CMBSB
Computational Methods in Bioinformatics and Systems Biology
The success of bioinformatics in recent years has been prompted by research in molecular biology and molecular medicine in initiatives like the human genome project. These initiatives gave rise to an exponential increase in the volume and diversification of data, including protein and gene data, nucleotide sequences and biomedical literature.
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 modelling, 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 Artificial Intelligence (AI) techniques.
In fact, these methods have been helping in tasks related to knowledge discovery, modelling and optimization tasks, aiming at the development of computational models so that the response of biological complex systems to any perturbation can be predicted. Hence, this workshop brings the opportunity to discuss applications of AI with an interdisciplinary character, exploring the interactions between sub-areas of AI, Bioinformatics and Systems Biology.
Topics of Interest
Computational areas of interest include, but are not limited to:
- Knowledge Discovery and Data Mining techniques for the Analysis of high-throughput biological data (trancriptomics, proteomics, metabolomics, fluxomics)
- Text Mining and Language Processing;
- Machine Learning and Pattern Recognition;
- Rough, Fuzzy and Hybrid Techniques;
- Hidden Markov Models;
- Bayesian Approaches;
- Artificial Neural Networks;
- Support Vector Machines;
- Evolutionary Computing;
- Non-linear dynamical analysis methods and Intelligent signal processing;
- Feature selection
Biological areas of interest include, but are not limited to:
- Sequence analysis, comparison and alignment methods;
- Motif, gene and signal recognition;
- Molecular evolution, phylogenetics and phylogenomics;
- Determination or prediction of the structure of RNA and protein in two and three dimensions;
- DNA twisting and folding;
- Gene expression and gene regulatory networks;
- Deduction of metabolic pathways;
- Microarray design and analysis;
- Proteomics;
- Functional genomics;
- Molecular docking and drug design;
- Computational problems in genetics such as linkage and QTL analysis, linkage disequilibrium analysis in populations, and haplotype determination;
- Molecular and cellular interactions;
- Emergence of properties in complex biological systems;
- Visualization of biological systems and networks;
- Data and software integration;
- In silico optimization of biological systems;
- Metabolic engineering applications;
- Cell simulation and modelling;
- Metabolic, regulatory and signalling networks: properties, dynamics, inference and reverse engineering.
Organising Committee
- Miguel Rocha, Universidade do Minho, Portugal
- Rui Camacho, Universidade do Porto, Portugal
- Florentino Fdez-Riverola, Universidad de Vigo, Spain
Contact
mrocha[at]di[.]uminho[.]pt
Program Committee
- Alexessander Alves, Imperial College, UK
- Alípio Jorge, LIAAD/ FEP, Portugal
- André Carvalho, Univ. São Paulo São Carlos, Brasil
- Arlo Zan Randall, Univ. Califórnia Irvine, USA
- Chris Bystroff, Rensselaer Polytechnic Institute, USA
- Elaine Holmes, Imperial College, UK
- Enrique C. Pelaez, Fichuvi, Spain
- Eugénio C. Ferreira, IBB/CEB, Univ. Minho, Portugal
- Eva Iglesias, Univ. Vigo, Spain
- Fazel Famili, NRC Inst. for Inform. Technology, Canada
- Fernando Diaz-Gomez, Univ. Valladolid, Spain
- Francisco Couto, FCUL, Univ. Lisboa, Portugal
- Hasan Jamil, Wayne State Univ., USA
- Ines Dutra, CRACS/ FCUP, Portugal
- Isabel Rocha, IBB/CEB, Univ. Minho, Portugal
- Jorge Vieira, IBMC, Porto, Portugal
- José Mendez-Reboredo, , Univ. Vigo, Spain
- Kiran Patil, Biocentrum, DTU, Denmark
- Lourdes Borrajo, Univ. Vigo, Spain
- Luc Dehaspe, PharmaDM, Belgium
- Luis Rocha, Indiana University, USA
- Marie-France Sagot, Inria Rhone-Alpes, Un. Claude Bernard, France
- Mário Silva, FCUL, Univ. Lisboa, Portugal
- Mohammed Zaki, Rensselaer Polytechnic Institute, USA
- Nuno Fonseca, IBMC, Porto, Portugal
- Paulo Azevedo, CCTC, Univ. Minho, Portugal
- Pavel Brazdil, LIAAD, Univ. Porto, Portugal
- Philip Bourne, Univ. California San Diego
- Pierre Baldi, Univ. California Irvine, USA
- Reyes Pavon, Univ. Vigo, Spain
- Rosalia Laza, Univ. Vigo, Spain
- Rui Mendes, CCTC, Univ. Minho, Portugal
- Santiago Schnell, Indiana State University, USA
- Timothy Ebbels, Imperial College, UK
- Vítor Costa, CRACS/ FCUP, Univ. Porto, Portugal
- Yonghong Peng, Bradford University, UK