Understanding the undelaying mechanism of HASubtyping in the level of physic-chemical characteristics of protein

PLoS ONE

Volumn 9, Issue 5, 2014, Pages

  Ebrahimi, Mansour ^a   Aghagolzadeh, Parisa ^b   Shamabadi, Narges ^a   Tahmasebi, Ahmad ^c   Alsharifi, Mohammed ^d   Adelson, David L ^d   Hemmatzadeh, Farhid ^d   Ebrahimie, Esmaeil ^d  

^a UNIVERSITY OF QOM   (Iran)

^b UNIVERSITY OF BERN   (Switzerland)

^c SHIRAZ UNIVERSITY   (Iran)

^d UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

CYSTEINE; GLUTAMINE; INFLUENZA VIRUS HEMAGGLUTININ; TYROSINE;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYESIAN LEARNING; COMPUTER PREDICTION; CONTROLLED STUDY; DECISION TREE; GENE MUTATION; GENETIC REASSORTMENT; INFLUENZA; INFLUENZA VIRUS A; KERNEL METHOD; MACHINE LEARNING; PANDEMIC; PHYSICAL CHEMISTRY; PROTEIN ANALYSIS; PROTEIN STRUCTURE; RANDOM FOREST; SEQUENCE ANALYSIS; SUPPORT VECTOR MACHINE; VALIDATION PROCESS; ANIMAL; BIOLOGY; CHEMISTRY; CLASSIFICATION; DATA MINING; GENETICS; HUMAN; MUTATION; PROCEDURES;

ANIMALS; COMPUTATIONAL BIOLOGY; DATA MINING; DECISION TREES; HEMAGGLUTININ GLYCOPROTEINS, INFLUENZA VIRUS; HUMANS; INFLUENZA A VIRUS; MUTATION; NEURAL NETWORKS (COMPUTER); PHYSICOCHEMICAL PROCESSES; SUPPORT VECTOR MACHINES;

EID: 84901036307     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0096984     Document Type: Article

References (99)

