Fuzzy pattern trees for predicting the protein binding sites
Date Issued
2012
Author(s)
Mirceva, Georgina
Abstract
Protein molecules are very important in the living organisms,
since they are involved in many processes in the organisms.
The knowledge of their functions is crucial for designing new
drugs. There are various experimental methods for
determining their functions, but they are very complex, so the
number of known protein structures with undetermined
functions is growing too fast. Therefore, one of the main
research directions in bioinformatics community is
investigating new computational methods for determining the
protein functions. In this research paper, we present a twostep fuzzy pattern tree based method for predicting the
binding sites of the proteins. Further, this method could be
incorporated in a framework for protein function annotation.
The binding sites of the proteins are the amino acid residues
where interactions between protein structures occur, while
their features determine the functions that the proteins have in
these interactions. In the first step of our method, we extract
the most important features of the amino acids of the protein
molecules. In the second step, using the amino acids’ features
we induce fuzzy pattern trees that would be used to classify
the amino acids as binding or non-binding sites. We present
some experimental results of the evaluation of the fuzzy
pattern trees based method.
since they are involved in many processes in the organisms.
The knowledge of their functions is crucial for designing new
drugs. There are various experimental methods for
determining their functions, but they are very complex, so the
number of known protein structures with undetermined
functions is growing too fast. Therefore, one of the main
research directions in bioinformatics community is
investigating new computational methods for determining the
protein functions. In this research paper, we present a twostep fuzzy pattern tree based method for predicting the
binding sites of the proteins. Further, this method could be
incorporated in a framework for protein function annotation.
The binding sites of the proteins are the amino acid residues
where interactions between protein structures occur, while
their features determine the functions that the proteins have in
these interactions. In the first step of our method, we extract
the most important features of the amino acids of the protein
molecules. In the second step, using the amino acids’ features
we induce fuzzy pattern trees that would be used to classify
the amino acids as binding or non-binding sites. We present
some experimental results of the evaluation of the fuzzy
pattern trees based method.
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