The increased volume of existing information on biological processes and the use of large databases have significantly increased the accessibility of datasets to the scientific community. This has enabled performing an analysis to facilitate the extraction of relevant information or modeling and optimizing tasks in different processes. Parallel to the increasing volumes of information is the emergence of new or adapted distributed computing models such as grid computing and cloud computing. These management systems along with new techniques of artificial intelligence, or more specifically knowledge discovery, are making it possible to perform an analysis of the information in a more efficient manner and are enabling the creation of adaptive systems with learning ability.

We invite researchers to submit original papers on the treatment of information of biological processes from the point of view of distributed artificial intelligence techniques. The research should present novel models developed for clustering, classification, knowledge extraction, prediction, and so forth, in different fields of bioinformatics, biomedical big data, and distributed artificial intelligence.

Potential topics include, but are not limited to:

• Knowledge discovery and data mining techniques
• Rough, fuzzy, and hybrid techniques
• Artificial neural networks
• Case-based reasoning systems
• Cloud computing
• Multiagent systems
• Human computing
• Nature-inspired algorithms

Biological areas:

• Molecular evolution
• DNA twisting and folding
• High-throughput data analysis
• Phylogenetics and phylogenomics
• Gene expression data analysis
• Identification of metabolic pathways
• Biomarker identification
• Visualization of biological systems and networks
• In silico optimization of biological systems
• Metabolomics/metabolic fingerprints
• Health-care applications
• Phylogenetic classification