1. Driskell EA, Pickens JA, Humberd-Smith J, Gordy JT, Bradley KC, et al. (2012) Low Pathogenic Avian Influenza Isolates from Wild Birds Replicate and Transmit via Contact in Ferrets without Prior Adaptation. PLoS ONE 7: e38067.
2. Miotto O, Heiny AT, Albrecht R, García-Sastre A, Tan TW, et al. (2010) Complete-Proteome Mapping of Human Influenza A Adaptive Mutations: Implications for Human Transmissibility of Zoonotic Strains. PLoS ONE 5: e9025.
3. Gao R, Cao B, Hu Y, Feng Z, Wang D, et al. (2013) Human Infection with a Novel Avian-Origin Influenza A (H7N9) Virus. New England Journal of Medicine 368: 1888-1897.
4. Fouchier RAM, Kawaoka Y (2013) Avian flu: Gain-of-function experiments on H7N9. Nature 500: 150-151.
5. Watanabe T, Kiso M, Fukuyama S, Nakajima N, Imai M, et al. (2013) Characterization of H7N9 influenza A viruses isolated from humans. Nature 501: 551-555.
6. Zhou J, Wang D, Gao R, Zhao B, Song J, et al. (2013) Biological features of novel avian influenza A (H7N9) virus. Nature 499: 500-503.
7. Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, et al. (2009) Detecting influenza epidemics using search engine query data. Nature 457: 1012-1014.
8. Steinhauer DA (2013) Influenza: Pathways to human adaptation. Nature 499: 412-413.
9. Palese P (2004) Influenza: old and new threats. Nat Med 10: S82-87.
10. Pan CE, Wang GP, Liao M, Zhang GH, Jiang SB (2009) High genetic and antigenic similarity between a swine H3N2 influenza A virus and a prior human influenza vaccine virus: A possible immune pressure-driven cross-species transmission. Biochemical and Biophysical Research Communications 385: 402-407.
11. Campitelli L, Donatelli I, Foni E, Castrucci MR, Fabiani C, et al. (1997) Continued evolution of H1N1 and H3N2 influenza viruses in pigs in Italy. Virology 232: 310-318. (Pubitemid 27293574)
12. Adeola OA, Adeniji JA, Olugasa BO (2009) Isolation of influenza A viruses from pigs in Ibadan, Nigeria. Vet Ital 45: 383-390.
13. Scholtissek C, Burger H, Kistner O, Shortridge KF (1985) The Nucleoprotein as a Possible Major Factor in Determining Host Specificity of Influenza H3n2 Viruses. Virology 147: 287-294. (Pubitemid 16172175)
14. Imai M, Kawaoka Y (2012) The role of receptor binding specificity in interspecies transmission of influenza viruses. Current Opinion in Virology 2: 160-167.
15. Rogers GN, Paulson JC, Daniels RS, Skehel JJ, Wilson IA, et al. (1983) Single amino acid substitutions in influenza haemagglutinin change receptor binding specificity. Nature 304: 76-78. (Pubitemid 13063111)
16. Weis W, Brown JH, Cusack S, Paulson JC, Skehel JJ, et al. (1988) Structure of the influenza virus haemagglutinin complexed with its receptor, sialic acid. Nature 333: 426-431.
17. Herfst S, Schrauwen EJA, Linster M, Chutinimitkul S, de Wit E, et al. (2012) Airborne Transmission of Influenza A/H5N1 Virus Between Ferrets. Science 336: 1534-1541.
18. Imai M, Watanabe T, Hatta M, Das SC, Ozawa M, et al. (2012) Experimental adaptation of an influenza H5 HA confers respiratory droplet transmission to a reassortant H5 HA/H1N1 virus in ferrets. Nature 486: 420-428.
19. Russell CA, Fonville JM, Brown AE, Burke DF, Smith DL, et al. (2012) The potential for respiratory droplet-transmissible A/H5N1 influenza virus to evolve in a mammalian host. Science 336: 1541-1547.
20. Shinya K, Hamm S, Hatta M, Ito H, Ito T, et al. (2004) PB2 amino acid at position 627 affects, replicative efficiency, but not cell tropism, of Hong Kong H5N1 influenza A viruses in mice. Virology 320: 258-266. (Pubitemid 38315152)
21. Kumar M, Gromiha MM, Raghava GP (2011) SVM based prediction of RNA-binding proteins using binding residues and evolutionary information. J Mol Recognit 24: 303-313.
22. Xiong W, Guo Y, Li M (2010) Prediction of lipid-binding sites based on support vector machine and position specific scoring matrix. Protein J 29: 427-431.
23. Ebrahimi M, Ebrahimie E (2010) Sequence-based prediction of enzyme thermostability through bioinformatics algorithms. Current Bioinformatics 5: 195-203.
24. Tahrokh E, Ebrahimi M, Ebrahimi M, Zamansani F, Rahpeyma Sarvestani N, et al. (2011) Comparative study of ammonium transporters in different organisms by study of a large number of structural protein features via data mining algorithms. Genes & Genomics 33: 565-575.
25. Lakizadeh A, Agha-Golzadeh P, Ebrahimi M, Ebrahimie E, Ebrahimi M (2011) Engineering Thermostable Enzymes; Application of Unsupervised Clustering Algorithms. Advanced Studies in Biology 3: 63-78.
