An Overview on Semantic Analysis of Proteomics Data

Authors:
Pietro Hiram Guzzi;Marco Mina;Concettina Guerra;Mario Cannataro
Affiliations:
Dept Surgical and Medical Sciences, University of Catanzaro, Italy;MPA, Fondazione Bruno Kessler, Italy;College of Computing, Georgia Tech Institute, Atlanta, GA USA;Dept Surgical and Medical Sciences, University of Catanzaro, Italy
Venue:
Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
Year:
2013

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Abstract

The availability of biological knowledge, recently encoded in ontologies such as the Gene Ontology, is leading the development of novel methods for the analysis of experimental data that integrate prior information. A recent trend consists in the use of Semantic Similarity Measures (SSMs) to quantify the functional similarity of biological molecules starting from qualitative data (i.e. their functions or localization within cells). A plethora of SSMs and analysis frameworks based on them have been recently proposed. There are, however, several issues in the use of SSMs still to be fully addressed, as well as their assessment with respect to biological features (e.g. is there any correlation between SSMs and biological properties such as sequence similarity?). In this work, after a brief introduction of the main SSMs, we dissect the ongoing assessment efforts.