Fuzz-SSVS: A Fuzzy logic based voting scheme to improve protein secondary structure prediction

This paper presents a novel approach, Fuzz-SSVS, to improve the secondary structure prediction of proteins. In this work, a Sugeno based Fuzzy System is trained to act as a voting system to combine results of several secondary structure prediction techniques and produce superior answers. Fuzz-SSVS is tested with three of the well-known benchmarks in this field. The results demonstrate the superiority of the proposed technique even in the case of formidable sequences.

[1]  C Geourjon,et al.  SOPM: a self-optimized method for protein secondary structure prediction. , 1994, Protein engineering.

[2]  Yücel Altunbasak,et al.  Protein secondary structure prediction with semi Markov HMMs , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  B. Rost,et al.  Prediction of protein secondary structure at better than 70% accuracy. , 1993, Journal of molecular biology.

[4]  J. Gibrat,et al.  Further developments of protein secondary structure prediction using information theory. New parameters and consideration of residue pairs. , 1987, Journal of molecular biology.

[5]  V. Lim.  Structural principles of the globular organization of protein chains. A stereochemical theory of globular protein secondary structure. , 1974, Journal of molecular biology.

[6]  R Langridge,et al.  Improvements in protein secondary structure prediction by an enhanced neural network. , 1990, Journal of molecular biology.

[7]  G J Barton,et al.  Evaluation and improvement of multiple sequence methods for protein secondary structure prediction , 1999, Proteins.

[8]  M. Sternberg,et al.  Prediction of protein secondary structure and active sites using the alignment of homologous sequences. , 1987, Journal of molecular biology.

[9]  Burkhard Rost,et al.  Rising Accuracy of Protein Secondary Structure Prediction , 2003 .

[10]  Giovanni Soda,et al.  Exploiting the past and the future in protein secondary structure prediction , 1999, Bioinform..

[11]  P. K. Mehta,et al.  A simple and fast approach to prediction of protein secondary structure from multiply aligned sequences with accuracy above 70% , 1995, Protein science : a publication of the Protein Society.

[12]  P. Argos,et al.  Knowledge‐based protein secondary structure assignment , 1995, Proteins.

[13]  W. Kabsch,et al.  Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features , 1983, Biopolymers.

[14]  M J Sternberg,et al.  Machine learning approach for the prediction of protein secondary structure. , 1990, Journal of molecular biology.

[15]  J. Garnier,et al.  Analysis of the accuracy and implications of simple methods for predicting the secondary structure of globular proteins. , 1978, Journal of molecular biology.

[16]  R. King,et al.  Identification and application of the concepts important for accurate and reliable protein secondary structure prediction , 1996, Protein science : a publication of the Protein Society.

[17]  Albert Y. Zomaya,et al.  A voting scheme to improve the secondary structure prediction , 2010, ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010.

[18]  J. Gibrat,et al.  GOR method for predicting protein secondary structure from amino acid sequence. , 1996, Methods in enzymology.

[19]  A A Salamov,et al.  Prediction of protein secondary structure by combining nearest-neighbor algorithms and multiple sequence alignments. , 1995, Journal of molecular biology.

[20]  Barry Robson,et al.  An algorithm for secondary structure determination in proteins based on sequence similarity , 1986, FEBS letters.

[21]  Sean R. Eddy,et al.  Profile hidden Markov models , 1998, Bioinform..

[22]  Victor V. Solovyev,et al.  Predicting alpha-helix and beta-strand segments of globular proteins , 1994, Comput. Appl. Biosci..

[23]  M. Karplus,et al.  Protein secondary structure prediction with a neural network. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[24]  Lotfi A. Zadeh,et al.  Fuzzy Logic , 2009, Encyclopedia of Complexity and Systems Science.

[25]  Scott R. Presnell,et al.  A segment-based approach to protein secondary structure prediction. , 1991, Biochemistry.

[26]  P. Argos,et al.  Incorporation of non-local interactions in protein secondary structure prediction from the amino acid sequence. , 1996, Protein engineering.

[27]  G Deléage,et al.  An algorithm for protein secondary structure prediction based on class prediction. , 1987, Protein engineering.

[28]  Yann Guermeur,et al.  Combinaison de classifieurs statistiques : application à la prédiction de la structure secondaire des protéines , 1997 .

[29]  Christophe Geourjon,et al.  SOPMA: significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments , 1995, Comput. Appl. Biosci..

[30]  Christophe Geourjon,et al.  Improved performance in protein secondary structure prediction by inhomogeneous score combination , 1999, Bioinform..