[1] Peters B, Sidney J, Bourne P, et al. The design and implementation of the immune epitope database and analysis resource[J]. Immunogenetics, 2005, 57(5):326-336.
[2] Fruci D, Lauvau G, Saveanu L, et al. Quantifying recruitment of cytosolic peptides for HLA class Ⅰ presentation:Impact of TAP transport[J]. J Immunol, 2003, 170(6):2977-2984.
[3] He Y, Xiang Z, Mobley H L. Vaxign:The first web-based vaccine design program for reverse vaccinology and applications for vaccine development[J]. J Biomed Biotechnol, 2010, 7(1):297505-297520.
[4] Trim P J, Snel M F. Small molecule MALDI MS imaging:Current technologies and future challenges[J]. Methods, 2016, 16(1):e11.
[5] Vandemoortele G, Gevaert K, Eyckerman S. Proteomics in the genome engineering era[J]. Proteomics, 2016, 16(2):177-187.
[6] Armengol E, Wiesmuller K H, Wienhold D, et al. Identification of T-cell epitopes in the structural and non-structural proteins of classical swine fever virus[J]. J Gen Virol, 2002, 83(3):551-560.
[7] Larsen J E, Lund O, Nielsen M. Improved method for predicting linear B-cell epitopes[J]. Immunome Res, 2006, 2(1):2-9.
[8] Saha S, Raghava G P. Prediction of continuous B-cell epitopes in an antigen using recurrent neural network[J]. Proteins, 2006, 65(1):40-48.
[9] Chen J, Liu H, Yang J, et al. Prediction of linear B-cell epitopes using amino acid pair antigenicity scale[J]. Amino Acids, 2007, 33(3):423-428.
[10] El-Manzalawy Y, Dobbs D, Honavar V. Predicting linear B-cell epitopes using string kernels[J]. J Mol Recognit, 2008, 21(4):243-255.
[11] Kringelum J V, Lundegaard C, Lund O, et al. Reliable B cell epitope predictions:Impacts of method development and improved benchmarking[J]. PLoS Comput Biol, 2012, 8(12):e1002829.
[12] Lian Y, Ge M, Pan X M. EPMLR:Sequence-based linear B-cell epitope prediction method using multiple linear regression[J]. BMC Bioinformatics, 2014, 15(1):414-420.
[13] Lian Y, Huang Z C, Ge M, et al. An Improved method for predicting linear B-cell epitope using deep maxout networks[J]. Biomed Environ Sci, 2015, 28(6):460-463.
[14] Sun J, Wu D, Xu T, et al. SEPPA:A computational server for spatial epitope prediction of protein antigens[J]. Nucleic Acids Res, 2009, 37(4):612-616.
[15] Garcia-Prieto F F, Fdez Galvan I, Aguilar M A, et al. Study on the conformational equilibrium of the alanine dipeptide in water solution by using the averaged solvent electrostatic potential from molecular dynamics methodology[J]. J Chem Phys, 2011, 135(19):194502-194511.
[16] Brenke R, Hall D R, Chuang G Y, et al. Application of asymmetric statistical potentials to antibody-protein docking[J]. Bioinformatics, 2012, 28(20):2608-2614.
[17] Hu Y J, Lin S C, Lin Y L,et al. A meta-learning approach for B-cell conformational epitope prediction[J]. BMC Bioinformatics, 2014, 15(1):378-393.
[18] Castrignano T, De Meo P D, Carrabino D, et al. The MEPS server for identifying protein conformational epitopes[J]. BMC Bioinformatics, 2007, 8(1):1-6.
[19] Chen W H, Sun P P, Lu Y, et al. MimoPro:A more efficient Web-based tool for epitope prediction using phage display libraries[J]. BMC Bioinformatics, 2011, 12(1):199-212.
[20] Zhao L, Li J Y. Mining for the antibody-antigen interacting associations that predict the B cell epitopes[J]. BMC Struct Biol, 2010, 10(suppl 1):1-6.
[21] Zhao L, Wong L, Li J Y. Antibody-specified B-cell epitope prediction in line with the principle of context-awareness[J]. IEEE/ACM Trans Comput Biol Bioinform, 2011, 8(6):1483-1494.
[22] Sun P, Qi J, Zhao Y, et al. A novel conformational B-cell epitope prediction method based on mimotope and patch analysis[J]. J Theor Biol, 2016, 394(1):102-108.
[23] Huang W L, Tsai M J, Hsu K T, et al. Prediction of linear B-cell epitopes of hepatitis C virus for vaccine development[J]. BMC Med Genomics, 2015, 8(14):1-3.
