 Integrated host/microbe metagenomics enables accurate lower respiratory tract infection diagnosis in critically ill children JCI, 2023
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 Autoantigen profiling reveals a shared post-COVID signature in fully recovered and long COVID patients JCI Insight, 2023
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 Prolonged silent carriage, genomic virulence potential and transmission between staff and patients characterize a neonatal intensive care unit (NICU) outbreak of methicillin-resistant Staphylococcus aureus (MRSA) Cambridge University Press, 2023
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 Field assessment of BinaxNOW antigen tests as COVID-19 treatment entry point at a community testing site in San Francisco during evolving omicron surges PLOS One, 2023
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 Antibodies to repeat-containing antigens in Plasmodium falciparum are exposure-dependent and short-lived in children in natural malaria infections eLife, 2023
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 Successful Treatment of Balamuthia mandrillaris Granulomatous Amebic Encephalitis with Nitroxoline Emerging Infectious Diseases, 2023
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 Dual ankyrinG and subpial autoantibodies in a man with well-controlled HIV infection with steroid-responsive meningoencephalitis: A case report Frontiers, 2023
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|  DNA microarrays may be used to identify microbial species present in environmental and clinical samples. However, automated tools for reliable species identification based on observed microarray hybridization patterns are lacking. We present an algorithm, E-Predict, for microarray-based species identification. E-Predict compares observed hybridization patterns with theoretical energy profiles representing different species. We demonstrate the application of the algorithm to viral detection in a set of clinical samples and discuss its relevance to other metagenomic applications. E-Predict Software Download Page |
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