Predicting Golgi-resident protein types using pseudo amino acid compositions: Approaches with positional specific physicochemical properties

Journal of Theoretical Biology

Volumn 391, Issue , 2016, Pages 35-42

  Jiao, Ya Sen ^a   Du, Pu Feng ^a  

^a TIANJIN UNIVERSITY   (China)

Author keywords

ANOVA; Golgi apparatus; PseAAC; PSPCP; SVM

Indexed keywords

AMINO ACID; CELL PROTEIN; GOLGI RESIDENT PROTEIN; UNCLASSIFIED DRUG; PROTEIN;

AMINO ACID; MOLECULAR ANALYSIS; PHYSICOCHEMICAL PROPERTY; PROTEIN;

ACCURACY; ALGORITHM; AMINO ACID ANALYSIS; AMINO ACID COMPOSITION; AMINO ACID SEQUENCE; ANALYSIS OF VARIANCE; ARTICLE; CALIBRATION; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL PARAMETERS; PHYSICAL CHEMISTRY; POSITIONAL SPECIFIC PHYSICOCHEMICAL PROPERTY; PREDICTION; PRIORITY JOURNAL; PROTEIN DETERMINATION; VALIDATION PROCESS; ANIMAL; GENETICS; GOLGI COMPLEX; HUMAN; METABOLISM; PROCEDURES; SEQUENCE ANALYSIS;

ANIMALS; GOLGI APPARATUS; HUMANS; PROTEINS; SEQUENCE ANALYSIS, PROTEIN;

EID: 84949870971     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2015.11.009     Document Type: Article

References (66)

