title: Solenoid and non-solenoid protein recognition using stationary wavelet packet transform.
abstract: BACKGROUND
  Solenoid proteins are emerging as a protein class with properties intermediate between structured and intrinsically unstructured proteins. Containing repeating structural units, solenoid proteins are expected to share sequence similarities. However, in many cases, the sequence similarities are weak and non-detectable. Moreover, solenoids can be degenerated and widely vary in the number of units. So that it is difficult to detect them. Recently, several solenoid repeats detection methods have been proposed, such as self-alignment of the sequence, spectral analysis and discrete Fourier transform of sequence. Although these methods have shown good performance on certain data sets, they often fail to detect repeats with weak similarities. In this article, we propose a new approach to recognize solenoid repeats and non-solenoid proteins using stationary wavelet packet transform (SWPT). Our method associates with three advantages: (i) naturally representing five main factors of protein structure and properties by wavelet analysis technique; (ii) extracting novel wavelet features that can capture hidden components from solenoid sequence similarities and distinguish them from global proteins; (iii) obtaining statistics features that capture repeating motifs of solenoid proteins.
  
  
  RESULTS
  Our method analyzes the characteristics of amino acid sequence in both spectral and temporal domains using SWPT. Both global and local information of proteins are captured by SWPT coefficients. We obtain and integrate wavelet-based features and statistics-based features of amino acid sequence to improve the classification task. Our proposed method is evaluated by comparing to state-of-the-art methods such as HHrepID and REPETITA. The experimental results show that our algorithm consistently outperforms them in areas under ROC curve. At the same false positive rate, the sensitivity of our WAVELET method is higher than other methods.
  
  
  BACKGROUND
  http://www.naaan.org/anvo/Software/Software.htm.
authors.affiliation: The Feinstein Institute for Medical Research, North Shore LIJ Health System, NY, USA. anphuocnhu.vo@mavs.uta.edu
authors.forename: An
authors.initials: A
authors.lastname: Vo
authors.forename: Nha
authors.initials: N
authors.lastname: Nguyen
authors.forename: Heng
authors.initials: H
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D000595:Amino Acid Sequence; D003062:Codon; D004563:Electrochemistry; D005583:Fourier Analysis; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry* / Q000145:classification / Q000235:genetics; D012372:ROC Curve; D012984:Software
chemical_list: D003062:Codon; D011506:Proteins
references.citation: J Mol Biol. 2002 Feb 15;316(2):341-63
references.pmid: 11851343
references.citation: Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W137-42
references.pmid: 16844977
references.citation: Nat Struct Biol. 1996 Dec;3(12):991-4
references.pmid: 8946850
references.citation: Trends Biochem Sci. 1997 Oct;22(10):399-404
references.pmid: 9357316
references.citation: BMC Genomics. 2008 Sep 16;9 Suppl 2:S17
references.pmid: 18831782
references.citation: Bioinformatics. 2008 Nov 15;24(22):2632-3
references.pmid: 18796478
references.citation: Nucleic Acids Res. 2003 Jan 1;31(1):452-5
references.pmid: 12520050
references.citation: Proc Natl Acad Sci U S A. 2005 May 3;102(18):6395-400
references.pmid: 15851683
references.citation: Bioinformatics. 2004 Aug 4;20 Suppl 1:i311-7
references.pmid: 15262814
references.citation: EMBO J. 1993 Sep;12(9):3357-64
references.pmid: 8253063
references.citation: J Mol Biol. 1999 Oct 15;293(1):151-60
references.pmid: 10512723
references.citation: J Biol Chem. 2002 Dec 20;277(51):49791-8
references.pmid: 12270919
references.citation: Science. 1995 Nov 10;270(5238):997-1000
references.pmid: 7481807
references.citation: J Comput Biol. 2010 Feb;17(2):139-52
references.pmid: 20078226
references.citation: Proteins. 2000 Nov 1;41(2):224-37
references.pmid: 10966575
references.citation: New Biol. 1992 Apr;4(4):408-11
references.pmid: 1622936
references.citation: Curr Opin Struct Biol. 1999 Jun;9(3):383-9
references.pmid: 10361086
references.citation: Proteins. 2004 Nov 1;57(2):365-80
references.pmid: 15340924
references.citation: Nat Genet. 1995 Oct;11(2):115-6
references.pmid: 7550332
references.citation: Trends Biochem Sci. 2000 Oct;25(10):509-15
references.pmid: 11050437
references.citation: J Mol Biol. 2006 May 12;358(4):1094-105
references.pmid: 16580019
references.citation: Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W239-43
references.pmid: 15980460
references.citation: Bioinformatics. 1998;14(6):498-507
references.pmid: 9694988
references.citation: Protein Sci. 1998 Jun;7(6):1477-80
references.pmid: 9655353
references.citation: Biochim Biophys Acta. 1987 Nov 26;916(2):220-6
references.pmid: 3676333
references.citation: J Mol Biol. 1998 Apr 3;277(3):519-27
references.pmid: 9533877
references.citation: BMC Bioinformatics. 2007 Jun 19;8:210
references.pmid: 17578580
references.citation: Nature. 2000 Jul 20;406(6793):325-8
references.pmid: 10917537
references.citation: Bioinformatics. 2003 Jan;19(1):2-9
references.pmid: 12499286
references.citation: Nucleic Acids Res. 1997 Sep 1;25(17):3389-402
references.pmid: 9254694
references.citation: Bioinformatics. 2008 Mar 15;24(6):807-14
references.pmid: 18245125
references.citation: Trends Biochem Sci. 2000 Oct;25(10):515-7
references.pmid: 11203383
references.citation: Bioinformatics. 2009 Jun 15;25(12):i289-95
references.pmid: 19478001
references.citation: J Struct Biol. 2001 May-Jun;134(2-3):132-44
references.pmid: 11551175