[24] Saravanan V, Gautham N. Harnessing computational biology for exact linear B-cell epitope prediction:A novel amino acid composition-based feature descriptor[J]. OMICS, 2015, 19(10):648-658.
[25] Guan P, Doytchinova I A, Zygouri C, et al. MHCPred:A server for quantitative prediction of peptide-MHC binding[J]. Nucleic Acids Res, 2003, 31(13):3621-3624.
[26] Parker K C, Bednarek M A, Coligan J E. Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side-chains[J]. J Immunol, 1994, 152(1):163-175.
[27] Rammensee H, Bachmann J, Emmerich N P, et al. SYFPEITHI:Database for MHC ligands and peptide motifs[J]. Immunogenetics, 1999, 50(3-4):213-219.
[28] Wang B, Chen H, Jiang X, et al. Identification of an HLA-A*0201-restricted CD8+ T-cell epitope SSp-1 of SARS-CoV spike protein[J]. Blood, 2004, 104(1):200-206.
[29] Abdel-Hady K M, Gutierrez H, Terry F, et al. Identification and retrospective validation of T-cell epitopes in the hepatitis C virus genotype 4 proteome:An accelerated approach toward epitope-driven vaccine development[J]. Hum Vaccin Immunother, 2014, 10(8):2366-2377.
[30] Bhasin M, Raghava G P. A hybrid approach for predicting promiscuous MHC class Ⅰ restricted T cell epitopes[J]. J Biosci, 2007, 32(1):32-42.
[31] Zhang G L, DeLuca D S, Keskin D B, et al. MULTIPRED:A computational system for prediction of promiscuous HLA binding peptides[J]. Nucleic Acids Res, 2005, 33(6):172-179.
[32] Vita R, DeLuca D S, Keskin D B, et al. The immune epitope database 2.0[J]. Nucleic Acids Res, 2010, 38(10):854-862.
[33] Larsen M V, Lundegaard C, Lamberth K, et al. Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction[J]. BMC Bioinformatics, 2007, 8(1):424-435.
[34] Donnes P, Kohlbacher O. Integrated modeling of the major events in the MHC class Ⅰ antigen processing pathway[J]. Protein Sci, 2005, 14(8):2132-2140.
[35] Lundegaard C, Lamberth K, Harndahl M, et al. NetMHC-3.0:Accurate web accessible predictions of human, mouse and monkey MHC class Ⅰ affinities for peptides of length 8-11[J]. Nucleic Acids Res, 2008, 36(12):509-512.
[36] Farrell D, Gordon S V. Epitopemap:A web application for integrated whole proteome epitope prediction[J]. BMC Bioinformatics, 2015, 16(1):221-227.
[37] Lu Y F, Sheng H, Zhang Y, et al. Computational prediction of cleavage using proteasomal in vitro digestion and MHC Ⅰ ligand data[J]. J Zhejiang Univ Sci B, 2013, 14(9):816-828.
[38] Schubert B, Brachvogel H P, Jurges C, et al. EpiToolKit-a web-based workbench for vaccine design[J]. Bioinformatics, 2015, 31(13):2211-2231.
[39] Atanasova M, Patronov A, Dimitrov I, et al. EpiDOCK:A molecular docking-based tool for MHC class Ⅱ binding prediction[J]. Protein Eng Des Sel, 2013, 26(10):631-641.
[40] Grabowska A K, Kaufmann A M, Riemer A B. Identification of promiscuous HPV 16-derived T helper cell epitopes for therapeutic HPV vaccine design[J]. Int J Cancer, 2015,136(1):212-224.
[41] Lohia N, Baranwal M. Identification of conserved peptides comprising multiple T cell epitopes of matrix 1 protein in H1N1 influenza virus[J]. Viral Immunol, 2015, 28(10):570-579.
[42] Shahsavandi S, Ebrahimi M M, Sadeghi K, et al. Design of a heterosubtypic epitope-based peptide vaccine fused with hemokinin-1 against influenza viruses[J]. Virol Sin, 2015, 30(3):200-207.
[43] Duan Z L, Liu H F, Huang X, et al. Identification of conserved and HLA-A*2402-restricted epitopes in Dengue virus serotype 2[J]. Virus Res, 2015, 196(1):5-12.
[44] Liao Y C, Lin H H, Lin C H, et al. Identification of cytotoxic T lymphocyte epitopes on swine viruses:Multi-epitope design for universal T cell vaccine[J]. PLoS One, 2013, 8(12):e84443.
[45] Manijeh M, Mehrnaz K, Violaine M, et al. In silico design of discontinuous peptides representative of B and T-cell epitopes from HER 2-ECD as potential novel cancer peptide vaccines[J]. Asian Pac J Cancer Prev, 2013, 14(10):5973-5981.
