{"id":81,"date":"2010-07-08T16:19:57","date_gmt":"2010-07-08T16:19:57","guid":{"rendered":"http:\/\/blogviejo.sld.cu\/oserranob\/?page_id=81"},"modified":"2023-01-24T17:25:16","modified_gmt":"2023-01-24T17:25:16","slug":"inmunoinformatica","status":"publish","type":"page","link":"https:\/\/blogs.sld.cu\/oserranob\/inmunoinformatica\/","title":{"rendered":"INMUNOINFO"},"content":{"rendered":"

En esta p\u00e1gina encontrar\u00e1 recursos e informaciones sobre las aplicaciones bioinform\u00e1ticas relacionadas con el sistema inmune.<\/p>\n

BASES DE DATOS Y HERRAMIENTAS:<\/strong><\/p>\n

ALLERGOME<\/strong><\/a>: Base de datos sobre alergenos reportados que inducen respuesta IgE y otras fuentes de alergias, aunque no se haya identificado la mol\u00e9cula responsable. Requiere registro<\/strong>.<\/p>\n

BIMAS<\/strong><\/a>: Permite predecir p\u00e9ptidos de una prote\u00edna a ser presentados por una mol\u00e9cula MHC particular.<\/p>\n

Bcepred<\/strong><\/a>: Predicci\u00f3n de ep\u00edtopes B lineales a partir de propiedades fisicoqu\u00edmicas.<\/p>\n

CTLPred<\/strong><\/a>: Predicci\u00f3n de ep\u00edtopes CTL basado en m\u00e1quina de soporte vectorial y red neuronal artificial.<\/p>\n

dbMHC<\/strong><\/a>: base con datos cl\u00ednicos y de secuencia del MHC (Major Histocompatibility Complex<\/em>) humano.<\/p>\n

EpiSearch<\/strong><\/a>: Busca ep\u00edtopes conformacionales a partir de una secuencia.<\/p>\n

FluKB<\/strong><\/a>: Propiedades inmunol\u00f3gicas de virus de la influenza.<\/p>\n

HLA-DR4Pred<\/strong><\/a>: Predicci\u00f3n de p\u00e9ptidos con afinidad por HLA-DRB1*0401, basado en m\u00e1quina de soporte vectorial y red neuronal artificial.<\/p>\n

HLAPred<\/strong><\/a>: Predicci\u00f3n de p\u00e9ptidos con afinidad para MHC-I y -II.<\/p>\n

HIV Molecular Immunology Database<\/strong><\/a>: colecci\u00f3n de ep\u00edtopes T, para CD4 y CD8, as\u00ed como sitios de uni\u00f3n de anticuerpos para VIH-1.<\/p>\n

IEDB<\/strong><\/a>: Immune Epitope Database and Analysis Resource, contiene datos sobre ep\u00edtopes T y de anticuerpos de origen humano y de otras especies.<\/p>\n

IMGT<\/strong><\/a>: Proyecto internacional ImMunoGeneTics, una colecci\u00f3n de bases de datos integradas, especializadas en inmunoglobulinas, receptores de c\u00e9lulas T y el MHC de vertebrados.<\/p>\n

ImmPort<\/strong><\/a>: Immunology Database and Analysis Portal, almac\u00e9n de datos (data warehouse<\/em>) obtenidos por investigadores del NIAID<\/a>.<\/p>\n

MAPP<\/strong><\/a>: Predice ep\u00edtopes con afinidad por MHC-I de humanos y otras especies.<\/p>\n

MHCBench<\/strong><\/a>: Interfase con varios algoritmos de predicci\u00f3n de p\u00e9ptidos con afinidad por MHC.<\/p>\n

MMBPred<\/strong><\/a>: Predicci\u00f3n de secuencias mutadas de alta afinidad por MHC-I.<\/p>\n

MOT<\/strong><\/a>: T\u00e9cnica de optimizaci\u00f3n de matrices para la predicci\u00f3n de uni\u00f3n a MHC-II.<\/p>\n

