Guimarães (Portugal) - Hybrid

12th-14th July, 2023

17th International Conference on Practical Applications of Computational Biology & Bioinformatics

Guimarães (Portugal) | 12th-14th July, 2023 |

The success of Bioinformatics in recent years has been prompted by research in Molecular Biology and Molecular Medicine in several initiatives. These initiatives gave rise to an exponential increase in the volume and diversification of data, including nucleotide and protein sequences and annotations, high-throughput experimental data, biomedical literature, among many others.

Systems Biology is a related research area that has been replacing the reductionist view that dominated Biology research in the last decades, requiring the coordinated efforts of biological researchers with those related to data analysis, mathematical modeling, computer simulation and optimization.

The accumulation and exploitation of large-scale data bases prompts for new computational technology and for research into these issues. In this context, many widely successful computational models and tools used by biologists in these initiatives, such as clustering and classification methods for gene expression data, are based on Computer Science/ Artificial Intelligence (CS/AI) techniques. In fact, these methods have been helping in tasks related to knowledge discovery, modeling and optimization tasks, aiming at the development of computational models so that the response of biological complex systems to any perturbation can be predicted.

The 17th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB) aims to promote the interaction among the scientific community to discuss applications of CS/AI with an interdisciplinary character, exploring the interactions between sub-areas of CS/AI, Bioinformatics, Chemoinformatics and Systems Biology.

Brand new ideas in these fields are sought, as well as substantial and relevant revisions and actualizations of previously presented work, project summaries and PhD thesis presented or not.

The proceedings of the previous edition are available:


Special Issues

The Scientific Committee of the co-located conferences in collaboration with the guest editors will select the best papers from those presented in the conferences to be considered for publication in the following Special Issues:

Authors of selected papers from SSCt2023 will be invited to submit an extended and improved version to a Special Issue published in ADCAIJ (ISSN: 2255-2863, JCI (2021): 0,05(Q4)) indexed in DOAJ, ProQuest, Scholar, WorldCat, Dialnet, Sherpa ROMEO, Dulcinea, UlrichWeb, Emerging Sources Citation Index of Thomson Reuters, BASE y Academic Journals Database.

To Be Updated

PACBB'22 awards


“The NAD interactome - Identification of putative new NAD-binding proteins” by Sara Duarte-Pereira, Sérgio Matos, José Luís Oliveira and Raquel M. Silva


“The Covid-19 Decision Support System (C19DSS)” by Pierpaolo Vittorini, Nicolò Casano, Gaia Sinatti, Silvano Jr Santini and Clara Balsano

2022 Electronics MDPI Best papers

MDPI Electronics

"Nature-inspired algorithms and individual decision-making" by Juan Manuel Sánchez-Cartas and Inés Pérez-Sancristóbal

"Real-time algorithm recommendation using meta-learning" by Guilherme Palumbo, Miguel Guimarães, Davide Carneiro, Paulo Novais, and Victor Alves

"A Flexible Agent Architecture in SPADE" by Javier Palanca, Jaime A. Rincon, Carlos Carrascosa, Vicente Julian, and Andres Terrasa

"A Hybrid Model to Classify Physical Activity Profiles" by Vítor Crista, Diogo Martinho, Jorge Meira, João Carneiro, Juan Corchado and Goreti Marreiros

2022 Systems MDPI Best Papers


First Award: "The use of corporate architecture in planning and automation of production processes" by Zbigniew Juzoń, Jarosław Wikarek, and Paweł Sitek

Second Award: "Data Synchronization in Distributed Simulation of Multi-Agent Systems" by Paul Breugnot, Bénédicte Herrmann, Christophe Lang, and Laurent Philippe

Third Award: "The case for Somalia and Sudan debt relief. Insights from the evolution of HIPC countries using machine learning methods" by Tony Persico