| Id |
Subject |
Object |
Predicate |
Lexical cue |
| T23 |
0-130 |
Sentence |
denotes |
In this regard, we report our recent effort to computationally identify immunogenic and/or cross-reactive peptides from 2019-nCoV. |
| T24 |
131-461 |
Sentence |
denotes |
We provide a detailed screen of candidate peptides based on comparison with immunogenic peptides deposited in the Immune Epitope Database and Analysis Resource (IEDB) database including those derived from Severe acute respiratory syndrome-related coronavirus (SARS CoV) along with de novo prediction from 2019-nCoV 9-mer peptides. |
| T25 |
462-884 |
Sentence |
denotes |
Here, we found i) 28 SARS-derived peptides having exact matches in 2019-nCoV proteome previously characterized to be immunogenic by in vitro T cell assays, ii) 22 nCoV peptides having a high sequence similarity with immunogenic peptides but with a greater predicted immunogenicity score, and iii) 44 + 19 nCoV peptides predicted to be immunogenic by the iPred algorithm and 1G4 TCR positional weight matrices respectively. |
