INMUNOINFORMATICA - CNB - Protein Design Group

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GENERATION OF MLA-BASED PREDICTICE MODELS D + DATABASE Annotated sequences + Sequence IS a T cell epitope D – – Sequence is NOT T cell epitope Codificacion de datos en vectores numericos de longitud fija + D t – D t (Hidrofilicidad, Accesibilidad, 1) (Hidrofilicidad, Accesibilidad, 0) MLA PREDICTIVE MODEL
MLA: WEKA • Support Vector Machine • Decision Trees • Artificial Neural Networks • K-nearest neighbour learner
Page 1 and 2: INMUNOINFORMATICA Pedro A Reche, Ph
Page 3 and 4: INMUNOINFORMATICA? • IMMUNOINFORM
Page 5 and 6: IMMUNE SYSTEM ORGANS Functions: •
Page 7 and 8: Innate versus Adaptive Immune Syste
Page 9 and 10: DIVERSITY OF TCR AND BCR REPETOIRES
Page 11 and 12: ANTIBODY - ANTIGEN INTERACTION Anti
Page 13 and 14: Structural recognition of peptide-M
Page 15 and 16: TCR-PMHC FIT AND SELF TOLERANCE OF
Page 17 and 18: INNATE AND ADAPTIVE IMMUNE SYSTEM A
Page 19 and 20: IMMUNE RESPONSE Lymph node Skin/Muc
Page 21 and 22: CD4 T cell Efector Function: B-Cell
Page 23 and 24: IMMUNOINFORMATICS: AREAS OF DEVELOP
Page 25 and 26: IMMUNOINFORMATICS DATABASES: IMGT h
Page 27 and 28: IMMUNOINFORMATICS: SYSTEM LEVEL MOD
Page 29 and 30: WHY BOTHER EPITOPE PREDICTION? •
Page 31 and 32: 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2
Page 33: GENERAL PROCEDURE TO DERIVE DATA DR
Page 37 and 38: Computer aided design of epitope ba
Page 39 and 40: KNOWN CTL EPITOPES IN HIV-1 INFECTE
Page 41 and 42: HIV-1 SEQUENCES
Page 43 and 44: Conserved HIV1 CTL Epitopes H < 1 H
Page 45 and 46: Responses of stimulated T cells fro
Page 47 and 48: Cytotoxic activity of HIV-1 peptide
Page 49 and 50: Innate responses to virus infection

INMUNOINFORMATICA - CNB - Protein Design Group

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