DocumentCode :
1706745
Title :
Protein complex identification by graph local clustering and use of Chou´s amphiphilic Pseudo amino-acid features
Author :
Nomani, Ashkan ; Mohammadbeigi, Mohsen ; Saleki, Amir
Author_Institution :
Biomed. Eng., Univ. of Isfahan, Isfahan, Iran
fYear :
2013
Firstpage :
247
Lastpage :
249
Abstract :
The intend of this paper is to introduce a new method for protein complex identification. Proteins share an important role by signaling cells. Proteins are three dimensional objects and any types of deformed proteins can cause severe disease, because their function is related to their shape and also the amino-acid sequence they have coded with. Technically speaking similar types of proteins tend to act by forming a group or a complex and if we can find a highly accurate way to identify the complexes we can find a group of proteins that are responsible for something. For this purpose different types of algorithms have proposed but most of them failed to achieve enough precision. Here we will use a new method which uses Chou Pseudo amino-acid as a set of features and we will get a good result even by using machine learning techniques that were supposed as not an effective tool in this field before.
Keywords :
biology computing; graph theory; learning (artificial intelligence); molecular biophysics; pattern clustering; proteins; Chou amphiphilic pseudoamino-acid features; amino-acid sequence; disease; graph local clustering; machine learning techniques; protein complex identification; Educational institutions; Eigenvalues and eigenfunctions; Kernel; Protein engineering; Proteins; Support vector machines; Complex; Identification; protein; yeast;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Engineering (ICBME), 2013 20th Iranian Conference on
Conference_Location :
Tehran
Type :
conf
DOI :
10.1109/ICBME.2013.6782228
Filename :
6782228
Link To Document :
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