NetChop<\/strong><\/a>: Predice sitios de escisi\u00f3n por proteasoma.<\/p>\n

NetMHCIIpan-2.0<\/strong><\/a>: Predice uni\u00f3n de p\u00e9ptidos a m\u00e1s de 500 alelos HLA-DR por medio de redes neurales artificiales.<\/p>\n

nHLAPred<\/strong><\/a>: Predicci\u00f3n de p\u00e9ptidos con afinidad para MHC-I, basado en\u00a0red neuronal.<\/p>\n

PAProC<\/strong><\/a>: Predice sitios de escisi\u00f3n por el proteasoma.<\/p>\n

ProPred-I<\/strong><\/a>: Servicio en l\u00ednea para identificar regiones con afinidad por MHC-I en ant\u00edgenos.<\/p>\n

ProPred<\/strong><\/a>: Herramientas para identificar ep\u00edtopes con afinidad por MHC-II.<\/p>\n

SDAP <\/strong><\/a>– Structural Database of Allergenic Proteins: Base de datos de prote\u00ednas alerg\u00e9nicas con varias herramientas computacionales para estudios de alergenos.<\/p>\n

SYFPEITHI<\/strong><\/a>: Base de datos con m\u00e1s de 7000 p\u00e9ptidos con afinidad por MHC I y II. Permite hacer predicci\u00f3n de p\u00e9ptidos a partir de una secuencia de prote\u00edna.<\/p>\n

 <\/p>\n

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ART\u00cdCULOS DE INTER\u00c9S:<\/strong><\/p>\n

– Clifford JN,\u00a0H\u00f8ie MH,\u00a0Deleuran S,\u00a0Peters B,\u00a0Nielsen M,\u00a0Marcatili P. BepiPred-3.0: Improved B-cell epitope prediction using protein language models<\/strong><\/a>. Protein Sci. 2022 Dec;31(12):e4497.<\/p>\n

– Moghram BA, Nabil E, Badr A. Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design<\/strong><\/a>. Comput Methods Programs Biomed. 2018 Jan;153:161-170.<\/p>\n

– Dhanik A, Kirshner JR, MacDonald D, Thurston G, Lin HC, Murphy AJ, et al<\/em>. In-silico discovery of cancer-specific peptide-HLA complexes for targeted therapy<\/strong><\/a>. BMC Bioinformatics 2016;17:286.<\/p>\n

– Dar H, Zaheer T, Rehman MT, Ali A, Javed A, Khan GA, et al<\/em>. Prediction of promiscuous T-cell epitopes in the Zika virus polyprotein: An in silico approach<\/strong><\/a>. Asian Pac J Trop Med. 2016 Sep;9(9):844-50.<\/p>\n

– Tapia D, Ross BN, Kalita A, Kalita M, Hatcher CL, Muruato LA, et al<\/em>. From In silico Protein Epitope Density Prediction to Testing Escherichia coli O157:H7 Vaccine Candidates in a Murine Model of Colonization<\/a><\/strong>. Front Cell Infect Microbiol. 2016 Aug 30;6:94.<\/p>\n

– de Freitas R, Gomes LF, Zaldini M, Felinto ME, Coutinho B, da Silva AA, et al<\/em>. Combination of In Silico Methods in the Search for Potential CD4+ and CD8+ T Cell Epitopes in the Proteome of Leishmania braziliensis<\/a><\/strong>. Front. Immunol., 29 August 2016; http:\/\/dx.doi.org\/10.3389\/fimmu.2016.00327.<\/p>\n

– Hackl H, Charoentong P, Finotello F, Trajanoski Z. Computational genomics tools for dissecting tumour\u2013immune cell interactions<\/a><\/strong>. Nature Reviews Genetics 2016;17:441\u2013458.<\/p>\n

– Sheikh QM, Gatherer D, Reche PA, Flower DR. Towards the Knowledge-based Design of Universal Influenza Epitope Ensemble Vaccines<\/a><\/strong>. Bioinformatics 2016; doi: 10.1093\/bioinformatics\/btw399.<\/p>\n

– Levy M, Thaiss CA, Elinav E. Metagenomic cross-talk: the regulatory interplay between immunogenomics and the microbiome<\/a><\/strong>. Genome Medicine 2015;7:120.<\/p>\n

– Backert L, Kohlbacher O. Immunoinformatics and epitope prediction in the age of genomic medicine<\/strong><\/a>. Genome Medicine 2015;7:119.<\/p>\n

