Improved methodology for accessing industry based microbial database using Fuzzy Relational Algebra and proposing a microbial fuzzy database model

Numerous biological databases such as Microbial Genome Database for Comparative Analysis (MBGD), Microbial Identification and Typing Database (HPA) and National Microbiological Database (NMD) have been developed in recent times which triggered impacts in the different research fields of biological sciences. It has been observed that due to adaptability, evolution, and emergence, the biological systems are very much uncertain and hence require complexity analysis. Reports suggest that little work has been done in modeling uncertainty and developing methodologies for such databases at the industrial level. Although, there have been several proposals for extending relational database system to represent and retrieve data, the present concept emphasizes the use of fuzzy relational algebra to access the database as applicable in the Industries. Aim To fill this gap an applicable Industry based Microbial Fuzzy database model and an improved methodology for accessing the Industry based Microbial Fuzzy Database using Fuzzy Relational Algebra (MBFRDB) is proposed in this paper. MethodsIn the present proposal access to database is accomplished through a relation algebra which comprises of sequential applications of operations including an operation name, names of relations, names of domains to be operated on and an optional conditional expression. The algebra also contain other relational operations such as compliment, union, intersection and joins which performs the tasks on the relations and the domains specified in order to produce the desired information. ResultsThe approach focuses on solving the complexity in a robust system and managing its uncertainty at diversified industrial and lab scale respectively. ISSN: 2277 – 9043 International Journal of Advanced Research in Computer Science and Electronics Engineering (IJARCSEE) Volume 1, Issue 7, September 2012