 A Novel Cause of Chronic Viral Meningoencephalitis: Cache Valley Virus Annals of Neurology, 2017
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 Zika virus cell tropism in the developing human brain and inhibition by azithromycin PNAS, 2017
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 Plasmid-free CRISPR/Cas9 genome editing in Plasmodium falciparum confirms mutations conferring resistance to the dihydroisoquinolone clinical candidate SJ733 PLoS One, 2017
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 Metagenomic DNA Sequencing for the Diagnosis of Intraocular Infections American Academy of Ophthamology, 2017
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 Differential disease susceptibility in experimentally reptarenavirus infected boa constrictors and ball pythons Journal of Virology, 2017
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 A Herpesviral induction of RAE-1 NKG2D ligand expression occurs through release of HDAC mediated repression eLIFE, 2016
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 Illuminating uveitis: metagenomic deep sequencing identifies common and rare pathogens Genome Medicine, 2016
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|  Here we introduce HMMSplicer, an accurate and efficient algorithm for discovering canonical and non-canonical splice junctions in short read datasets. HMMSplicer identifies more splice junctions than currently available algorithms when tested on publicly available A. thaliana, P. falciparum, and H. sapiens datasets without a reduction in specificity. HMMSplicer was found to perform especially well in compact genomes and on genes with low expression levels, alternative splice isoforms, or non-canonical splice junctions. Because HHMSplicer does not rely on pre-built gene models, the products of inexact splicing are also detected. In addition, HMMSplicer provides a score for every predicted junction allowing the user to set a threshold to tune false positive rates depending on the needs of the experiment. HMMSplicer is implemented in Python. Code and documentation are freely available at the link below. Download HMMSplicer! (Updated Nov 25th 2010 - Version: 0.9.5) |
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