Identifying correct bacteriological vocabulary: software to look up RKC codes and statements

Area of Science:

• Microbiology
• Bioinformatics
• Computer Science

Background:

• Accurate coding of microbiological attributes is essential for data standardization and analysis.
• The Rogosa, Krichevsky, and Colwell (RKC) coding system provides a framework for describing these attributes.
• Manual identification and selection of RKC codes can be time-consuming and prone to error.

Purpose of the Study:

• To develop a software tool that facilitates the identification and selection of RKC codes.
• To enhance the usability of the RKC coding scheme for microbiological data management.
• To create a program that can be integrated into other software packages.

Main Methods:

• A program named RKCLIST was developed to search a database of approximately 13,800 RKC codes.
• Users can input terms (words, parts of words, or numbers) to find matching RKC code descriptions.
• The program displays matching statements and allows users to build a list of selected codes.

Main Results:

• RKCLIST successfully identifies relevant RKC codes based on user-defined search terms.
• The software enables the creation of custom lists of RKC statements.
• The program is designed for the MS-DOS operating system and its routines are modular for integration.

Conclusions:

• RKCLIST offers an efficient method for accessing and utilizing the RKC coding system for microbiological data.
• The software promotes consistency and accuracy in microbiological attribute description.
• The design facilitates the incorporation of RKC coding into diverse bioinformatics and data management workflows.