205
Views
15
CrossRef citations to date
0
Altmetric
Original

Bioinformatics for study of autoimmunity

&
Pages 635-643 | Published online: 07 Jul 2009

References

  • Brusic V, Petrovsky N. Immunoinformatics and its relevance to understanding human immune disease. Exp Rev Clin Immunol 2005, 1: 145–157
  • Korber B, LaBute M, Yusim K. Immunoinformatics comes of age. PLoS Comput Biol 2006, 2: e71
  • Mount DW. Bioinformatics: Sequence and genome analysis. Cold Spring Harbor Laboratory Press. 2004
  • Gavaghan D, Garny A, Maini PK, Kohl P. Mathematical models in physiology. Philos Transact A Math Phys Eng Sci 2006; 364: 1099–1106
  • Motta S, Brusic V. Mathematical modelling of the immune system. Modelling in molecular biology, natural computing series, G Ciobanu, G Rozenberg. Springer. 2004; 193–218
  • Brusic V, Zeleznikow J, Petrovsky N. Molecular immunology databases and data repositories. J Immunol Methods 2000; 238: 17–28
  • Lefranc MP. IMGT, the international ImMunoGeneTics information system: A standardized approach for immunogenetics and immunoinformatics. Immunome Res 2005; 1: 3
  • Moise L, De Groot AS. Nat Biotechnol 2006; 24: 791–792
  • Lollini PL, Motta S, Pappalardo F. Discovery of cancer vaccination protocols with a genetic algorithm driving an agent based simulator. BMC Bioinformatics 2006; 7: 352
  • Brusic V. Information management for the study of allergies. Inflamm Allergy Drug Targets 2006; 5: 35–42
  • Karopka T, Fluck J, Mevissen HT, Glass A. The autoimmune disease database: A dynamically compiled literature-derived database. BMC Bioinformatics 2006; 7: 325
  • Antonelli A, Tuomi T, Nannipieri M, Fallahi P, Nesti C, Okamoto H, Groop L, Ferrannini E. Autoimmunity to CD38 and GAD in type I and type II diabetes: CD38 and HLA genotypes and clinical phenotypes. Diabetologia 2002, 5: 1298–1306
  • Selmi C, Lleo A, Zuin M, Podda M, Rossaro L, Gershwin ME. Interferon alpha and its contribution to autoimmunity. Curr Opin Investig Drugs 2006; 7: 451–456
  • Royle P, Bain L, Waugh N. Systematic reviews of epidemiology in diabetes: Finding the evidence. BMC Med Res Methodol 2005, 5: 2
  • Ioannidis JP, Trikalinos TA, Khoury MJ. Implications of small effect sizes of individual genetic variants on the design and interpretation of genetic association studies of complex diseases. Am J Epidemiol 2006, (in press)
  • Cree BA, Khan O, Bourdette D, Goodin DS, Cohen JA, Marrie RA, Glidden D, Weinstock-Guttman B, Reich D, Patterson N, Haines JL, Pericak-Vance M, DeLoa C, Oksenberg JR, Hauser SL. Clinical characteristics of African Americans vs. Caucasian Americans with multiple sclerosis. Neurology 2004; 63: 2039–2045
  • Hershko AY, Naparstek Y. Autoimmunity in the era of genomics and proteomics. Autoimmun Rev 2006; 5: 230–233
  • Carl PL, Temple BR, Cohen PL. Most nuclear systemic autoantigens are extremely disordered proteins: Implications for the etiology of systemic autoimmunity. Arthritis Res Ther 2005, 7: R1360–R1374
  • Samarkos M, Vaiopoulos G. The role of infections in the pathogenesis of autoimmune diseases. Curr Drug Targets Inflamm Allergy 2005, 4: 99–103
  • Hamosh A, Scott AF, Amberger JS, Bocchini CA, McKusick VA. Nucleic Acids Res 2005; 33: D514–D517, Online Mendelian inheritance in man (OMIM), a knowledgebase of human genes and genetic disorders
  • Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. GenBank Nucleic Acids Res 2006; 34: D16–D20
