ApicoAMP: The first computational model for identifying apicoplast-targeted transmembrane proteins in Apicomplexa

Journal of Microbiological Methods

Volumn 95, Issue 3, 2013, Pages 313-319

  Cilingir, Gokcen ^a   Lau, Audrey O T ^b   Broschat, Shira L ^a,b  

^a Washington State University   (United States)

^b WASHINGTON STATE UNIVERSITY   (United States)

Author keywords

Apicomplexa; Apicoplast; Apicoplast targeted membrane proteins; Ensemble classification models; Machine learning; Transmembrane proteins

Indexed keywords

MEMBRANE PROTEIN;

ALGORITHM; AMINO ACID SEQUENCE; APICOMPLEXA; APICOPLAST; ARTICLE; CLASSIFICATION ALGORITHM; CRYPTOSPORIDIUM HOMINIS; CRYPTOSPORIDIUM PARVUM; EIMERIA TENELLA; HYDROPHOBICITY; MACHINE LEARNING; NEOSPORA CANINUM; NONHUMAN; PLASMODIUM BERGHEI; PLASMODIUM CHABAUDI; PLASMODIUM CYNOMOLGI; PLASMODIUM FALCIPARUM; PLASMODIUM KNOWLESI; PLASMODIUM VIVAX; PLASMODIUM YOELII; PREDICTION; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN DOMAIN; PROTEIN MOTIF; SUPPORT VECTOR MACHINE; THEILERIA ANNULATA; THEILERIA PARVA; TOXOPLASMA GONDII;

APICOMPLEXA; APICOPLAST; APICOPLAST-TARGETED MEMBRANE PROTEINS; ENSEMBLE CLASSIFICATION MODELS; MACHINE LEARNING; TRANSMEMBRANE PROTEINS;

AMINO ACID MOTIFS; AMINO ACIDS; APICOMPLEXA; APICOPLASTS; COMPUTATIONAL BIOLOGY; HYDROPHOBIC AND HYDROPHILIC INTERACTIONS; MEMBRANE PROTEINS; PROTEIN TRANSPORT; PROTOZOAN PROTEINS;

EID: 84886286907     PISSN: 01677012     EISSN: 18728359     Source Type: Journal    
DOI: 10.1016/j.mimet.2013.09.017     Document Type: Article

References (38)