1. Ali F., Hayat M. Classification of membrane protein types using voting feature interval in combination with Chou's pseudo amino acid composition. J. Theor. Biol. 2015, 384:78-83. 10.1016/j.jtbi.2015.07.034.
2. Altschul S.F., Madden T.L., Schäffer A.A., Zhang J., Zhang Z., Miller W., Lipman D.J. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 1997, 25:3389-3402.
3. Cao D.-S., Xu Q.-S., Liang Y.-Z. propy: a tool to generate various modes of Chou's PseAAC. Bioinformatics 2013, 29:960-962. 10.1093/bioinformatics/btt072.
4. Chang C., Chang C., Lin C. LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2011.
5. Chen W., Feng P., Ding H., Lin H., Chou K.-C. iRNA-Methyl: Identifying N(6)-methyladenosine sites using pseudo nucleotide composition. Anal. Biochem. 2015, 490:26-33. 10.1016/j.ab.2015.08.021.
6. Chen W., Feng P.-M., Deng E.-Z., Lin H., Chou K.-C. iTIS-PseTNC: a sequence-based predictor for identifying translation initiation site in human genes using pseudo trinucleotide composition. Anal. Biochem. 2014, 462:76-83. 10.1016/j.ab.2014.06.022.
7. Chen W., Feng P.-M., Lin H., Chou K.-C. iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition. Nucleic Acids Res. 2013, 41:e68. 10.1093/nar/gks1450.
8. Chen W., Lei T.-Y., Jin D.-C., Lin H., Chou K.-C. PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition. Anal. Biochem. 2014, 456:53-60. 10.1016/j.ab.2014.04.001.
9. Chen W., Lin H., Chou K.-C. Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences. Mol. Biosyst. 2015, 11:2620-2634. 10.1039/c5mb00155b.
10. Chen W., Zhang X., Brooker J., Lin H., Zhang L., Chou K.-C. PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions. Bioinformatics 2015, 31:119-120. 10.1093/bioinformatics/btu602.
11. Chou K.-C. Impacts of bioinformatics to medicinal chemistry. Med. Chem. 2015, 11:218-234.
12. Chou K.-C. Some remarks on predicting multi-label attributes in molecular biosystems. Mol. Biosyst. 2013, 9:1092-1100. 10.1039/c3mb25555g.
13. Chou K.-C. Some remarks on protein attribute prediction and pseudo amino acid composition. J. Theor. Biol. 2011, 273:236-247. 10.1016/j.jtbi.2010.12.024.
14. Chou K.-C. Pseudo Amino Acid Composition and its Applications in Bioinformatics. Proteom. Syst. Biol. Curr. Proteom. 2009, 6:262-274. 10.2174/157016409789973707.
15. Chou K.-C. Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes. Bioinformatics 2005, 21:10-19. 10.1093/bioinformatics/bth466.
16. Chou K.C. Prediction of protein cellular attributes using pseudo-amino acid composition. Proteins 2001, 43:246-255.
17. Chou K.C. Using subsite coupling to predict signal peptides. Protein Eng. 2001, 14:75-79.
18. Chou K.-C., Cai Y.-D. Predicting protein quaternary structure by pseudo amino acid composition. Proteins 2003, 53:282-289. 10.1002/prot.10500.
19. Chou K.-C., Shen H.-B. Cell-PLoc: a package of Web servers for predicting subcellular localization of proteins in various organisms. Nat. Protoc. 2008, 3:153-162. 10.1038/nprot.2007.494.
20. Chou K.-C., Wu Z.-C., Xiao X. iLoc-Hum: using the accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites. Mol. Biosyst. 2012, 8:629-641. 10.1039/c1mb05420a.
21. Chou K.-C., Wu Z.-C., Xiao X. iLoc-Euk: a multi-label classifier for predicting the subcellular localization of singleplex and multiplex eukaryotic proteins. Plos. ONE 2011, 6:e18258. 10.1371/journal.pone.0018258.
22. Chou K.C., Zhang C.T. Prediction of protein structural classes. Crit. Rev. Biochem. Mol. Biol. 1995, 30:275-349. 10.3109/10409239509083488.
23. Dehzangi A., Heffernan R., Sharma A., Lyons J., Paliwal K., Sattar A. Gram-positive and Gram-negative protein subcellular localization by incorporating evolutionary-based descriptors into Chou's general PseAAC. J. Theor. Biol. 2015, 364:284-294. 10.1016/j.jtbi.2014.09.029.
24. Ding H., Deng E.-Z., Yuan L.-F., Liu L., Lin H., Chen W., Chou K.-C. iCTX-type: a sequence-based predictor for identifying the types of conotoxins in targeting ion channels. Biomed. Res. Int. 2014, 2014:286419. 10.1155/2014/286419.
25. Ding H., Guo S.-H., Deng E.-Z., Yuan L.-F., Guo F.-B., Huang J., Rao N., Chen W., Lin H. Prediction of Golgi-resident protein types by using feature selection technique. Chemom. Intell. Lab. Syst. 2013, 124:9-13. 10.1016/j.chemolab.2013.03.005.
