scholarly journals The Immune Epitope Database and Analysis Resource Program 2003–2018: reflections and outlook

2019 ◽  
Vol 72 (1-2) ◽  
pp. 57-76 ◽  
Author(s):  
Sheridan Martini ◽  
Morten Nielsen ◽  
Bjoern Peters ◽  
Alessandro Sette
Keyword(s):  
Immune Epitope ◽  
Resource Program ◽  
Immune Epitope Database

scholarly journals Epitope Specific Antibodies and T Cell Receptors in the Immune Epitope Database

2018 ◽  
Vol 9 ◽  
Author(s):  
Swapnil Mahajan ◽  
Randi Vita ◽  
Deborah Shackelford ◽  
Jerome Lane ◽  
Veronique Schulten ◽  
...  
Keyword(s):  
T Cell ◽  
T Cell Receptors ◽  
Specific Antibodies ◽  
Cell Receptors ◽  
Immune Epitope ◽  
Immune Epitope Database

scholarly journals Computer-aided prediction and design of IL-6 inducing peptides: IL-6 plays a crucial role in COVID-19

2020 ◽  
Author(s):  
Anjali Dhall ◽  
Sumeet Patiyal ◽  
Neelam Sharma ◽  
Salman Sadullah Usmani ◽  
Gajendra P S Raghava
Keyword(s):  
Scientific Community ◽  
Prediction Models ◽  
Vital Role ◽  
Machine Learning Techniques ◽  
Validation Dataset ◽  
Independent Validation ◽  
Immune Epitope ◽  
Learning Techniques ◽  
Wide Range ◽  
Immune Epitope Database

Abstract Interleukin 6 (IL-6) is a pro-inflammatory cytokine that stimulates acute phase responses, hematopoiesis and specific immune reactions. Recently, it was found that the IL-6 plays a vital role in the progression of COVID-19, which is responsible for the high mortality rate. In order to facilitate the scientific community to fight against COVID-19, we have developed a method for predicting IL-6 inducing peptides/epitopes. The models were trained and tested on experimentally validated 365 IL-6 inducing and 2991 non-inducing peptides extracted from the immune epitope database. Initially, 9149 features of each peptide were computed using Pfeature, which were reduced to 186 features using the SVC-L1 technique. These features were ranked based on their classification ability, and the top 10 features were used for developing prediction models. A wide range of machine learning techniques has been deployed to develop models. Random Forest-based model achieves a maximum AUROC of 0.84 and 0.83 on training and independent validation dataset, respectively. We have also identified IL-6 inducing peptides in different proteins of SARS-CoV-2, using our best models to design vaccine against COVID-19. A web server named as IL-6Pred and a standalone package has been developed for predicting, designing and screening of IL-6 inducing peptides (https://webs.iiitd.edu.in/raghava/il6pred/).

scholarly journals The Immune Epitope Database and Analysis Resource in Epitope Discovery and Synthetic Vaccine Design

2017 ◽  
Vol 8 ◽  
Author(s):  
Ward Fleri ◽  
Sinu Paul ◽  
Sandeep Kumar Dhanda ◽  
Swapnil Mahajan ◽  
Xiaojun Xu ◽  
...  
Keyword(s):  
Vaccine Design ◽  
Immune Epitope ◽  
Epitope Discovery ◽  
Immune Epitope Database

scholarly journals The design and implementation of the immune epitope database and analysis resource

2005 ◽  
Vol 57 (5) ◽  
pp. 326-336 ◽  
Author(s):  
Bjoern Peters ◽  
John Sidney ◽  
Phil Bourne ◽  
Huynh-Hoa Bui ◽  
Soeren Buus ◽  
...  
Keyword(s):  
Design And Implementation ◽  
Immune Epitope ◽  
Immune Epitope Database

scholarly journals Overlap of the cancer genome atlas and the immune epitope database

2016 ◽  
Vol 12 (4) ◽  
pp. 2982-2984
Author(s):  
Shaimaa Sait ◽  
Timothy Fawcett ◽  
George Blanck
Keyword(s):  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Immune Epitope ◽  
Cancer Genome Atlas ◽  
Immune Epitope Database ◽  
Genome Atlas

scholarly journals A Multiple Peptides Vaccine against nCOVID-19 Designed from the Nucleocapsid phosphoprotein (N) and Spike Glycoprotein (S) via the Immunoinformatics Approach

2020 ◽  
Author(s):  
Sahar Obi Abd Albagi ◽  
Mosab Yahya Al-Nour ◽  
Mustafa Elhag ◽  
Asaad Tageldein Idris Abdelihalim ◽  
Esraa Musa Haroun ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Binding Affinity ◽  
Effective Vaccine ◽  
Spike Glycoprotein ◽  
Mhc I ◽  
Immunological Responses ◽  
Mhc Ii ◽  
Immune Epitope ◽  
Hla Dqa1 ◽  
Immune Epitope Database

AbstractDue to the current COVID-19 pandemic, the rapid discovery of a safe and effective vaccine is an essential issue, consequently, this study aims to predict potential COVID-19 peptide-based vaccine utilizing the Nucleocapsid phosphoprotein (N) and Spike Glycoprotein (S) via the Immunoinformatics approach. To achieve this goal, several Immune Epitope Database (IEDB) tools, molecular docking, and safety prediction servers were used. According to the results, The Spike peptide peptides SQCVNLTTRTQLPPAYTNSFTRGVY is predicted to have the highest binding affinity to the B-Cells. The Spike peptide FTISVTTEI has the highest binding affinity to the MHC I HLA-B1503 allele. The Nucleocapsid peptides KTFPPTEPK and RWYFYYLGTGPEAGL have the highest binding affinity to the MHC I HLA-A0202 allele and the three MHC II alleles HLA-DPA1*01:03/DPB1*02:01, HLA-DQA1*01:02/DQB1- *06:02, HLA-DRB1, respectively. Furthermore, those peptides were predicted as non-toxic and non-allergen. Therefore, the combination of those peptides is predicted to stimulate better immunological responses with respectable safety.

Complex Network Study of the Immune Epitope Database for Parasitic Organisms

2018 ◽  
Vol 17 (30) ◽  
pp. 3249-3255 ◽  
Author(s):  
Severo Vazquez- Prieto ◽  
Esperanza Paniagua ◽  
Hugo Solana ◽  
Florencio M. Ubeira
Keyword(s):  
Complex Network ◽  
Immune Epitope ◽  
Immune Epitope Database

scholarly journals IEDB-3D: structural data within the immune epitope database

2010 ◽  
Vol 39 (Database) ◽  
pp. D1164-D1170 ◽  
Author(s):  
J. Ponomarenko ◽  
N. Papangelopoulos ◽  
D. M. Zajonc ◽  
B. Peters ◽  
A. Sette ◽  
...  
Keyword(s):  
Structural Data ◽  
Immune Epitope ◽  
Immune Epitope Database
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