Accepted paper at IEEE Transactions on Cybernetics

The paper entitled Monodirectional tissue P systems with promoters, authored by B. Song, X. Zeng, M. Jiang, M.J. Pérez-Jiménez, has been accepted in the journal IEEE Transactions on Cybernetics, which has a JCR impact factor of 11.079. It can be accessed here.

The project Allen has been selected for the next LHCb update

The project Allen, co-leaded by Daniel Hugo Cámpora-Pérez, Roel Aaij and Dorothea vom Bruch is being adopted as the new HLT 1 standard, giving way to the computing power of graphic units to parallelize the process of the data processing. This project was materialized in the PhD thesis of Daniel, co-supervised by Agustín Riscos-Núñez and Niko Neufeld.
You can read more in the press appearances page of the group.

COVID-19 contribution

The Research Group on Natural Computing is working on contributions to the current situation caused by Covid-19, mainly based on our previous work on a SIR model for pandemics using PDP systems and by extracting ideas employed for virus machines (computing with viruses):

Welcome to the Research Group on Natural Computing Site

(What is Natural Computing? click here for more information)

The Research Group on Natural Computing (RGNC, www.gcn.us.es) belongs to the Department of Computer Science and Artificial Intelligence of the University of Seville. The RGNC consists of 11 members, and is headed by Agustín Riscos-Núñez, associate professor in Computer Science and Artificial Intelligence. Moreover, Mario J. Pérez-Jiménez is the founder of the group, who is currently a Professor Emeritus at the University of Seville, a full professor in Computer Science and Artificial Intelligence, and a numerary member of the Academia Europaea (The Academy of Europe), section Informatics.

The research activities of the RGNC focus on the interplay between Computer Science, Mathematics, Biology and Population Dynamics. Specifically, it focuses on the development of enabling technologies based on bio-inspired formal methods, more precisely Membrane Computing, a recent branch of Natural Computing that provides an abstraction of the living eukaryotic cell.

Research lines:

Bio-inspired Models of Computation

Application of new computational paradigms
inspired by living Nature to the setting of
novel frontiers in efficiency. Characterization of
the conjecture P≠NP in these unconventional
models of computation.

Ecological Modelling

Development of probabilistic and multi-
environment models of real ecosystems based on
bio-inspired models of computation.
Development of software tools that allow
ecologists to easily use our models.

High Performance Computing with
Graphics Processing Units (GPUs)

Development of high-performance simulation
tools for bio-inspired models by using massively
parallel architectures such as GPUs.
Management of a GPU cluster inside the group.

Computational Systems Biology

Application of bio-inspired models to the
modelling of cellular systems such as signalling
pathways involved in the uncontrolled
proliferation of tumour cells and in the
communication between bacterial cells.

Engineering-related models

Wide range of applications to various engineering areas,
including engineering optimization, power system fault diagnosis, controller design of mobile
robots, or complex systems involving data modeling and process interactions.

This research group is funded by: