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.
PACBB welcomes contributions reporting substantial, original and previously unpublished work in all areas of Bioinformatics, Chemoinformatics and Systems Biology. The papers can be presented from a formal, methodological, technical or applied point of view.
The aim of the Doctoral Consortium is to provide a framework as part of which students can present their ongoing research work and meet other students and researchers and obtain feedback on lines of research for the future.
The Doctoral Consortium is intended for students who have a specific research proposal and some preliminary results, but who are still far from completing their dissertation.
All proposals submitted to the Doctoral Consortium will undergo a thorough reviewing process with the aim of providing detailed and constructive feedback. The accepted submissions will be presented at the Doctoral Consortium and published in the conference proceedings.
PACBB welcomes the submission of papers and gives preference to the topics listed under the call. All submitted papers will undergo a thorough review process; each paper will be refereed by at least three experts in the field based on relevance, originality, significance, quality and clarity.
The papers must consist of original, relevant and previously unpublished sound research results related to any of the topics of the conference.
PACBB papers must be formatted according to the Springer LNNS Template, with a maximum length of 10 pages in length (6 pages for Doctoral Consortia), including figures and references. All proposed papers must be submitted in electronic form (PDF format) using the Paper Submission Page.
Accepted papers will be included in PACBB Proceedings. At least one of the authors will be required to register and attend the symposium to present the paper in order to include the paper in the conference proceedings. All accepted papers will be published by LNNS series of Springer Verlag.
** Indexing: The books of this series are submitted to DBLP, INSPEC, Norwegian Register for Scientific Journals and Series, SCImago, SCOPUS, WTI Frankfurt eG, zbMATH, Google Scholar, Springerlink. **
Authors of selected papers from PACBB will be invited to submit an extended and improved version to special issue in different journals.