– Schultze JL. Teaching ‘big data’ analysis to young immunologists<\/a><\/strong>. Nature Immunology 2015;16:902\u2013905.<\/p>\n

– Vishnu Udayakumar S, Sankarasubramanian J, Gunasekaran P, Rajendhran J. Novel Vaccine Candidates against Brucella melitensis Identified through Reverse Vaccinology Approach<\/a><\/strong>. OMICS: A Journal of Integrative Biology November 2015;19(11):722-729.<\/p>\n

– Molero-Abraham M, Glutting JP, Flower DR, Lafuente EM, Reche PA. EPIPOX: Immunoinformatic Characterization of the Shared T-Cell Epitome between Variola Virus and Related Pathogenic Orthopoxviruses<\/a><\/strong>. J Immunol Res. 2015;2015:738020.<\/p>\n

– Simon C, Kudahl UJ, Sun J, Olsen LR, Zhang GL, Reinherz EL, et al<\/em>. FluKB: A Knowledge-Based System for Influenza Vaccine Target Discovery and Analysis of the Immunological Properties of Influenza Viruses<\/strong><\/a>. Journal of Immunology Research 2015;2015:380975.<\/p>\n

– Tyagi N, Farnell EJ, Fitzsimmons CM, Ryan S, Tukahebwa E, Maizels RM, et al<\/em>. Comparisons of Allergenic and Metazoan Parasite Proteins: Allergy the Price of Immunity<\/strong><\/a>. PLoS Comput Biol 2015;11(10):e1004546.<\/p>\n

– Tsangemail JS. Utilizing population variation, vaccination, and systems biology to study human immunology<\/strong><\/a>. Trends in Immunology August 2015;36(8):479\u2013493.<\/p>\n

– Pellegrino P, Falvella FS, Perrone V, Carnovale C, Brusadelli T, Pozzi M, et al<\/em>. The first steps towards the era of personalised vaccinology: predicting adverse reactions<\/a><\/strong>. The Pharmacogenomics Journal 2015;15:284\u2013287.<\/p>\n

– Calis JJA, Reinink P, Keller C, Kloetzel PM, Kesmir C. Role of peptide processing predictions in T cell epitope identification: contribution of different prediction programs<\/strong><\/a>. Immunogenetics February 2015;67(2):85-93.<\/p>\n

– Schubert B, Brachvogel HP, J\u00fcrges CH, Kohlbacher O. EpiToolKit\u2014a web-based workbench for vaccine design<\/strong><\/a>. Bioinformatics 2015; doi: 10.1093\/bioinformatics\/btv116.<\/p>\n

– Oany AR, Ahmad SA, Hossain MU, Jyoti TP. Identification of highly conserved regions in L-segment of Crimean-Congo hemorrhagic fever virus and immunoinformatic prediction about potential novel vaccine<\/a><\/strong>. Adv Appl Bioinform Chem. 2015 Jan 8;8:1-10.<\/p>\n

– Jameson-Lee M, Koparde V, Griffith P, Scalora AF, Sampson JK, Khalid H, et al<\/em>. In silico derivation of HLA-specific alloreactivity potential from whole exome sequencing of stem-cell transplant donors and recipients: understanding the quantitative immunobiology of allogeneic transplantation<\/strong><\/a>. Front. Immunol., 06 November 2014; doi: 10.3389\/fimmu.2014.00529.<\/p>\n

– Pappalardo F, Brusic V, Castiglione F, Sch\u00f6nbach C. Computational and bioinformatics techniques for immunology<\/strong><\/a>. Biomed Res Int. 2014;2014:263189.<\/p>\n

– Moorhouse MJ, van Zessen D, IJspeert H, Hiltemann S, Horsman S, van der Spek PJ, et al<\/em>. ImmunoGlobulin galaxy (IGGalaxy) for simple determination and quantitation of immunoglobulin heavy chain rearrangements from NGS<\/strong><\/a>. BMC Immunology 2014;15:59.<\/p>\n

– McGarvey PB, Suzek BE, Baraniuk JN, Rao S, Conkright B, Lababidi S, et al<\/em>. In silico analysis of autoimmune diseases and genetic relationships to vaccination against infectious diseases<\/strong><\/a>. BMC Immunology 2014;15:61.<\/p>\n