26. Ebrahimie E, Ebrahimi M, Ebrahimi M (2011) Amino acid features: a missing compartment of prediction of protein function. Natureprecedings.
27. Ashrafi E, Alemzadeh A, Ebrahimi M, Ebrahimie E, Dadkhodaei N (2011) Amino Acid Features of P1B-ATPase Heavy Metal Transporters Enabling Small Numbers of Organisms to Cope with Heavy Metal Pollution. Bioinform Biol Insights 5: 59-82.
28. Ebrahimie E, Ebrahimi M, Sarvestani NR (2011) Protein attributes contribute to halo-stability, bioinformatics approach. Saline Systems 7: 1.
29. Gromiha MM, Suresh MX (2008) Discrimination of mesophilic and thermophilic proteins using machine learning algorithms. Proteins: Structure, Function, and Bioinformatics 70: 1274-1279. (Pubitemid 351304088)
30. Gromiha MM, Yukimitsu Yi (2008) Functional discrimination of membrane proteins using machine learning techniques. BMC Bioinformatics 9: 135.
31. Hosseinzadeh F, Ebrahimi M, Goliaei B, Shamabadi N (2012) Classification of lung cancer tumors based on structural and physicochemical properties of proteins by bioinformatics models. PLoS One 7: e40017.
32. Dugas AF, Jalalpour M, Gel Y, Levin S, Torcaso F, et al. (2013) Influenza Forecasting with Google Flu Trends. PLoS One 8: e56176.
33. Tang ZQ, Lin HH, Zhang HL, Han LY, Chen X, et al. (2009) Prediction of functional class of proteins and peptides irrespective of sequence homology by support vector machines. Bioinform Biol Insights 1: 19-47.
34. Lin HH, Han LY, Zhang HL, Zheng CJ, Xie B, et al. (2006) Prediction of the functional class of lipid binding proteins from sequence-derived properties irrespective of sequence similarity. J Lipid Res 47: 824-831.
35. Hosseinzadeh F, Kayvanjoo AH, Ebrahimi M, Goliaei B (2013) Prediction of lung tumor types based on protein attributes by machine learning algorithms. Springerplus 2: 238.
36. Ong SA, Lin HH, Chen YZ, Li ZR, Cao Z (2007) Efficacy of different protein descriptors in predicting protein functional families. BMC Bioinformatics 8: 300.
37. Ding CH, Dubchak I (2001) Multi-class protein fold recognition using support vector machines and neural networks. Bioinformatics 17: 349-358. (Pubitemid 32421929)
38. Ebrahimi M (2011) Comparing various attributes of prolactin hormones in different species: application of bioinformatics tools. Iranian Journal of Veterinary Research 12: 205-213.
39. Niu XH, Hu XH, Shi F, Xia JB (2012) Predicting protein solubility by the general form of Chou's pseudo amino acid composition: approached from chaos game representation and fractal dimension. Protein Pept Lett 19: 940-948.
40. Tsipouras MG, Tzallas AT, Rigas G, Tsouli S, Fotiadis DI, et al. (2012) An automated methodology for levodopa-induced dyskinesia: assessment based on gyroscope and accelerometer signals. Artif Intell Med 55: 127-135.
41. Macas M, Lhotska L, Bakstein E, Novak D, Wild J, et al. (2012) Wrapper feature selection for small sample size data driven by complete error estimates. Comput Methods Programs Biomed 108: 138-150.
42. Hu X, Sapo M, Nenov V, Barry T, Kim S, et al. (2012) Predictive combinations of monitor alarms preceding in-hospital code blue events. J Biomed Inform 45: 913-921.
43. Huang LT, Gromiha MM (2012) Real value prediction of protein folding rate change upon point mutation. J Comput Aided Mol Des 26: 339-347.
44. Zhao X, Ma Z, Yin M (2012) Using Support Vector Machine and Evolutionary Profiles to Predict Antifreeze Protein Sequences. International Journal of Molecular Sciences 13: 2196-2207.
45. Martinez JG, Carroll RJ, Muller S, Sampson JN, Chatterjee N (2011) Empirical Performance of Cross-Validation With Oracle Methods in a Genomics Context. Am Stat 65: 223-228.
46. McCarthy LC, Newcombe PJ, Whittaker JC, Wurzelmann JI, Fries MA, et al. (2012) Predictive models of choroidal neovascularization and geographic atrophy incidence applied to clinical trial design. Am J Ophthalmol 154: 568-578 e512.
47. Nongpiur ME, Haaland BA, Friedman DS, Perera SA, He M, et al. (2013) Classification algorithms based on anterior segment optical coherence tomography measurements for detection of angle closure. Ophthalmology 120: 48-54.
48. Tamaki T, Yoshimuta J, Kawakami M, Raytchev B, Kaneda K, et al. (2013) Computer-aided colorectal tumor classification in NBI endoscopy using local features. Medical Image Analysis 17: 78-100.
49. Wu W, Dasgupta S, Ramirez EE, Peterson C, Norman JG (2012) Classification Accuracies of Physical Activities Using Smartphone Motion Sensors. J Med Internet Res 14: e130.
50. Xia X-Y, Ge M, Wang Z-X, Pan X-M (2012) Accurate Prediction of Protein Structural Class. PLoS ONE 7: e37653.
