022.913168

[11] Keedwell, E., & Narayanan, A. (2005). Intelligent bioinformatics : the application of artificial intelligence techniques to bioinformatics problems. Wiley. https://cir.nii.ac.jp/crid/1130000794616810624

[12] Jirotka, M., Lee, C. P., & Olson, G. M. (2013). Supporting scientific collaboration: Methods, tools and concepts. Computer Supported Cooperative Work (CSCW), 22, 667-715. https://doi.org/10.1007/s10606-012-9184-0

[13] Outeiral, C., Strahm, M., Shi, J., Morris, G. M., Benjamin, S. C., & Deane, C. M. (2021). The prospects of quantum computing in computational molecular biology. Wiley Interdisciplinary Reviews: Computational Molecular Science, 11(1), e1481. https://doi.org/10.1002/wcms.1481

[14] Ezziane, Z. (2006). Applications of artificial intelligence in bioinformatics: A review. Expert Systems with Applications, 30(1), 2-10. https://doi.org/10.1016/j.eswa.2005.09.042

[15] Nicolas, J. (2020). Artificial intelligence and bioinformatics. A Guided Tour of Artificial Intelligence Research: Volume III: Interfaces and Applications of Artificial Intelligence, 209-264. https://doi.org/10.1007/978-3-030-06170-8_7

[16] Jamialahmadi, H., Khalili-Tanha, G., Nazari, E., & Rezaei-Tavirani, M. (2024). Artificial intelligence and bioinformatics: a journey from traditional techniques to smart approaches. Gastroenterology and Hepatology from Bed to Bench, 17(3), 241. https://doi.org/10.22037/ghfbb.v17i3.2977

[17] Valentini, G., Tagliaferri, R., & Masulli, F. (2009). Computational intelligence and machine learning in bioinformatics. In (Vol. 45, pp. 91-96): Elsevier. https://doi.org/10.1016/j.artmed.2008.08.014

[18] Shree, D. V., Kumar, B. S., Ganesan, V., Umadevi, N., Sivaraman, M., & Sumitha, J. (2024). The Role of Artificial Intelligence and Machine Learning Methodologies in Bioinformatics. 2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 194-201. https://doi.org/10.1109/ICAAIC60222.2024.10575828

[19] Karunarathna, I., Gunasena, P., Hapuarachchi, T., & Gunathilake, S. (2024). Comprehensive data collection: Methods, challenges, and the importance of accuracy. Uva Clinical Research, 1-24. http://dx.doi.org/10.13140/RG.2.2.13134.47689

[20] Onwuegbuzie, A. J., & Leech, N. L. (2005). On becoming a pragmatic researcher: The importance of combining quantitative and qualitative research methodologies. International journal of social research methodology, 8(5), 375-387. https://doi.org/10.1080/13645570500402447

[21] Taherdoost, H. (2022). What are different research approaches? Comprehensive review of qualitative, quantitative, and mixed method research, their applications, types, and limitations. Journal of Management Science & Engineering Research, 5(1), 53-63. http://doi.org/10.30564/jmser.v5i1.4538ff.ffhal-03741840

[22] Ahmed, U., Zin, M., & Majid, A. (2016). Impact of Intention and Technology Awareness on Transport Industry’s E-service: Evidence from an Emerging Economy. 산경연구논집 (IJIDB), 7 (3), 13-18. In. https://db.koreascholar.com/article/Detail/316838

[23] Smith, K. A., Morassaei, S., Ruco, A., Bola, R., Currie, K. L., Cooper, N., & Di Prospero, L. (2022). An evaluation of the impact for healthcare professionals after a leadership innovation fellowship program. Journal of Medical Imaging and Radiation Sciences, 53(4), S137-S144.http://doi.org/ 10.1016/j.jmir.2022.09.004