– Curigliano G. From precision medicine to cancer care through the immunome: highlights from the European Society of Medical Oncology Congress, Madrid, 26-30th September 2014<\/a><\/strong>. Ecancermedicalscience. 2014 Oct 16;8:472.<\/p>\n

– Teh-Poot C, Tzec-Arjona E, Martinez-Vega P, Ramirez-Sierra MJ, Rosado-Vallado M, Dumonteil E. From genome to a vaccine against Trypanosoma cruzi<\/em> by immunoinformatics<\/a><\/strong>. J Infect Dis. 2014 Jul 28; doi: 10.1093\/infdis\/jiu418.<\/p>\n

– Snijder B, Kandasamy RK, Superti-Furga G. Toward effective sharing of high-dimensional immunology data<\/strong><\/a>. Nature Biotechnology 2014;32:755\u2013759.<\/p>\n

– Zhang GL, Sun J, Chitkushev L, Brusic V. Big data analytics in immunology: a knowledge-based approach<\/a><\/strong>. Biomed Res Int. 2014:437987. doi: 10.1155\/2014\/437987.<\/p>\n

– Zhang S, Desrosiers J, Aponte-Pieras JR, DaSilva K, Fast LD, et al<\/em>. Human Immune Responses to H. pylori HLA Class II Epitopes Identified by Immunoinformatic Methods<\/strong><\/a>. PLoS ONE 2014;9(4):e94974.<\/p>\n

– Gaze S, Driguez P, Pearson MS, Mendes T, Doolan DL, et al<\/em>. An Immunomics Approach to Schistosome Antigen Discovery: Antibody Signatures of Naturally Resistant and Chronically Infected Individuals from Endemic Areas<\/strong><\/a>. PLoS Pathog 2014;10(3):e1004033.<\/p>\n

– Zhang GL, Riemer AB, Keskin DB, Chitkushev L, Reinherz EL, Brusic V. HPVdb: a data mining system for knowledge discovery in human papillomavirus with applications in T cell immunology and vaccinology<\/a><\/strong>. Database 2014 Apr 4;2014:bau031. doi: 10.1093\/database\/bau031.<\/p>\n

– Zhong J, Sharma J, Raju R, Palapetta SM, Prasad TSK, Huang TC, et al. TSLP signaling pathway map: a platform for analysis of TSLP-mediated signaling<\/strong><\/a>. Database 2014:bau007; doi: 10.1093\/database\/bau007.<\/p>\n

– Dimitrakopoulou K, Dimitrakopoulos GN, Wilk E, Tsimpouris C, Sgarbas KN, Schughart K, Bezerianos A. Influenza A Immunomics and Public Health Omics: The Dynamic Pathway Interplay in Host Response to H1N1 Infection<\/strong>. <\/a>OMICS: A Journal of Integrative Biology. February 10, 2014; doi:10.1089\/omi.2013.0062.<\/p>\n

– Whelan FJ, Yap NVL, Surette MG, Golding GB, Bowdish DME. A guide to bioinformatics for immunologists<\/strong><\/a>. Front. Immunol. 04 December 2013; doi: 10.3389\/fimmu.2013.00416.<\/p>\n

– Grifoni A, Montesano C, Patronov A, Colizzi V, Amicosante M. Immunoinformatic Docking Approach for the Analysis of KIR3DL1\/HLA-B Interaction<\/strong><\/a>. BioMed Research International 2013;283805.<\/p>\n

– Addine BC, Marr\u00f3n R, Calero R, Mirabal M, Ram\u00edrez JC, Sarmiento ME, et al. In silico identification of common epitopes from pathogenic mycobacteria<\/strong><\/a>. BMC Immunology 2013;14(Suppl 1):S6.<\/p>\n

– Patronov A, Doytchinova I. T-cell epitope vaccine design by immunoinformatics<\/strong><\/a>. Open Biol. 2013;3:120-139.<\/p>\n

– Sun J, Kudahl UJ, Simon C, Cao Z, Reinherz EL, Brusic V. Large-scale analysis of B-cell epitopes on influenza virus hemagglutinin \u2013 implications for cross-reactivity of neutralizing antibodies<\/strong><\/a>. Front. Immunol., 07 February 2014;doi: 10.3389\/fimmu.2014.00038.<\/p>\n

