PROTEIN is aimed at innovating in multiple fronts of parallelism, multiobjective metaheuristics (multiobjective optimization, MO), and bioinformatics (mainly, the one based on proteins). For this purpose, we will achieve a relatively ambitious set of contributions at the end of the project, spreading the advances to multiple research niches (informatics, operations research, algorithmics, specialists and applications...), thus increasing the international impact.

First, we want to advance in the use of new technologies and research lines that are presently hot topics at an international level, but from a multiobjective perspective in our case. For this purpose, we will apply parallelism-based technologies (in their different varieties: multi-core computing, cluster computing, hardware accelerators...) to the MO resolution of complex problems, improving their results, performance and throughput. The scalability and efficiency of the parallel techniques developed will be also studied, including comparative studies, and analyzing the possible combination of different parallel technologies and parallelism levels to solve a same problem.

Second, we plan to advance in fundamental research by developing new multiobjective models for metaheuristics, evolutionary and bio-inspired algorithms (including techniques from swarm intelligence) and other procedures capable of solving problems of realistic dimension and complexity. In conclusion, we aim at improving, creating and disseminating advanced MO algorithms. Furthermore, we will study combinations with other techniques (hybridization) using also problem-aware operations.

Third, the tackled problems will not be synthetic/artificial problems, but instead we will address real-world problems from the hot domain of bioinformatics (applied research); and mainly, from the bioinformatics based on proteins, whose problems generally are more complex than the ones based on DNA. This way, the benefits will lie in both methodology and real applications. The goal is to improve the efficiency and effectivity of the solutions to bioinformatics problems with respect to the present state of the art; we aim at showing that the contributed techniques are not only appealing in theory, but also effective and useful for society. These will be important, complex and real problems in the bioinformatics domain, representing by themselves interesting project outcomes.

This project has foreseeable transfers to industry (i.e., EPOs) and focuses on multidisciplinary advances in applications of social interest and in Computer Science (TIN). Furthermore, in order to obtain a higher impact in research, we will also do transfers of the developed techniques to other domains. We will tackle a clear mission for internationalization of the results, with high impact publications, research staff training, organization of conferences and workshops, and special issues in international journals.