id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-004395-erqmbi2b	Bugembe, Daniel Lule	Computational MHC-I epitope predictor identifies 95% of experimentally mapped HIV-1 clade A and D epitopes in a Ugandan cohort	2020-02-22		.txt	text/plain	4391	216	45	METHODS: We tested the performance of the NetMHCpan4.0 computational neural network in re-identifying 93 T-cell epitopes that had been previously independently mapped using the whole proteome IFN-γ ELISPOT assays in 6 HLA class I typed Ugandan individuals infected with HIV-1 subtypes A1 and D. Using experimental epitope mapping data generated from 757 peptides tested on cells of 6 early HIV-1 infected individuals at paired time points, we show that NetMHCpan4.0 can be useful for markedly reducing pooled peptide experiments as demonstrated by the 95% experimental and computational concordance. Experimental data of peptides previously mapped for HIV-1 epitope recognition of 6 individuals for a separate study (Table 1) at 2 time points each was used for comparison with the computationally predicted binders. In this analysis we showed that the computational method NetMHCpan4.0 predicted 95% of previously experimentally mapped HIV-1 epitopes in 6 HIV-1 infected individuals expressing a total of 22 different HLA class I alleles.	./cache/cord-004395-erqmbi2b.txt	./txt/cord-004395-erqmbi2b.txt