1. Alpaydin E. Introduction to Machine Learning 2010, 9. The MIT Press.
2. Aurrecoechea C., Brestelli J., Brunk B.P., Fischer S., Gajria B., Gao X., Gingle A., Grant G., Harb O.S., Heiges M., Innamorato F., Iodice J., Kissinger J.C., Kraemer E.T., Li W., Miller J.A., Nayak V., Pennington C., Pinney D.F., Roos D.S., Ross C., Srinivasamoorthy G., Stoeckert C.J., Thibodeau R., Treatman C., Wang H. EuPathDB: a portal to eukaryotic pathogen databases. Nucleic Acids Res. 2010, 38(Database issue):D415-D419.
3. Bailey T.L., Williams N., Misleh C., Li W.W. MEME: discovering and analyzing DNA and protein sequence motifs. Nucleic Acids Res. 2006, 1(34):W369-W373.
4. Bailey T.L., Bodén M., Whitington T., Machanick P. The value of position-specific priors in motif discovery using MEME. BMC Bioinforma. 2010, 9(11):179.
5. Bendtsen J.D., Nielsen H., von Heijne G., Brunak S. Improved prediction of signal peptides: SignalP 3.0. J. Mol. Biol. 2004, 340(4):783-795.
6. Ben-Hur A., Weston J. A user's guide to support vector machines. Methods Mol. Biol. 2010, 609:223-239.
7. Blum T., Briesemeister S., Kohlbacher O. MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction. BMC Bioinforma. 2009, 1(10):274.
8. Camacho C., Coulouris G., Avagyan V., Ma N., Papadopoulos J., Bealer K., Madden T. BLAST+: architecture and applications. BMC Bioinforma. 2009, 15(10):421.
9. Chen F., Mackey A.J., Stoeckert C.J., Roos D.S. OrthoMCL-DB: querying a comprehensive multi-species collection of ortholog groups. Nucleic Acids Res. 2006, 34:D363-D368.
10. Chi S.M., Nam D. WegoLoc: accurate prediction of protein subcellular localization using weighted Gene Ontology terms. Bioinformatics 2012, 28(7):1028-1030.
11. Cilingir G., Broschat S.L., Lau A.O.T. ApicoAP: the first computational model for identifying apicoplast-targeted proteins in multiple species of Apicomplexa. PLoS ONE 2012, 7(5).
12. DeRocher A.E., Coppens I., Karnataki A., Gilbert L.A., Rome M.E., Feagin J.E., Bradley P.J., Parsons M. A thioredoxin family protein of the apicoplast periphery identifies abundant candidate transport vesicles in Toxoplasma gondii. Eukaryot. Cell 2008, 7(9):1518-1529.
13. DeRocher A.E., Karnataki A., Vaney P., Parsons M. Apicoplast targeting of a Toxoplasma gondii transmembrane protein requires a cytosolic tyrosine-based motif. Traffic 2012, 15(5):694-704.
14. Du P. Predicting subcellular localizations of membrane proteins in eukaryotes with weighted Gene Ontology scores. Adv. Intell. Soft Comput. 2012, 124:191-195.
15. Du P., Tian Y., Yan Y. Subcellular localization prediction for human internal and organelle membrane proteins with Projected Gene Ontology Scores. J. Theor. Biol. 2012, 313:61-67.
16. Engelman D.M., Steitz T.A., Goldman A. Identifying nonpolar transbilayer helices in amino acid sequences of membrane proteins. Annu. Rev. Biophys. Biophys. Chem. 1986, 15:321-353.
17. Fleige T., Limenitakis J., Soldati-Favre D. Apicoplast: keep it or leave it. Microbes Infect. 2010, 12(4):253-262.
18. Foth B.J., Ralph S.A., Tonkin C.J., Struck N.S., Fraunholz M., Roos D.S., Cowman A.F., McFadden G.I. Dissecting apicoplast targeting in the malaria parasite Plasmodium falciparum. Science 2003, 299:705-708.
19. Hofmann K., Stoffel W. TMbase - a database of membrane spanning proteins segments. Biol. Chem. Hoppe-Seyler 1993, 374:166.
20. Huang W.L., Tung C.W., Ho S.W., Hwang S.F., Ho S.Y. ProLoc-GO: utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization. BMC Bioinforma. 2008, 1(9):80.
21. Joachims T. Making large-scale support vector machine learning practical. Advances in Kernel Methods 1999, 169-184. MIT Press. B. Schölkopf, C. Burges, A. Smola (Eds.).
22. Karnataki A., DeRocher A.E., Coppens I., Feagin J.E., Parsons M. A membrane protease is targeted to the relict plastid of toxoplasma via an internal signal sequence. Traffic 2007, 8(11):1543-1553.
23. Karnataki A., DeRocher A.E., Coppens I., Nash C., Feagin J.E., Parsons M. Cell cycle-regulated vesicular trafficking of Toxoplasma APT1, a protein localized to multiple apicoplast membranes. Mol. Microbiol. 2007, 63(6):1653-1668.
24. Krogh A., Larsson B., von Heijne G., Sonnhammer E.L. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J. Mol. Biol. 2001, 305(3):567-580.
25. Li W., Godzik A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 2006, 22:1658-1659.
26. Li L., Zhang Y., Zou L., Li C., Yu B., Zheng X., Zhou Y. An ensemble classifier for eukaryotic protein subcellular location prediction using Gene Ontology categories and amino acid hydrophobicity. PLoS One 2012, 7(1).
27. Lim L., Kalanon M., McFadden G.I. New proteins in the apicoplast membranes: time to rethink apicoplast protein targeting. Trends Parasitol. 2009, 25(5):197-200.
28. Mei S., Fei W., Zhou S. Gene Ontology based transfer learning for protein subcellular localization. BMC Bioinforma. 2011, 2(12):44.
29. Michelsen K., Yuan H., Schwappach B. Hide and run. Arginine-based endoplasmic-reticulum-sorting motifs in the assembly of heteromultimeric membrane proteins. EMBO Rep. 2005, 6(8):717-722.
30. Pierleoni A., Martelli P.L., Casadio R. MemLoci: predicting subcellular localization of membrane proteins in Eukaryotes. Bioinformatics 2011, 27(9):1224-1230.
31. Provost F. Machine learning from imbalanced data sets 101. Proceedings of the AAAI-2000 Workshop on Imbalanced Data Sets 2000.
32. Sato K., Nakano A. Emp47p and its close homolog Emp46p have a tyrosine-containing endoplasmic reticulum exit signal and function in glycoprotein secretion in Saccharomyces cerevisiae. Mol. Biol. Cell 2002, 13(7):2518-2532.
33. Sharpe H.J., Stevens T.J., Munro S. A comprehensive comparison of transmembrane domains reveals organelle-specific properties. Cell 2010, 142(1):158-169.
34. Sheiner L., Demerly J.L., Poulsen N., Beatty W.L., Lucas O., Behnke M.S., White M.W., Striepen B. A systematic screen to discover and analyze apicoplast proteins identifies a conserved and essential protein import factor. PLoS Pathog. 2011, 7(12).
35. Vapnik V. The Nature of Statistical Learning Theory 1995, Springer, New York.
36. Vapnik V. Statistical Learning Theory 1998, Wiley, New York.
37. Vens C., Rosso M.N., Danchin E.G. Identifying discriminative classification-based motifs in biological sequences. Bioinformatics 2011, 27(9):1231-1238.
38. von Heijne G. Membrane protein structure prediction. Hydrophobicity analysis and the positive-inside rule. J. Mol. Biol. 1992, 225(2):487-494.