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Similarity and Prioritization of Disease Proteins using Path Length Measure
 

Summary: Similarity and Prioritization of Disease Proteins using Path
Length Measure
Anurag Nagar
University of Houston-Clear Lake
Houston, TX, 77058, USA
Hisham Al-Mubaid
University of Houston-Clear Lake
Houston, TX, 77058, USA
hisham@uhcl.edu
Abstract- Semantic similarity measures have been used successfully and extensively in the biomedical research
with various applications. As the biomedical ontologies, which form the main ground for most of the similarity
measures, are growing and progressing towards more completeness and higher accuracy, the results and outcomes
of these semantic similarity measures become more acceptable and more reliable in the field. In this paper, we
investigate a path length based measure for prioritization of disease proteins and for computing the similarity
between diseases and proteins. Our measure is based on the GO annotation terms of the proteins and uses a simple
exponential transfer function to convert the path length to similarity score. The evaluation results prove that this
similarity measure is fairly effective in assessing the closeness of proteins and diseases in the disease protein
ranking and protein prioritization experiments.
1. Introduction
Biomedical ontologies have received increasing

  

Source: Al-Mubaid, Hisham - School of Science and Computer Engineering, University of Houston-Clear Lake

 

Collections: Computer Technologies and Information Sciences