Measuring similarity between gene interaction profiles

Measuring semantic similarity between Gene Ontology terms

Many bioinformatics applications would benefit from comparing proteins based on their biological role rather than their sequence. This manuscript adds two new contributions. First, a study of the correlation between Gene Ontology (GO) terms and family similarity demonstrates that protein families constitute an appropriate baseline for validating GO similarity. Secondly, we introduce GraSM, a no...

Measuring Similarity between Ontologies

Ontologies now play an important role for many knowledge-intensive applications for which they provide a source of precisely defined terms. However, with their wide-spread usage there come problems concerning their proliferation. Ontology engineers or users frequently have a core ontology that they use, e.g., for browsing or querying data, but they need to extend it with, adapt it to, or compar...

Classifying Microarray Data Using Pairwise Similarity between Gene Profiles

Figure 1: Dendrogram with a threshold applied (---) to create clusters. The first cluster has genes A and B while the second one has genes C, D, and E. genes to be measured simultaneously. However, interpretation of the large data sets is complex. Commonly used methods include hierarchical clustering and k-nearest-neighbor [3]. After applying these methods, clusters of co-expressed genes are pr...

Gene ontology for measuring similarity

Measuring Similarity between XML Documents

With the advance of World Wide Web standards, XML documents become popular in e-business applications for information exchange. Electronic catalogs and transaction records are now formatted in XML. XML documents are semi-structured documents with XML schemas marking up the semantics. XML separates presentation from semantics so that presentation of information on different devices can be proces...