[46] Park H, Chung Y S, Yoon C H, et al. Presentation of available CTL epitopes that induction of cell-mediatedimmune response against HIV-1 Koran clade B strain using computational technology[J]. HIV Med, 2015, 17(6):460-466.
[47] Sela-Culang I, Ashkenazi S, Peters B, et al. PEASE:Predicting B-cell epitopes utilizing antibody sequence[J]. Bioinformatics, 2015, 31(8):1313-1325.
[48] Mardis E R. The impact of next-generation sequencing technology on genetics[J]. Trends Genet, 2008, 24(3):133-141.
[49] Whitehead T A, Chevalie A, Song Y, et al. Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing[J]. Nat Biotechnol, 2012, 30(6):543-548.
[50] He L, Sok D, Azadnia P, et al. Toward a more accurate view of human B-cell repertoire by next-generation sequencing, unbiased repertoire capture and single-molecule barcoding[J]. Sci Rep, 2014, 4(1):6778-6790.
[51] Tschochner M, Leary S, Cooper D, et al. Identifying patient-specific epstein-barr nuclear antigen-1 genetic variation and potential autoreactive targets relevant to multiple sclerosis pathogenesis[J]. PLoS One, 2016, 11(2):e0147567.
[52] Yu Y, R Ceredig, C Seoighe. LymAnalyzer:A tool for comprehensive analysis of next generation sequencing data of T cell receptors and immunoglobulins[J]. Nucleic Acids Res, 2016, 44(4):e31.
[53] Van Blarcom T, Rossi A, Foletti D, et al. Precise and efficient antibody epitope determination through library design, yeast display and next-generation sequencing[J]. J Mol Biol, 2015, 427(6):1513-1534.
[54] Doolan K M, Colby D W. Conformation-dependent epitopes recognized by prion protein antibodies probed using mutational scanning and deep sequencing[J]. J Mol Biol, 2015, 427(2):328-340.
[55] Allegra C J, Rumble R B, Hamilton S R, et al. Extended RAS gene mutation testing in metastatic colorectal carcinoma to predict response to anti-epidermal growth factor receptor monoclonal antibody therapy:American society of clinical oncology provisional clinical opinion update 2015[J]. J Clin Oncol, 2016, 34(2):179-185.
[56] Hart J R, Zhang Y, Liao L, et al. The butterfly effect in cancer:A single base mutation can remodel the cell[J]. Proc Natl Acad Sci USA, 2015, 112(4):1131-1136.
[57] Alam M, Vance D E, Lehner R. Structure-function analysis of human triacylglycerol hydrolase by site-directed mutagenesis:Identification of the catalytic triad and a glycosylation site[J]. Biochemistry, 2002, 41(21):6679-6687.
[58] An M C, O' Brien R N, Zhang N, et al. Polyglutamine disease modeling:Epitope based screen for homologous recombination using CRISPR/Cas9 system[J]. PLoS Curr, 2014, 6(1):1-18.
[59] Keilhauer E C, Hein M Y, Mann M. Accurate protein complex retrieval by affinity enrichment mass spectrometry (AE-MS) rather than affinity purification mass spectrometry (AP-MS)[J]. Mol Cell Proteomics, 2015, 14(1):120-135.
[60] Hansen T H, Bouvier M. MHC class Ⅰ antigen presentation:Learning from viral evasion strategies[J]. Nat Rev Immunol, 2009, 9(7):503-513.
[61] Lopez D, Lorente E, Barriga A, et al. Vaccination and the TAP-independent antigen processing pathways[J]. Expert Rev Vaccine, 2013, 12(9):11077-11083.
[62] Gil-Torregrosa B C, Castano A R, Lopez D, et al. Generation of MHC class Ⅰ peptide antigens by protein processing in the secretory route by furin[J]. Traffic, 2000, 1(8):641-651.
[63] Doorduijn E M, Sluijter M, Querido B J, et al. TAP-independent self-peptides enhance T cell recognition of immune-escaped tumors[J]. J Clin Invest, 2016, 126(2):784-794.
[64] Weinzierl A O, Rudolf D, Hillen N, et al. Features of TAP-independent MHC class Ⅰ ligands revealed by quantitative mass spectrometry[J]. Eur J Immunol, 2008, 38(6):1503-1510.
[65] Rodriguez-Garcia A, Svensson E, Gil-Hoyo R, et al. Insertion of exogenous epitopes in the E3-19K of oncolytic adenoviruses to enhance TAP-independent presentation and immunogenicity[J]. Gene Ther, 2015, 22(7):596-601. |