51. Quinlan JR (1986) Induction of decision trees. Machine Learning 1: 81-106.
52. Huang L-T, Gromiha MM, Hwang S-F, Ho S-Y (2006) Knowledge acquisition and development of accurate rules for predicting protein stability changes. Computational Biology and Chemistry 30: 408-415. (Pubitemid 44803125)
53. Vapnik V (1995) The Nature of Statistical I. eaming Theory. New York: Spfnger Vef lag.
54. Brown MP, Grundy WN, Lin D, Cristianini N, Sugnet CW, et al. (2000) Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc Natl Acad Sci U S A 97: 262-267. (Pubitemid 30055819)
55. Cui G, Fang C, Han K (2012) Prediction of protein-protein interactions between viruses and human by an SVM model. BMC Bioinformatics 13 Suppl 7: S5.
56. Markowetz F, Edler L, Vingron M (2003) Support vector machines for protein fold class prediction. Biometrical Journal 45: 377-389. (Pubitemid 36571156)
57. Byvatov E, Fechner U, Sadowski J, Schneider G (2003) Comparison of support vector machine and artificial neural network systems for drug/nondrug classification. J Chem Inf Comput Sci 43: 1882-1889.
58. Baseri S, Towhidi M, Ebrahimie E (2011) A Modified Efficient Empirical Bayes Regression Model for Predicting Phenomena with a Large Number of Independent Variables and Fewer Observations; Examples of its Application in Human Disease, Protein Bioinformatics, and Microarray Gene Expression Profiling. Advanced Studies in Biology 3: 181-204.
59. Wen X, Fang J, Diao M, Zhang C (2012) Artificial neural network modeling of dissolved oxygen in the Heihe River, Northwestern China. Environ Monit Assess.
60. Cartwright HM (2008) Artificial neural networks in biology and chemistry: the evolution of a new analytical tool. Methods Mol Biol 458: 1-13.
61. Zhao R, Xu G, Yue B, Liebich HM, Zhang Y (1998) Artificial neural network classification based on capillary electrophoresis of urinary nucleosides for the clinical diagnosis of tumors. J Chromatogr A 828: 489-496. (Pubitemid 29046450)
62. Tsilo LC (2009) Protein secondary structure prediction using neural networks and support vector machines: Rhodes University.
63. Patel AK, Patel S, Naik PK (2012) Prediction and classification of DNA binding proteins into four major classes based on simple sequence derived features using Ann. Digest Journal of Nanomaterials and Biostructures 5: 191-200.
64. Westerlund I, Von Heijne G, Emanuelsson O (2009) LumenP-A neural network predictor for protein localization in the thylakoid lumen. Protein science 12: 2360-2366.
65. He J, Deem MW (2010) Low-dimensional clustering detects incipient dominant influenza strain clusters. Protein Engineering Design and Selection 23: 935-946.
66. Attaluri PK, Zheng X, Chen Z, Lu G (2009) Applying machine learning techniques to classify H1N1 viral strains occurring in 2009 flu pandemic. BIOT-2009: 21.
67. Sherif FF, El Hefnawi M, Kadah Y (2011) Genomic signatures and associative classification of the Hemagglutinin protein for Human versus Avian versus Swine Influenza A viruses. IEEE. pp. 1-8.
68. Ebrahimi M, Ebrahimie E, Shamabadi N, Ebrahimi M (2010) Are there any differences between features of proteins expressed in malignant and benign breast cancers? Journal of Research in Medical Sciences 15: 299-309.
69. Ebrahimie E, Ebrahimi M, Rahpayma M (2010) Investigating protein features contribute to salt stability of halolysin proteins. Journal of Cell and Molecular Research 2: 15-28.
70. Tahrokh E, Ebrahimi M, Ebrahimi M, Zamansani F, Sarvestani NR, et al. (2011) Comparative study of ammonium transporters in different organisms by study of a large number of structural protein features via data mining algorithms. Genes & Genomics 33: 565-575.
71. Ashrafi E, Alemzadeh A, Ebrahimi M, Ebrahimie E, Dadkhodaei N, et al. (2011) Determining specific amino acid features in P1B-ATPase heavy metals transporters which provides a unique ability in small number of organisms to cope with heavy metal pollution Bioinformatics and Biology Insights Accepted.
72. Ebrahimi M, Lakizadeh A, Agha-Golzadeh P, Ebrahimie E (2011) Prediction of thermostability from amino acid attributes by combination of clustering with attribute weighting: a new vista in engineering enzymes. PLoS One 6: e23146.
73. Liu JP (2006) Avian influenza-a pandemic waiting to happen? J Microbiol Immunol Infect 39: 4-10.
74. Zhu H, Webby R, Lam TT, Smith DK, Peiris JS, et al. (2011) History of Swine Influenza Viruses in Asia. Curr Top Microbiol Immunol.
