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Using fuzzy set theory and scale-free network properties to relate MEDLINE terms

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Abstract

Automated construction and annotation of biological networks is becoming increasingly important in bioinformatics as the amount of biological data increases. At the center of this are metrics required for relating biological entities such as genes, diseases, signaling molecules and chemical compounds. Co-occurrence of terms within abstracts is widely used to establish tentative relationships because it is easy to use, implement, understand, and is reasonably accurate. However, it is also very imprecise – the cutoffs for how many co-occurrences of terms are necessary to establish a relationship is arbitrary and the nature of the relationship is generic. Since the frequency of co-occurrence for terms usually follows a scale-free distribution, this property can be exploited to define degree of membership in fuzzy sets. Beginning with a set of co-occurrences for any biomedical term (or its synonyms), relations are defined by the overlap of sets, normalizing by the area under the curve that the two sets share. The ability of this method to rank the relative specificity of biological relationships is tested by comparing cumulative term co-occurrences within 7.5 million MEDLINE abstracts with focused summaries of gene function and disease association within LocusLink. On average, the fuzzy set ranking (FSR) was in the top 0.6% of all potential associations, showing a good correlation between domain overlap and the biological association between two terms.

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Authors and Affiliations

  1. Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, 101 David L. Boren Blvd., Room 2025, Norman, OK, 73019, USA

    Jonathan D. Wren

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  1. Jonathan D. Wren
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Correspondence to Jonathan D. Wren.

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Wren, J. Using fuzzy set theory and scale-free network properties to relate MEDLINE terms. Soft Comput 10, 374–381 (2006). https://doi.org/10.1007/s00500-005-0497-5

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  • DOI: https://doi.org/10.1007/s00500-005-0497-5

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