  • Wu CH, Apweiler R, Bairoch A, Natale DA, Barker WC, Boeckmann B, Ferro S, Gasteiger E, Huang H, Lopez R, Magrane M, Martin MJ, Mazumder R, O'Donovan C, Redaschi N, Suzek B. The Universal Protein Resource (UniProt): An expanding universe of protein information. Nucleic Acids Res 2006; 34: D187–D191
  • Kouranov A, Xie L, de la Cruz J, Chen L, Westbrook J, Bourne PE, Berman HM. The RCSBPDB information portal for structural genomics. Nucleic Acids Res 2006; 34: D302–D305
  • Tong JC, Kong L, Tan TW, Ranganathan S. MPID-T: Database for sequence-structure–function information on T-cell receptor/peptide/MHC interactions. Appl Bioinformatics 2006; 5: 111–114
  • Rudolph MG, Stanfield RL, Wilson IA. How TCRs bind MHCs, peptides, and coreceptors. Annu Rev Immunol 2006; 24: 419–466
  • Smink LJ, Helton EM, Healy BC, Cavnor CC, Lam AC, Flamez D, Burren OS, Wang Y, Dolman GE, Burdick DB, Everett VH, Glusman G, Laneri D, Rowen L, Schuilenburg H, Walker NM, Mychaleckyj J, Wicker LS, Eizirik DL, Todd JA, Goodman N. T1DBase, a community web-based resource for type 1 diabetes research. Nucleic Acids Res 2005; 33: D544–D549
  • Scearce LM, Brestelli JE, McWeeney SK, Lee CS, Mazzarelli J, Pinney DF, Pizarro A, Stoeckert CJ, Jr, Clifton SW, Permutt MA, Brown J, Melton DA, Kaestner KH. Functional genomics of the endocrine pancreas: The pancreas clone set and PancChip, new resources for diabetes research. Diabetes 2002; 51: 1997–2004
  • Vita R, Vaughan K, Zarebski L, Salimi N, Fleri W, Grey H, Sathiamurthy M, Mokili J, Bui HH, Bourne PE, Ponomarenko J, de Castro R, Jr, Chan RK, Sidney J, Wilson SS, Stewart S, Way S, Peters B, Sette A. Curation of complex, context-dependent immunological data. BMC Bioinformatics 2006; 7: 341
  • Robinson J, Waller MJ, Parham P, de Groot N, Bontrop R, Kennedy LJ, Stoehr P, Marsh SG. IMGT/HLA MGT/MHC: Sequence databases for the study of the major histocompatibility complex. Nucleic Acids Res 2003; 31: 311–314
  • Giudicelli V, Duroux P, Ginestoux C, Folch G, Jabado-Michaloud J, Chaume D, Lefranc MP. IMGT/LIGM-DB, the IMGT comprehensive database of immunoglobulin and T cell receptor nucleotide sequences. Nucleic Acids Res 2006; 34: D781–D784
  • Stadler MB, Arnold D, Frieden S, Luginbuhl S, Stadler BM. Single nucleotide polymorphisms as a prerequisite for autoantigens. Eur J Immunol 2005, 35: 371–378
  • Wang CX, Teufel A, Cheruti U, Grotzinger J, Galle PR, Lohse AW, Herkel J. Characterization of human gene encoding SLA/LP autoantigen and its conserved homologs in mouse, fish, fly, and worm. World J Gastroenterol 2006, 12: 902–907
  • Ng B, Yang F, Huston DP, Yan Y, Yang Y, Xiong Z, Peterson LE, Wang H, Yang XF. Increased noncanonical splicing of autoantigen transcripts provides the structural basis for expression of untolerized epitopes. J Allergy Clin Immunol 2004, 114: 1463–1470
  • Yang F, Chen IH, Xiong Z, Yan Y, Wang H, Yang XF. Model of stimulation-responsive splicing and strategies in identification of immunogenic isoforms of tumor antigens and autoantigens. Clin Immunol 2006, (in press)
  • Kovvali G, Das KM. Molecular mimicry may contribute to pathogenesis of ulcerative colitis. FEBS Lett 2005, 579: 2261–2266
  • Kumar R, Eastwood AL, Brown ML, Laurie GW. Human genome search in celiac disease: Mutated gliadin T-cell-like epitope in two human proteins promotes T-cell activation. J Mol Biol 2002, 319: 593–602
  • Tsuchiya N, Kyogoku C. Role of Fc gamma receptor IIb polymorphism in the genetic background of systemic lupus erythematosus: Insights from Asia. Autoimmunity 2005; 38: 347–352
  • Trowsdale J. HLA genomics in the third millennium. Curr Opin Immunol 2005; 17: 498–504
