Hybrid Fuzzy Algorithm for Protein Clustering Using Secondary Structure Parameters

Hybrid Fuzzy Algorithm for Protein Clustering Using Secondary Structure Parameters

Clustering of proteins is important in the field of bioinformatics. Clustering of proteins is used for analyzing the proteins to determine their functions and structure. The number of partitioning techniques, hierarchical methods and graph-based methods are available for clustering protein sequences. In this paper, we propose a hybrid fuzzy technique for clustering proteins based on its seconda...

OPTIMIZATION OF FUZZY CLUSTERING CRITERIA BY A HYBRID PSO AND FUZZY C-MEANS CLUSTERING ALGORITHM

This paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (FPSO) and fuzzy c-means (FCM) algorithms, to solve the fuzzyclustering problem, especially for large sizes. When the problem becomes large, theFCM algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. The PSO algorithm does find ago...

RFCM: A Hybrid Clustering Algorithm Using Rough and Fuzzy Sets

A hybrid unsupervised learning algorithm, termed as rough-fuzzy c-means, is proposed in this paper. It comprises a judicious integration of the principles of rough sets and fuzzy sets. While the concept of lower and upper approximations of rough sets deals with uncertainty, vagueness, and incompleteness in class definition, the membership function of fuzzy sets enables efficient handling of ove...

Protein Structure Abstractionand Automatic Clustering Using Secondary Structure Element Sequences

To study protein clustering is very important in diverse fields such as drug design and environmental industry. For a meaningful clustering, protein structure must be considered. But, protein structures are very complicated and have so much information such as angles, 3-dimensional coordinates. Thus, it is not easy to efficiently compute their relations. In this paper, we present a method to ef...

Automatic Protein Structure Clustering Using Secondary Structure Elements