– Olsen LR, Kudahl UJ, Simon C, Sun J, Sch\u00f6nbach C, Reinherz EL, et al. BlockLogo: visualization of peptide and sequence motif conservation. J Immunol Methods<\/strong><\/a>. 2013 Dec 31;400-401:37-44.<\/p>\n

– Priya Doss CG, Nagasundaram N, Srajan J, Chiranji C. LSHGD: A database for human leprosy susceptible genes<\/strong><\/a>. Genomics September 2012;100(3):162\u2013166.<\/p>\n

– Benichou J, Ben-Hamo R, Louzoun Y, Efroni S. Rep-Seq: uncovering the immunological repertoire through next-generation sequencing<\/strong><\/a>. Immunology March 2012;135(3):183\u2013191.<\/p>\n

– Zhang L, Chen Y, Wong H-S, Zhou S, Mamitsuka H, et al. TEPITOPEpan: Extending TEPITOPE for Peptide Binding Prediction Covering over 700 HLA-DR Molecules<\/strong><\/a>. PLoS ONE 2012;7(2): e30483.<\/p>\n

– Seib KL, Zhao X, Rappuoli R. Developing vaccines in the era of genomics: a decade of reverse vaccinology<\/strong><\/a>. Clinical Microbiology and Infection 2012;18:109-116.<\/p>\n

– Levitz L, Koita OA, Sangare K, Ardito MT, Boyle CM, Rozehnal J et al<\/em>. Conservation of HIV-1 T cell epitopes across time and clades: Validation of immunogenic HLA-A2 epitopes selected for the GAIA HIV vaccine<\/strong><\/a>. Retrovirology. 2012;9(Suppl 2):P294.<\/p>\n

– Saethang T, Hirose O, Kimkong I, Tran VA, Dang XT, Nguyen LA et al<\/em>. EpicCapo: epitope prediction using combined information of amino acid pairwise contact potentials and HLA-peptide contact site information<\/strong><\/a>. BMC Bioinformatics 2012, 13:313.<\/p>\n

– Prabdial-Sing N, Puren AJ, Bowyer SM. Sequence-based in silico analysis of well studied Hepatitis C Virus epitopes and their variants in other genotypes (particularly genotype 5a) against South African human leukocyte antigen backgrounds<\/strong><\/a>. BMC Immunology 2012;13:67.<\/p>\n

– Kim Y, Ponomarenko J, Zhu Z, Tamang D, Wang P, Greenbaum J et al<\/em>. Immune epitope database analysis resource<\/strong><\/a>. Nucl. Acids Res. 2012;40(W1):W525-W530.<\/p>\n

– Chailyan A, Tramontano A, Marcatili P. A database of immunoglobulins with integrated tools: DIGIT<\/strong><\/a>. Nucl. Acids Res. 2012;40(D1):D1230-D1234.<\/p>\n

– Moss SF, Moise L, Lee DS, Kim W, Zhang S, Lee J et al. HelicoVax: Epitope-based therapeutic H. pylori vaccination in a mouse model<\/strong><\/a>. Vaccine. 2011 March 3;29(11):2085\u20132091.<\/p>\n

– Patronov A, Dimitrov I, Flower DR, Doytchinova I. Peptide binding prediction for the human class II MHC allele HLA-DP2: a molecular docking approach<\/strong><\/a>. BMC Structural Biology 2011;11:32.<\/p>\n

– Megan M. O’Meara and Mary L. Disis. Therapeutic Cancer Vaccines and Translating Vaccinomics Science to the Global Health Clinic: Emerging Applications Toward Proof of Concept<\/strong><\/a>. OMICS: A Journal of Integrative Biology. September 2011;15(9):579-588.<\/p>\n

– Bagnoli F, Baudner B, Mishra RPN, Bartolini E, Fiaschi L, Mariotti P, et al<\/em>. Designing the Next Generation of Vaccines for Global Public Health<\/strong><\/a>. OMICS: A Journal of Integrative Biology. September 2011;15(9):545-566.<\/p>\n

– Poland GA, Ovsyannikova IG, Kennedy RB, Haralambieva IH, Jacobson RM. Vaccinomics and a New Paradigm for the Development of Preventive Vaccines Against Viral Infections<\/strong><\/a>. OMICS: A Journal of Integrative Biology. September 2011;15(9):625-636.<\/p>\n

