Literature DB >> 17695749

An agent-based multilayer architecture for bioinformatics grids.

Ezio Bartocci1, Diletta Cacciagrano, Nicola Cannata, Flavio Corradini, Emanuela Merelli, Luciano Milanesi, Paolo Romano.   

Abstract

Due to the huge volume and complexity of biological data available today, a fundamental component of biomedical research is now in silico analysis. This includes modelling and simulation of biological systems and processes, as well as automated bioinformatics analysis of high-throughput data. The quest for bioinformatics resources (including databases, tools, and knowledge) becomes therefore of extreme importance. Bioinformatics itself is in rapid evolution and dedicated Grid cyberinfrastructures already offer easier access and sharing of resources. Furthermore, the concept of the Grid is progressively interleaving with those of Web Services, semantics, and software agents. Agent-based systems can play a key role in learning, planning, interaction, and coordination. Agents constitute also a natural paradigm to engineer simulations of complex systems like the molecular ones. We present here an agent-based, multilayer architecture for bioinformatics Grids. It is intended to support both the execution of complex in silico experiments and the simulation of biological systems. In the architecture a pivotal role is assigned to an "alive" semantic index of resources, which is also expected to facilitate users' awareness of the bioinformatics domain.

Mesh:

Year:  2007        PMID: 17695749     DOI: 10.1109/tnb.2007.897492

Source DB:  PubMed          Journal:  IEEE Trans Nanobioscience        ISSN: 1536-1241            Impact factor:   2.935


  2 in total

Review 1.  Computational Modeling, Formal Analysis, and Tools for Systems Biology.

Authors:  Ezio Bartocci; Pietro Lió
Journal:  PLoS Comput Biol       Date:  2016-01-21       Impact factor: 4.475

2.  Machine learning models predicting multidrug resistant urinary tract infections using "DsaaS".

Authors:  Alessio Mancini; Leonardo Vito; Elisa Marcelli; Marco Piangerelli; Renato De Leone; Sandra Pucciarelli; Emanuela Merelli
Journal:  BMC Bioinformatics       Date:  2020-08-21       Impact factor: 3.169

  2 in total

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