SLNSW-Deep learning using tumor HLA peptide mass spectr...-TN_cdi_proquest_miscellaneous_2157679721

Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification

Full title: Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification

Author/creator: Bulik-Sullivan, Brendan, Busby, Jennifer, Palmer, Christine D, Davis, Matthew J, Murphy, Tyler, Clark, Andrew, Busby, Michele, Duke, Fujiko, Yang, Aaron, Young, Lauren, Ojo, Noelle C, Caldwell, Kamilah, Abhyankar, Jesse, Boucher, Thomas, Hart, Meghan G, Makarov, Vladimir, Montpreville, Vincent Thomas De, Mercier, Olaf, Chan, Timothy A, Scagliotti, Giorgio, Bironzo, Paolo, Novello, Silvia, Karachaliou, Niki, Rosell, Rafael, Anderson, Ian, Gabrail, Nashat, Hrom, John, Limvarapuss, Chainarong, Choquette, Karin, Spira, Alexander, Rousseau, Raphael, Voong, Cynthia, Rizvi, Naiyer A, Fadel, Elie, Frattini, Mark, Jooss, Karin, Skoberne, Mojca, Francis, Joshua, Yelensky, Roman.

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Record Identifier: TN_cdi_proquest_miscellaneous_2157679721

Language: English

Formats: Articles

Publishers: United States: Nature Publishing Group

Permalink: https://collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2157679721

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    Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification

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    TN_cdi_proquest_miscellaneous_2157679721

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    https://collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2157679721

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    Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification

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    https://collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2157679721

    Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification

    Full title

    Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification

    Author / Creator

    Bulik-Sullivan, Brendan ; Busby, Jennifer ; Palmer, Christine D ; Davis, Matthew J ; Murphy, Tyler ; Clark, Andrew ; Busby, Michele ; Duke, Fujiko ; Yang, Aaron ; Young, Lauren ; Ojo, Noelle C ; Caldwell, Kamilah ; Abhyankar, Jesse ; Boucher, Thomas ; Hart, Meghan G ; Makarov, Vladimir ; Montpreville, Vincent Thomas De ; Mercier, Olaf ; Chan, Timothy A ; Scagliotti, Giorgio ; Bironzo, Paolo ; Novello, Silvia ; Karachaliou, Niki ; Rosell, Rafael ; Anderson, Ian ; Gabrail, Nashat ; Hrom, John ; Limvarapuss, Chainarong ; Choquette, Karin ; Spira, Alexander ; Rousseau, Raphael ; Voong, Cynthia ; Rizvi, Naiyer A ; Fadel, Elie ; Frattini, Mark ; Jooss, Karin ; Skoberne, Mojca ; Francis, Joshua ; Yelensky, Roman

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    United States: Nature Publishing Group

    Journal title

    Nature biotechnology, 2019, Vol.37 (1), p.55-63

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    TN_cdi_proquest_miscellaneous_2157679721

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    English

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    Alleles Anticancer properties Antigen presentation Antigens Antitumor activity Cancer Cancer immunotherapy Clinical trials Computer applications Datasets Deep learning DNA sequencing Gene expression Histocompatibility antigen HLA Histocompatibility antigens HLA histocompatibility antigens Identification methods Immunotherapy Invasiveness Leukocytes Lymphocytes Lymphocytes T Mass spectrometry Mass spectroscopy Mathematical models Neoantigens Neural networks Nucleotide sequencing Patients Peptides Predictions Synthetic peptides Tumor cells Tumors

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    TN_cdi_proquest_miscellaneous_2157679721

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    https://collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2157679721

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