Graphs and Digraphs, Fourth Edition
Graphs and Digraphs, Fourth Edition
A New Path Length Measure Based on GO for Gene Similarity with Evaluation using SGD Pathways
CBMS '08 Proceedings of the 2008 21st IEEE International Symposium on Computer-Based Medical Systems
Introduction to Algorithms, Third Edition
Introduction to Algorithms, Third Edition
Measuring semantic similarity between biomedical concepts within multiple ontologies
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
Graph edit distance with node splitting and merging, and its application to diatom identification
GbRPR'03 Proceedings of the 4th IAPR international conference on Graph based representations in pattern recognition
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The Gene Ontology has been used extensively for measuring the functional similarity among genes of various organisms. All the existing gene similarity methods use either molecular function or biological process taxonomies in computing gene similarity. In this paper, we apply an algorithm for combining graphs to connect the molecular function (F) and biological process (P) taxonomies into one FP taxonomy graph. We then measure the functional similarity of two genes using the resulting FP graph with path length function. The two aspects of GO, molecular function and biological process, are combined by connecting F nodes with P nodes using gene ontology annotation, GOA, databases. By combining two GO graphs, we can have more comprehensive way to explore the functional relationships between genes. We conducted the evaluation on a dataset of OMIM disease phenotypes to estimate the similarity of disease proteins from various diseases.