– Bocanegra-Garc\u00eda V, Valencia-Delgadillo J, Cruz-Pulido W, Cant\u00fa-Ram\u00edrez R, Rivera-S\u00e1nchez G, Palma-Nicol\u00e1s JP. De la gen\u00e9tica a la gen\u00f3mica en el dise\u00f1o de nuevas vacunas contra la tuberculosis<\/strong><\/a>. Enferm Infecc Microbiol Clin. 2011;29(8):609-14.<\/p>\n

– Loukas A, Gaze S, Mulvenna JP, Gasser RB, Brindley PJ, Doolan DL et al. Vaccinomics for the Major Blood Feeding Helminths of Humans<\/strong><\/a>. OMICS: A Journal of Integrative Biology. Online Ahead of Print: June 16, 2011.<\/p>\n

– Bremel RD, Homan EJ. An integrated approach to epitope analysis II: A system for proteomic-scale prediction of immunological characteristics<\/strong><\/a>. Immunome Research 2010;6:8.<\/p>\n

– Bremel RD, Homan EJ. An integrated approach to epitope analysis I: Dimensional reduction, visualization and prediction of MHC binding using amino acid principal components and regression approaches<\/strong><\/a>. Immunome Research 2010;6:7.<\/p>\n

– Ansari HR, Raghava GPS. Identification of conformational B-cell Epitopes in an antigen from its primary sequence<\/strong><\/a>. Immunome Research 2010;6:6.<\/p>\n

– Cong H, Mui EJ, Witola WH, Sidney J, Alexander J, Sette A et al. Human immunome, bioinformatic analyses using HLA supermotifs and the parasite genome, binding assays, studies of human T cell responses, and immunization of HLA-A*1101 transgenic mice including novel adjuvants provide a foundation for HLA-A03 restricted CD8+T cell epitope based, adjuvanted vaccine protective against Toxoplasma gondii<\/em><\/strong><\/a>. Immunome Research 2010;6:12.<\/p>\n

– Nielsen M, Justesen S, Lund O, Lundegaard C, Buus S. NetMHCIIpan-2.0 – Improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedure<\/strong><\/a>. Immunome Research 2010;6:9.<\/p>\n

– Wee LJK, Simarmata D, Kam YW, Ng LFP, Tong JC. SVM-based prediction of linear B-cell epitopes using Bayes Feature Extraction<\/strong><\/a>. BMC Genomics 2010, 11(Suppl 4):S21.<\/p>\n

– Lane J, Duroux P, Lefranc MP. From IMGT-ONTOLOGY to IMGT\/LIGMotif: the IMGT\u00ae standardized approach for immunoglobulin and T cell receptor gene identification and description in large genomic sequences<\/strong><\/a>. BMC Bioinformatics 2010;11:223.<\/p>\n

– Flower DR, Macdonald IK, Ramakrishnan K, Davies MN, Doytchinova IA. Computer aided selection of candidate vaccine antigens<\/strong><\/a>.\u00a0 Immunome Res. 2010; 6(Suppl 2):S1.<\/p>\n

– Dimitrov I, Garnev P, Flower DR, Doytchinova I. EpiTOP\u2014a proteochemometric tool for MHC class II binding prediction<\/strong><\/a>.\u00a0 Bioinformatics 2010;26(16):2066-2068.<\/p>\n

– Dimitrov I, Garnev P, Flower DR, Doytchinova I. MHC Class II Binding Prediction\u2014A Little Help from a Friend<\/strong><\/a>. J Biomed Biotechnol. 2010;2010:705821.<\/p>\n

– Zhao l, Li J. Mining for the antibody-antigen interacting associations that predict the B cell epitopes<\/strong><\/a>. BMC Structural Biology 2010;10(Suppl 1):S6.<\/p>\n

– Ehrenmann F, Kaas Q, Lefranc MP. IMGT\/3Dstructure-DB and IMGT\/DomainGapAlign: a database and a tool for immunoglobulins or antibodies, T cell receptors, MHC, IgSF and MhcSF<\/strong><\/a>. Nucleic Acids Research 2010;38(Database issue):D301-D307.<\/p>\n

