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OLDBB-IEEE-CEC 2019 : IEEE CEC 2019: Special Session on “Optimization, Learning, and Decision-Making in Bioinformatics and Bioengineering” | |||||||||||
Link: http://cec2019.org/papers.html | |||||||||||
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Call For Papers | |||||||||||
Scope and topics
Bioinformatics and Bioengineering (BB) are interdisciplinary scientific fields involving many branches of computer science, engineering, mathematics, and statistics. Bioinformatics is concerned with the development and application of computational methods for the modelling, retrieving and analysis of biological data, whilst Bioengineering is the application of engineering techniques to biology so as to create usable and economically viable products. Bioinformatics and Bioengineering are relatively new fields in which many challenges and issues can be formulated as (single and multiobjective) optimization problems. These problems span from traditional problems, such as the optimization of biochemical processes, construction of gene regulatory networks, protein structure alignment and prediction, to more modern problems, such as directed evolution, drug design, experimental design, and optimization of manufacturing processes, material and equipment. The main aim of this special session is to bring together both experts and new-comers working on Optimization, Learning and Decision-Making in Bioinformatics and Bioengineering to discuss new and exciting issues in this area. The topics are, but not limited to, the following • (Single and multiobjective) optimization techniques for Bioinformatics and Bioengineering (BB) problems • Decision-making and MCDM techniques for BB problems • Experimental optimization of BB problems • Learning in/from the optimization of BB problems • Data-driven optimization for BB problems • Tuning of optimization, learning and decision-making techniques for BB problems • Emerging topics in BB o Novel applications o Novel challenges o Interactive visualization o Predictive fitness landscape design o Many-objective optimization o Ecoinformatics o Side effect machines and other kernel representations for sequence analysis o Biomedical data modelling and mining Organizers Joseph A. Brown (j.brown@innopolis.ru), Innopolis University, Russia Gonzalo Ruz (gonzalo.ruz@uai.cl), Universidad Adolfo Ibanez, Chile Daniel Ashlock (dashlock@uoguelph.ca), University of Guelph, Canada Richard Allmendinger (richard.allmendinger@manchester.ac.uk), The University of Manchester, UK More information about the session can be found at https://tinyurl.com/OLDBB-IEEE-CEC-2019. Feel free to contact the session organizers if you have any further questions. Best wishes, Joseph, Gonzalo, Daniel, and Richard |
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