  • Morris GA, Lowe CE, Cooper JD, Payne F, Vella A, Godfrey L, Hulme JS, Walker NM, Healy BC, Lam AC, Lyons PA, Todd JA. Polymorphism discovery and association analyses of the interferon genes in type 1 diabetes. BMC Genet 2006, 7: 12
  • Husser CS, Buchhalter JR, Raffo OS, Shabo A, Brown SH, Lee KE, Elkin PL. Standardization of microarray and pharmacogenomics data. Methods Mol Biol 2006; 316: 111–157
  • Azuaje F, Al-Shahrour F, Dopazo J. Ontology-driven approaches to analyzing data in functional genomics. Methods Mol Biol 2006; 316: 67–86
  • Ness SA. Basic microarray analysis: Strategies for successful experiments. Methods Mol Biol 2006, 316: 13–33
  • Giallourakis C, Henson C, Reich M, Xie X, Motha VK. Disease gene discovery through integrative genomics. Annu Rev Genomics Hum Genet 2005; 381–406
  • Tian L, Greenberg SA, Kong SW, Altschuler J, Kohane IS, Park PJ. Discovering statistically significant pathways in expression profiling studies. Proc Natl Acad Sci USA 2005, 102: 13544–13549
  • Melanitou E. Functional genomics in early autoimmunity. Ann N Y Acad Sci 2005, 1050: 64–72
  • Glocker MO, Guthke R, Kekow J, Thiesen HJ. Rheumatoid arthritis, a complex multifactorial disease: On the way toward individualized medicine. Med Res Rev 2006; 26: 63–87
  • Sparre T, Bergholdt R, Nerup J, Pociot F. Application of genomics and proteomics in type 1 diabetes pathogenesis research. Expert Rev Mol Diagn 2003, 3: 743–757
  • Oksenberg JR, Barcellos LF. Multiple sclerosis genetics: Leaving no stone unturned. Genes Immun 2005; 6(5)375–387, Aug
  • Balboni I, Chan SM, Kattah M, Tenenbaum JD, Butte AJ, Utz PJ. Multiplexed protein array platforms for analysis of autoimmune diseases. Annu Rev Immunol 2006; 24: 391–418
  • Wilkins MR, Appel RD, Van Eyk JE, Chung MC, Gorg A, Hecker M, Huber LA, Langen H, Link AJ, Paik YK, Patterson SD, Pennington SR, Rabilloud T, Simpson RJ, Weiss W, Dunn MJ. Guidelines for the next 10 years of proteomics. Proteomics 2006; 6: 4–8
  • Haoudi A, Bensmail H. Bioinformatics and data mining in proteomics. Expert Rev Proteomics 2006; 3: 333–343
  • Jensen ON. Interpreting the protein language using proteomics. Nat Rev Mol Cell Biol 2006; 7: 391–403
  • Englbrecht CC, Facius A. Bioinformatics challenges in proteomics. Comb Chem High Throughput Screen 2005; 8: 705–715
  • Orchard S, Taylor CF, Hermjakob H, Zhu W, Julian RK, Jr, Apweiler R. Advances in the development of common interchange standards for proteomic data. Proteomics 2004; 4: 2363–2365
  • Gasteiger E, Gattiker A, Hoogland C, Ivanyi I, Appel RD, Bairoch A. ExPASy: The proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res 2003; 31: 3784–3788
  • Frishman D, Schmidt T. PROMPT: A protein mapping and comparison tool. BMC Bioinformatics 2006; 7: 331
  • Hu Y, Hines LM, Weng H, Zuo D, Rivera M, Richardson A, LaBaer J. Analysis of genomic and proteomic data using advanced literature mining. J Proteome Res 2003; 2: 405–412
  • Noben JP, Dumont D, Kwasnikowska N, Verhaert P, Somers V, Hupperts R, Stinissen P, Robben J. Lumbar cerebrospinal fluid proteome in multiple sclerosis: Characterization by ultrafiltration, liquid chromatography, and mass spectrometry. J Proteome Res 2006; 5: 1647–1657
  • Li QZ, Xie C, Wu T, Mackay M, Aranow C, Putterman C, Mohan C. Identification of autoantibody clusters that best predict lupus disease activity using glomerular proteome arrays. J Clin Invest 2005; 115: 3428–3439
  • Gerling IC, Singh S, Lenchik NI, Marshall DR, Wu J. New data analysis and mining approaches identify unique proteome and transcriptome markers of susceptibility to autoimmune diabetes. Mol Cell Proteomics 2006; 5: 293–305