– Ansari HR, Flower DR, Raghava GPS. AntigenDB: an immunoinformatics database of pathogen antigens<\/strong><\/a>. Nucleic Acids Research 2010;38(Database issue):D847-D853.<\/p>\n

– Feldhahn M, D\u00f6nnes P, Thiel P., Kohlbacher O. FRED\u2014a framework for T-cell epitope detection<\/strong><\/a>. Bioinformatics 2009 25(20):2758-2759.<\/p>\n

– Lefranc MP, Giudicelli V, Ginestoux C, Jabado-Michaloud J, Folch G, Bellahcene F et al. IMGT, the international ImMunoGeneTics information system<\/strong><\/a>. Nucleic Acids Res. 2009 Jan;37(Database issue):D1006-12.<\/p>\n

– Huang YX, Bao YL, Guo Sh, Wang Y, Zhou CG, Li YX. Pep-3D-Search: a method for B-cell epitope prediction based on mimotope analysis<\/strong><\/a>. BMC Bioinformatics 2008;9:538.<\/p>\n

– De Groot AS, Rivera DS, McMurry JA, Buus S, Martina W. Identification of immunogenic HLA-B7 \u201cAchilles’ heel\u201d epitopes within highly conserved regions of HIV<\/strong><\/a>. Vaccine. 2008 June 6;26(24):3059\u20133071.<\/p>\n

– Trost B, Bickis M, Kusalik A. Strength in numbers: achieving greater accuracy in MHC-I binding prediction by combining the results from multiple prediction tools<\/strong><\/a>. Immunome Research 2007;3:5.<\/p>\n

– Doytchinova IA, Flower DR. VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines<\/strong><\/a>. BMC Bioinformatics 2007;8:4.<\/p>\n

– Nielsen M, Lundegaard C, Lund O. Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method<\/strong><\/a>. BMC Bioinformatics 2007;8:238.<\/p>\n

– Korber B, LaBute M, Yusim K. Immunoinformatics Comes of Age<\/strong><\/a>. PLoS Comput Biol 2006;2(6):e71.<\/p>\n

– Liu W, Meng X, Xu Q, Flower DR, Li T. Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models<\/strong><\/a>. BMC Bioinformatics 2006;7:182.<\/p>\n

– Petrovsky N, Sch\u00f6nbach C, Brusic V. Bioinformatic strategies for better understanding of immune function<\/strong><\/a>. In Silico Biology 2003;3:0034.<\/p>\n

– Singh H, Raghava GPS. ProPred1: prediction of promiscuous MHC Class-I binding sites<\/strong><\/a>. Bioinformatics 2003;19(8):1009-1014.<\/p>\n","protected":false},"excerpt":{"rendered":"

En esta p\u00e1gina encontrar\u00e1 recursos e informaciones sobre las aplicaciones bioinform\u00e1ticas relacionadas con el sistema inmune. BASES DE DATOS Y HERRAMIENTAS: ALLERGOME: Base de datos sobre alergenos reportados que inducen respuesta IgE y otras fuentes de alergias, aunque no se haya identificado la mol\u00e9cula responsable. Requiere registro. BIMAS: Permite predecir p\u00e9ptidos de una prote\u00edna a […]<\/p>\n","protected":false},"author":125,"featured_media":0,"parent":0,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/blogs.sld.cu\/oserranob\/wp-json\/wp\/v2\/pages\/81"}],"collection":[{"href":"https:\/\/blogs.sld.cu\/oserranob\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/blogs.sld.cu\/oserranob\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.sld.cu\/oserranob\/wp-json\/wp\/v2\/users\/125"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.sld.cu\/oserranob\/wp-json\/wp\/v2\/comments?post=81"}],"version-history":[{"count":26,"href":"https:\/\/blogs.sld.cu\/oserranob\/wp-json\/wp\/v2\/pages\/81\/revisions"}],"predecessor-version":[{"id":5558,"href":"https:\/\/blogs.sld.cu\/oserranob\/wp-json\/wp\/v2\/pages\/81\/revisions\/5558"}],"wp:attachment":[{"href":"https:\/\/blogs.sld.cu\/oserranob\/wp-json\/wp\/v2\/media?parent=81"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}