26. Ding H., Liu L., Guo F.-B., Huang J., Lin H. Identify Golgi protein types with modified Mahalanobis discriminant algorithm and pseudo amino acid composition. Protein Pept. Lett. 2011, 18:58-63.
27. Du P., Cao S., Li Y. SubChlo: predicting protein subchloroplast locations with pseudo-amino acid composition and the evidence-theoretic K-nearest neighbor (ET-KNN) algorithm. J. Theor. Biol. 2009, 261:330-335. 10.1016/j.jtbi.2009.08.004.
28. Du P., Gu S., Jiao Y. PseAAC-General: fast building various modes of general form of Chou's pseudo-amino acid composition for large-scale protein datasets. Int. J. Mol. Sci. 2014, 15:3495-3506. 10.3390/ijms15033495.
29. Du P., Li T., Wang X. Recent progress in predicting protein sub-subcellular locations. Expert Rev. Proteom. 2011, 8:391-404. 10.1586/epr.11.20.
30. Du P., Li Y. Prediction of protein submitochondria locations by hybridizing pseudo-amino acid composition with various physicochemical features of segmented sequence. BMC Bioinf. 2006, 7:518. 10.1186/1471-2105-7-518.
31. Du P., Wang X., Xu C., Gao Y. PseAAC-Builder: a cross-platform stand-alone program for generating various special Chou's pseudo-amino acid compositions. Anal. Biochem. 2012, 425:117-119. 10.1016/j.ab.2012.03.015.
32. Du P., Xu C. Predicting multisite protein subcellular locations: progress and challenges. Expert Rev. Proteom. 2013, 10:227-237. 10.1586/epr.13.16.
33. Du P., Yu Y. SubMito-PSPCP: predicting protein submitochondrial locations by hybridizing positional specific physicochemical properties with pseudoamino acid compositions. Biomed. Res. Int. 2013, 2013:263829. 10.1155/2013/263829.
34. Du P., Yu Y. SubMito-PSPCP: Predicting Protein Submitochondrial Locations by Hybridizing Positional Specific Physicochemical Properties with Pseudoamino Acid Compositions. Biomed. Res. Int. 2013, 2013. 10.1155/2013/263829.
35. Guo S.-H., Deng E.-Z., Xu L.-Q., Ding H., Lin H., Chen W., Chou K.-C. iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition. Bioinformatics 2014, 30:1522-1529. 10.1093/bioinformatics/btu083.
36. Jia J., Liu Z., Xiao X., Liu B., Chou K.-C. iPPI-Esml: An ensemble classifier for identifying the interactions of proteins by incorporating their physicochemical properties and wavelet transforms into PseAAC. J. Theor. Biol. 2015, 377:47-56. 10.1016/j.jtbi.2015.04.011.
37. Jia J., Liu Z., Xiao X., Liu B., Chou K.-C. Identification of protein-protein binding sites by incorporating the physicochemical properties and stationary wavelet transforms into pseudo amino acid composition. J. Biomol. Struct. Dyn. 2015, 1-16. 10.1080/07391102.2015.1095116.
38. Kawashima S., Pokarowski P., Pokarowska M., Kolinski A., Katayama T., Kanehisa M. AAindex: amino acid index database, progress report 2008. Nucleic Acids Res. 2008, 36:D202-D205. 10.1093/nar/gkm998.
39. Kumar R., Srivastava A., Kumari B., Kumar M. Prediction of β-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine. J. Theor. Biol. 2015, 365:96-103. 10.1016/j.jtbi.2014.10.008.
40. Lin H., Chen W., Yuan L.-F., Li Z.-Q., Ding H. Using over-represented tetrapeptides to predict protein submitochondria locations. Acta Biotheor. 2013, 61:259-268. 10.1007/s10441-013-9181-9.
41. Lin H., Deng E.-Z., Ding H., Chen W., Chou K.-C. iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition. Nucleic Acids Res. 2014, 42:12961-12972. 10.1093/nar/gku1019.
42. Lin W.-Z., Fang J.-A., Xiao X., Chou K.-C. iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins. Mol. Biosyst. 2013, 9:634-644. 10.1039/c3mb25466f.
43. Liu B., Fang L., Liu F., Wang X., Chen J., Chou K.-C. Identification of real microRNA precursors with a pseudo structure status composition approach. Plos. ONE 2015, 10:e0121501. 10.1371/journal.pone.0121501.
44. Liu B., Fang L., Liu F., Wang X., Chou K.-C. iMiRNA-PseDPC: microRNA precursor identification with a pseudo distance-pair composition approach. J. Biomol. Struct. Dyn. 2015, 1-13. 10.1080/07391102.2015.1014422.
45. Liu B., Fang L., Wang S., Wang X., Li H., Chou K.-C. Identification of microRNA precursor with the degenerate K-tuple or Kmer strategy. J. Theor. Biol. 2015, 385:153-159. 10.1016/j.jtbi.2015.08.025.
46. Liu B., Liu F., Fang L., Wang X., Chou K.-C. repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects. Bioinformatics 2015, 31:1307-1309. 10.1093/bioinformatics/btu820.
