Computational Methods in Bioinformatics and Systems Biology
The success of bioinformatics in recent years has been prompted by research in molecular biology and medicine in initiatives like the human genome project. These initiatives gave rise to an enormous increase in the volume and diversification of data, including protein and genomic sequences, high-throughput experimental and biomedical literature. The widespread availability of low-cost, full genome sequencing, will introduce new challenges to bioinformatics as a key field to enable personalized medicine. New methods are needed to realize the potential of personalized medicine: (i) processing large-scale robust genomic data; (ii) interpreting the functional effect and the impact of genomic variation; (iii) integrating systems data to relate complex genetic interactions with phenotypes; and (iv) translating these discoveries into medical practice.
Systems Biology is a related field, devoted mainly to efforts in cell modeling, that requires the coordinated efforts of biological researchers with those related to data analysis, mathematical model-ling, computer simulation and optimization.
The accumulation and exploitation of large-scale databases prompts for new computational technologies 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 experimental data, are based on Artificial Intelligence (AI) techniques.
In fact, these methods have been helping in tasks related to knowledge discovery, model-ling 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
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;
- Inference/ reconstruction of metabolic/ regulatory networks or models;
- Analysis of high-throughput biological data (trancriptomics, proteomics, metabolomics, fluxomics);
- Functional genomics;
- Molecular docking and drug design;
- Problems in population genetics such as linkage and QTL analysis, linkage disequilibrium analysis in populations, and haplotype determination;
- Metabolic engineering applications.
Computational areas of interest include, but are not limited to:
- Knowledge Discovery and Data Mining techniques;
- 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.
Submissions must be original and not published elsewhere. Papers should not exceed twelve (12) pages in length and must adhere to the formatting instructions of the conference. Each submission will be peer reviewed by at least three members of the Program Committee. The reviewing process is double blind, so authors should remove names and affiliations from the submitted papers, and must take reasonable care to assure anonymity during the review process. References to own work may be included in the paper, as long as referred to in the third person. Acceptance will be based on the paper’s significance, technical quality, clarity, relevance and originality.
All accepted papers will be published by Springer in a volume of the LNAI-Lecture Notes in Artificial Intelligence series (indexed by the Thomson ISI Web of Knowledge). The number of pages of the accepted contributions has the following limits:
- Full Regular Papers: Contributions accepted as full papers should contain from 10 to 12 pages in its final version, according to the LNAI series formatting instructions. Extraordinarily, other two additional pages could be considered with a supplementary fee.
- Short Papers: Contributions accepted as short papers should contain from 4 to 6 pages in its final version, according to the LNAI series formatting instructions.
All accepted papers must be presented orally the conference by one of the authors and at least one author of each accepted paper must register for the conference.
Deadline for paper submission: March 23, 2015
Notification of paper acceptance: 27, April, 2015
Camera-ready papers due: 1, June, 2015
Conference dates: September 8-11, 2015
Department of Informatics, University of Minho, Braga, Portugal
Email: mrocha (at) di.uminho.pt
LIAAD & DEI – FEUP, Porto, Portugal
Email: rcamacho (at) fe.up.pt
Department of Informatics, Instituto Superior Técnico, Technical University of Lisbon, Portugal
Email: smadeira (at) kdbio.inesc-id.pt
José Luis Oliveira
DETI – University of Aveiro, Aveiro, Portugal
Email: jlo (at) ua.pt
Francisco Couto Faculty of Sciences, University of Lisbon, Portugal
Susana Vinga Centre for Intelligent Systems, IDMEC-LAETA, IST-UL, Portugal
Marie-France Sagot INRIA Grenoble Rhône-Alpes and Université de Lyon 1, Villeurbanne, France
Alexessander Couto Alves Imperial College London, UK
Alexandre P. Francisco INESC-ID CSE Dept, IST, Tech Univ of Lisbon, Portugal
Vítor Santos Costa Universidade do Porto, Portugal
Mário J. Silva INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, Portugal
Fernando Diaz University of Valladolid, Spain
Sérgio Matos IEETA, Universidade de Aveiro, Portugal
Paulo Azevedo Universidade do Minho, Portugal
Rui Mendes Universidade do Minho, Portugal
Inês Dutra CRACS INES-TEC LA, Faculdade de Ciências, Universidade do Porto,Portugal
Nuno A. Fonseca EMBL-EBI, European Bioinformatics Institute, UK
Florentino Fdez-Riverola University of Vigo, Spain
André Carvalho USP, Brazil
Alexandra Carvalho IT/ IST, Portugal
Arlindo Oliveira IST/INESC-ID and Cadence Research Laboratories, Portugal
Ross King University of Manchester, UK
Luiís M. Rocha Indiana University, USA