Multiobjective Optimization in Bioinformatics and Computational Biology
Open accessAbstract
This paper reviews the application of multiobjective optimization in the fields of bioinformatics and computational biology. A survey of existing work, organized by application area, forms the main body of the review, following an introduction to the key concepts in multiobjective optimization. An original contribution of the review is the identification of five distinct "contexts," giving rise to multiple objectives: These are used to explain the reasons behind the use of multiobjective optimization in each application area and also to point the way to potential future uses of the technique.
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Solving multiobjective problems is a huge challenge as demonstrated in robotics, bioinformatics, energy and power.
“Despite the merits of bioinspired optimizers, solving multiobjective problems is a huge challenge as demonstrated in different application domains (e.g. robotics [66], bioinformatics [67], energy and power [68]).”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [68]
Cites
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970 · see citing works
The elements of statistical learning: Data mining, inference, and prediction
Franklin, J. (2005) · The Mathematical Intelligencer · doi:10.1007/bf02985802 · Cited by 1,400 · see citing works
An improved protein decoy set for testing energy functions for protein structure prediction
Tsai, J., Bonneau, R., Morozov, A. V., Kuhlman, B., Rohl, C. A., & Baker, D. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10454 · Cited by 158 · see citing works
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Kell, D. B. (2010) · Archives of Toxicology · doi:10.1007/s00204-010-0577-x · Cited by 361 · see citing works
Self-citationOptimization in computational systems biology
Banga, J. R. (2008) · BMC Systems Biology · doi:10.1186/1752-0509-2-47 · Cited by 278 · see citing works
Applications and Challenges of Artificial Intelligence in Space Missions
Oche, P. A., Ewa, G. A., & Ibekwe, N. (2024) · IEEE Access · doi:10.1109/access.2021.3132500 · Cited by 68 · see citing works
- Authors
- Handl, J., Kell, D. B., & Knowles, J.
- Affiliations
- University of Manchester (GB)
- Venue
- IEEE/ACM Transactions on Computational Biology and Bioinformatics
- Published
- 2007-04
- Volume
- 4
- Issue
- 2
- Pages
- 279-292
- ISSN
- 1545-5963 (ISSN-L)
- 1557-9964
- 2374-0043
- OpenAlex
- W1970424517
- Cited by
- 308
- References
- 3
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 8 · 2023: 8 · 2022: 9 · 2021: 6 · 2020: 32 · 2019: 11 · 2018: 20 · 2017: 21 · 2016: 19 · 2015: 21 · 2014: 18 · 2013: 16 · 2012: 23
- FWCI
- 1.66
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- IEEE Transactions on Computational Biology and Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Research Explorer (The University of Manchester) (publishedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Multi-Objective Optimization Algorithms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- multi-objective optimization, bioinformatics, computational biology, multiple objectives
- MeSH terms
- Algorithms, Artificial Intelligence, Models, Biological, Pattern Recognition, Automated, Sequence Analysis, Computational Biology, Gene Expression Profiling
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