  • Ali M, Manolios N. Proteomics in rheumatology: A new direction for old diseases. Semin Arthritis Rheum 2005; 35: 67–76
  • Butte AJ, Kohane IS. Creation and implications of a phenome–genome network. Nat Biotechnol 2006; 24: 55–62
  • Hunter PJ, Borg TK. Integration from proteins to organs: The Physiome Project. Nat Rev Mol Cell Biol 2003; 4: 237–243
  • Coveney PV, Fowler PW. Modelling biological complexity: A physical scientist's perspective. J R Soc Interface 2005; 2: 267–280
  • Fathman CG, Soares L, Chan SM, Utz PJ. An array of possibilities for the study of autoimmunity. Nature 2005; 435: 605–611
  • Brusic V, Bajic VB, Petrovsky N. Computational methods for prediction of T-cell epitopes–a framework for modelling, testing, and applications. Methods 2004; 34: 436–443
  • Stevanovic S. Antigen processing is predictable: From genes to T cell epitopes. Transpl Immunol 2005; 14: 171–174
  • De Groot AS. Immunomics: Discovering new targets for vaccines and therapeutics. Drug Discov Today 2006; 11: 203–209
  • Rammensee H, Bachmann J, Emmerich NP, Bachor OA, Stevanovic S. SYFPEITHI: Database for MHC ligands and peptide motifs. Immunogenetics 1999; 50: 213–219
  • Reche PA, Glutting JP, Zhang H, Reinherz EL. Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles. Immunogenetics 2004; 56: 405–419
  • Lund O, Nielsen M, Kesmir C, Petersen AG, Lundegaard C, Worning P, Sylvester-Hvid C, Lamberth K, Roder G, Justesen S, Buus S, Brunak S. Definition of supertypes for HLA molecules using clustering of specificity matrices. Immunogenetics 2004; 55: 797–810
  • Zhang GL, Khan AM, Srinivasan KN, August JT, Brusic V. MULTIPRED: A computational system for prediction of promiscuous HLA binding peptides. Nucleic Acids Res 2005; 33: W172–W179
  • Rajapakse M, Zhang GL, Srinivasan KN, Schmidt B, Petrovsky N, Brusic V. PREDNOD, a prediction server for peptide binding to the H-2g7 haplotype of the non-obese diabetic mouse. Autoimmunity 2006; 40: 645–650
  • Surman S, Lockey TD, Slobod KS, Jones B, Riberdy JM, White SW, Doherty PC, Hurwitz JL. Localization of CD4+T cell epitope hotspots to exposed strands of HIV envelope glycoprotein suggests structural influences on antigen processing. Proc Natl Acad Sci USA 2001; 98: 4587–4592
  • Srinivasan KN, Zhang GL, Khan AM, August JT, Brusic V. Prediction of class I T-cell epitopes: Evidence of presence of immunological hot spots inside antigens. Bioinformatics 2004; 20: I297–I302
  • Tenzer S, Peters B, Bulik S, Schoor O, Lemmel C, Schatz MM, Kloetzel PM, Rammensee HG, Schild H, Holzhutter HG. Modeling the MHC class I pathway by combining predictions of proteasomal cleavage, TAP transport and MHC class I binding. Cell Mol Life Sci 2005; 62: 1025–1037
  • Doytchinova IA, Guan P, Flower DR. EpiJen: A server for multistep T cell epitope prediction. BMC Bioinformatics 2006; 7: 131
  • Moutaftsi M, Peters B, Pasquetto V, Tscharke DC, Sidney J, Bui HH, Grey H, Sette A. A consensus epitope prediction approach identifies the breadth of murine T(CD8+)-cell responses to vaccinia virus. Nat Biotechnol 2006; 24: 817–819
  • Tong JC, Bramson J, Kanduc D, Chow S, Sinha AA, Ranganathan S. Modeling the bound conformation of pemphigus vulgaris-associated peptides to MHC Class II DR and DQ Alleles. Immunome Res 2006; 2: 1
  • Huang L, Dai Y. Direct prediction of T-cell epitopes using support vector machines with novel sequence encoding schemes. J Bioinform Comput Biol 2006; 4: 93–107
