Selected article for: "discriminant analysis and linear discriminant analysis"

Author: Jacob W. Myerson; Priyal N. Patel; Nahal Habibi; Landis R. Walsh; Yi-Wei Lee; David C. Luther; Laura T. Ferguson; Michael H. Zaleski; Marco E. Zamora; Oscar A. Marcos-Contreras; Patrick M. Glassman; Ian Johnston; Elizabeth D. Hood; Tea Shuvaeva; Jason V. Gregory; Raisa Y. Kiseleva; Jia Nong; Kathryn M. Rubey; Colin F. Greineder; Samir Mitragotri; George S. Worthen; Vincent M. Rotello; Joerg Lahann; Vladimir R. Muzykantov; Jacob S. Brenner
Title: Supramolecular Organization Predicts Protein Nanoparticle Delivery to Neutrophils for Acute Lung Inflammation Diagnosis and Treatment
  • Document date: 2020_4_18
  • ID: ezrkg0dc_121
    Snippet: Error bars indicate standard error of the mean throughout. Significance was determined through paired t-test for comparison of two samples and ANOVA for group comparisons. Linear discriminant analysis and principal components analysis were completed in Gnu Octave scripts (adapted from https://www.bytefish.de/blog/pca_lda_with_gnu_octave/, and made available in full in the supplementary materials)......
    Document: Error bars indicate standard error of the mean throughout. Significance was determined through paired t-test for comparison of two samples and ANOVA for group comparisons. Linear discriminant analysis and principal components analysis were completed in Gnu Octave scripts (adapted from https://www.bytefish.de/blog/pca_lda_with_gnu_octave/, and made available in full in the supplementary materials).

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