47. Liu B., Liu F., Fang L., Wang X., Chou K.-C. repRNA: a web server for generating various feature vectors of RNA sequences. Mol. Genet. Genom. 2015, 10.1007/s00438-015-1078-7.
48. Liu B., Liu F., Wang X., Chen J., Fang L., Chou K.-C. Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences. Nucleic Acids Res. 2015, 43:W65-W71. 10.1093/nar/gkv458.
49. Liu B., Xu J., Fan S., Xu R., Zhou J., Wang X. PseDNA-Pro: DNA-Binding Protein Identification by Combining Chou's PseAAC and Physicochemical Distance Transformation. Mol. Inf. 2015, 34:8-17. 10.1002/minf.201400025.
50. Liu B., Xu J., Lan X., Xu R., Zhou J., Wang X., Chou K.-C. iDNA-Prot|dis: identifying DNA-binding proteins by incorporating amino acid distance-pairs and reduced alphabet profile into the general pseudo amino acid composition. Plos. ONE 2014, 9:e106691. 10.1371/journal.pone.0106691.
51. Liu Z., Xiao X., Qiu W.-R., Chou K.-C. iDNA-Methyl: identifying DNA methylation sites via pseudo trinucleotide composition. Anal. Biochem. 2015, 474:69-77. 10.1016/j.ab.2014.12.009.
52. Pacharawongsakda E., Theeramunkong T. Predict subcellular locations of singleplex and multiplex proteins by semi-supervised learning and dimension-reducing general mode of Chou's PseAAC. IEEE Trans. Nanobiosci. 2013, 12:311-320. 10.1109/TNB.2013.2272014.
53. Shen H.-B., Chou K.-C. PseAAC: a flexible web server for generating various kinds of protein pseudo amino acid composition. Anal. Biochem. 2008, 373:386-388. 10.1016/j.ab.2007.10.012.
54. Shen H.-B., Chou K.-C. Nuc-PLoc: a new web-server for predicting protein subnuclear localization by fusing PseAA composition and PsePSSM. Protein Eng. Des. Sel. 2007, 20:561-567. 10.1093/protein/gzm057.
55. Shen H.-B., Chou K.-C. Virus-PLoc: a fusion classifier for predicting the subcellular localization of viral proteins within host and virus-infected cells. Biopolymers 2007, 85:233-240. 10.1002/bip.20640.
56. Shen H.-B., Yang J., Chou K.-C. Euk-PLoc: an ensemble classifier for large-scale eukaryotic protein subcellular location prediction. Amino Acids 2007, 33:57-67. 10.1007/s00726-006-0478-8.
57. Shen H.-B., Yi D.-L., Yao L.-X., Yang J., Chou K.-C. Knowledge-based computational intelligence development for predicting protein secondary structures from sequences. Expert. Rev. Proteom. 2008, 5:653-662. 10.1586/14789450.5.5.653.
58. Shi S.-P., Qiu J.-D., Sun X.-Y., Huang J.-H., Huang S.-Y., Suo S.-B., Liang R.-P., Zhang L. Identify submitochondria and subchloroplast locations with pseudo amino acid composition: approach from the strategy of discrete wavelet transform feature extraction. Biochim. Biophys. Acta 2011, 1813:424-430. 10.1016/j.bbamcr.2011.01.011.
59. van Dijk A.D.J., Bosch D., ter Braak C.J.F., van der Krol A.R., van Ham R.C.H.J. Predicting sub-Golgi localization of type II membrane proteins. Bioinformatics 2008, 24:1779-1786. 10.1093/bioinformatics/btn309.
60. Vapnik V. The Nature of Statistical Learning Theory 1995, Springer, New York.
61. Wang X., Zhang W., Zhang Q., Li G.-Z. MultiP-SChlo: multi-label protein subchloroplast localization prediction with Chou's pseudo amino acid composition and a novel multi-label classifier. Bioinformatics 2015, 31:2639-2645. 10.1093/bioinformatics/btv212.
62. Wu Z.-C., Xiao X., Chou K.-C. iLoc-Gpos: a multi-layer classifier for predicting the subcellular localization of singleplex and multiplex Gram-positive bacterial proteins. Protein Pept. Lett. 2012, 19:4-14.
63. Wu Z.-C., Xiao X., Chou K.-C. iLoc-Plant: a multi-label classifier for predicting the subcellular localization of plant proteins with both single and multiple sites. Mol. Biosyst. 2011, 7:3287-3297. 10.1039/c1mb05232b.
64. Xiao X., Wang P., Lin W.-Z., Jia J.-H., Chou K.-C. iAMP-2L: a two-level multi-label classifier for identifying antimicrobial peptides and their functional types. Anal. Biochem. 2013, 436:168-177. 10.1016/j.ab.2013.01.019.
65. Xiao X., Wu Z.-C., Chou K.-C. iLoc-Virus: a multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites. J. Theor. Biol. 2011, 284:42-51. 10.1016/j.jtbi.2011.06.005.
66. Xu Y., Shao X.-J., Wu L.-Y., Deng N.-Y., Chou K.-C. iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins. PeerJ. 2013, 1:e171. 10.7717/peerj.171.