  • Kosmopoulou A, Vlassi M, Stavrakoudis A, Sakarellos C, Sakarellos-Daitsiotis M. T-cell epitopes of the La/SSB autoantigen: Prediction based on the homology modeling of HLA-DQ2/DQ7 with the insulin-B peptide/HLA-DQ8 complex. J Comput Chem 2006; 27: 1033–1044
  • Flynn JC, McCormick DJ, Brusic V, Wan Q, Panos JC, Giraldo AA, David CS, Kong YC. Pathogenic human thyroglobulin peptides in HLA-DR3 transgenic mouse model of autoimmune thyroiditis. Cell Immunol 2004; 229: 79–85
  • Kamphuis S, Kuis W, de Jager W, Teklenburg G, Massa M, Gordon G, Boerhof M, Rijkers GT, Uiterwaal CS, Otten HG, Sette A, Albani S, Prakken BJ. Tolerogenic immune responses to novel T-cell epitopes from heat-shock protein 60 in juvenile idiopathic arthritis. Lancet 2005; 366: 50–56
  • Boin F, Wigley FM, Schneck JP, Oelke M, Rosen A. Evaluation of topoisomerase-1-specific CD8+T-cell response in systemic sclerosis. Ann N Y Acad Sci 2005; 1062: 137–145
  • Ichiki Y, Selmi C, Shimoda S, Ishibashi H, Gordon SC, Gershwin ME. Mitochondrial antigens as targets of cellular and humoral auto-immunity in primary biliary cirrhosis. Clin Rev Allergy Immunol 2005; 28: 83–91
  • Sollner J. Selection and combination of machine learning classifiers for prediction of linear B-cell epitopes on proteins. J Mol Recognit 2006; 19: 209–214
  • Saha S, Bhasin M, Raghava GP. Bcipep: A database of B-cell epitopes. BMC Genomics 2005; 6: 79
  • Larsen JE, Lund O, Nielsen M. Improved method for predicting linear B-cell epitopes. Immunome Res 2006; 2: 2
  • Alix A. Predictive estimation of protein linear epitopes by using the program PEOPLE. Vaccine 1999; 18: 311–314
  • Odorico M, Pellequer JL. BEPITOPE: Predicting the location of continuous epitopes and patterns in proteins. J Mol Recognit 2003; 16: 20–22
  • Blythe MJ, Flower DR. Benchmarking B cell epitope prediction: Underperformance of existing methods. Protein Sci 2005; 14: 246–248
  • Enshell-Seijffers D, Denisov D, Groisman B, Smelyanski L, Meyuhas R, Gross G, Denisova G, Gershoni JM. The mapping and reconstitution of a conformational discontinuous B-cell epitope of HIV-1. J Mol Biol 2003; 334: 87–101
  • Batori V, Friis EP, Nielsen H, Roggen EL. An in silico method using an epitope motif database for predicting the location of antigenic determinants on proteins in a structural context. J Mol Recognit 2006; 19: 21–29
  • Nyarady Z, Czompoly T, Bosze S, Nagy G, Petrohai A, Pal J, Hudecz F, Berki T, Nemeth P. Validation of in silico prediction by in vitro immunoserological results of fine epitope mapping on citrate synthase specific autoantibodies. Mol Immunol 2006; 43: 830–838
  • Lucchese A, Mittelman A, Lin MS, Kanduc D, Sinha AA. Epitope definition by proteomic similarity analysis: Identification of the linear determinant of the anti-Dsg3 MAb 5H10. J Transl Med 2004; 2: 43
  • Kemp EH, Waterman EA, Ajjan RA, Smith KA, Watson PF, Ludgate ME, Weetman AP. Identification of antigenic domains on the human sodium-iodide symporter which are recognized by autoantibodies from patients with autoimmune thyroid disease. Clin Exp Immunol 2001; 124: 377–385
  • Esposito M, Venkatesh V, Otvos L, Weng Z, Vajda S, Banki K, Perl A. Human transaldolase and cross-reactive viral epitopes identified by autoantibodies of multiple sclerosis patients. J Immunol 1999; 163: 4027–4032
  • Quintana FJ, Getz G, Hed G, Domany E, Cohen IR. Cluster analysis of human autoantibody reactivities in health and in type 1 diabetes mellitus: A bioinformatic approach to immune complexity. J Autoimmun 2003; 21: 65–75

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.