75. Li Z, Chen H, Jiao P, Deng G, Tian G, et al. (2005) Molecular basis of replication of duck H5N1 influenza viruses in a mammalian mouse model. J Virol 79: 12058-12064. (Pubitemid 41279322)
76. Baumgartner C, Lewis GD, Netzer M, Pfeifer B, Gerszten RE (2010) A new data mining approach for profiling and categorizing kinetic patterns of metabolic biomarkers after myocardial injury. Bioinformatics 26: 1745-1751.
77. Bijanzadeh E, Emam Y, Ebrahimie E (2010) Determining the most important features contributing to wheat grain yield using supervised feature selection model. Australian Journal of Crop Science 4: 402-407.
78. Ebrahimi M, Ebrahimie E, Ebrahimi M (2009) Searching for patterns of thermostability in proteins and defining the main features contributing to enzyme thermostability through screening, clustering, and decision tree algorithms. EXCLI Journal 8: 218-233.
79. Sahini L, Tempczyk-Russell A, Agarwal R (2010) Large-scale sequence analysis of hemagglutinin of influenza A virus identifies conserved regions suitable for targeting an anti-viral response. PLoS One 5: e9268.
80. Nunthaboot N, Rungrotmongkol T, Malaisree M, Kaiyawet N, Decha P, et al. (2010) Evolution of human receptor binding affinity of H1N1 hemagglutinins from 1918 to 2009 pandemic influenza A virus. J Chem Inf Model 50: 1410-1417.
81. Wu ZQ, Ji J, Zuo KJ, Xie QM, Li HM, et al. (2010) Cloning and phylogenetic analysis of hemagglutinin gene of H9N2 subtype avian influenza virus from different isolates in China during 2002 to 2009. Poult Sci 89: 1136-1143.
82. Herfst S, Osterhaus ADME, Fouchier RAM (2012) The Future of Research and Publication on Altered H5N1 Viruses. Journal of Infectious Diseases 205: 1628-1631.
83. Radman A, Gredicak M, Kopriva I, Jeric I (2011) Predicting antitumor activity of peptides by consensus of regression models trained on a small data sample. Int J Mol Sci 12: 8415-8430.
84. Tan T, Platel B, Huisman H, Sanchez C, Mus R, et al. (2012) Computer Aided Lesion Diagnosis in Automated 3D Breast Ultrasound Using Coronal Spiculation. IEEE Trans Med Imaging.
85. Li Z, Liu P, Wang W, Xu C (2012) Using support vector machine models for crash injury severity analysis. Accid Anal Prev 45: 478-486.
86. Wang K, Hu X, Wang Z, Yan A (2012) Classification of Acetylcholinesterase Inhibitors and Decoys by a Support Vector Machine. Comb Chem High Throughput Screen.
87. Kuo CC, Lin WS, Dressel CA, Chiu AW (2011) Classification of intended motor movement using surface EEG ensemble empirical mode decomposition. Conf Proc IEEE Eng Med Biol Soc 2011: 6281-6284.
88. Sawagashira T, Hayashi T, Hara T, Katsumata A, Muramatsu C, et al. (2011) An automatic detection method for carotid artery calcifications using top-hat filter on dental panoramic radiographs. Conf Proc IEEE Eng Med Biol Soc 2011: 6208-6211.
89. Collier N, Son NT, Nguyen NM (2011) OMG U got flu? Analysis of shared health messages for bio-surveillance. J Biomed Semantics 2 Suppl 5: S9.
90. Watanabe T, Kawaoka Y (2011) Pathogenesis of the 1918 pandemic influenza virus. PLoS Pathog 7: e1001218.
91. Deng L, Guan J, Dong Q, Zhou S (2009) Prediction of protein-protein interaction sites using an ensemble method. BMC Bioinformatics 10: 426.
92. Ito K (2011) Bioinformatics technologies for the analysis of antigenic evolution of influenza viruses. Uirusu 61: 3-13.
93. Althouse BM, Ng YY, Cummings DA (2011) Prediction of dengue incidence using search query surveillance. PLoS Negl Trop Dis 5: e1258.
94. Wu X, Cai Z, Wan X-F, Hoang T, Goebel R, et al. (2007) Nucleotide composition string selection in HIV-1 subtyping using whole genomes. Bioinformatics 23: 1744-1752. (Pubitemid 47250306)
95. Qi J, Wang B, Hao B-I (2004) Whole Proteome Prokaryote Phylogeny Without Sequence Alignment: A K-String Composition Approach. Journal of Molecular Evolution 58: 1-11. (Pubitemid 38120400)
96. Qi J, Hao B (2004) Prokarote phylogeny without sequence allignment: from advoidance signature to composition distance. Journal of Bioinformatics and Computational Biology 02: 1-19. (Pubitemid 38996810)
97. Hemmatzadeh F, Sumarningsih S, Tarigan S, Indriani R, Dharmayanti NL, et al. (2013) Recombinant M2e Protein-Based ELISA: A Novel and Inexpensive Approach for Differentiating Avian Influenza Infected Chickens from Vaccinated Ones. PLoS One 8: e56801.
98. Zhao Y, Zhang Y (2008) Comparison of decision tree methods for finding active objects. Advances in Space Research 41: 1955-1959. (Pubitemid 351636394)
99. Manly BFJ (1994) Multivariate Statistical Methods: A Primer, Second Edition: Chapman & Hall.