Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

A Pappa Louisi

Showing results (41-50 of 43) with videos related to

Pageof 5
Sort By:
You have reached the last page of results.This site can display upto 43 results.
Journal of Chromatography. B, Biomedical Sciences and Applications|June 8, 2001
Study on the electrochemical detection of the macrolide antibiotics clarithromycin and roxithromycin in reversed-phase high-performance liquid chromatographyA Pappa-Louisi, A Papageorgiou, A Zitrou, et al.
Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences|January 30, 2022
Quantitative structure retention relationship (QSRR) modelling for Analytes' retention prediction in LC-HRMS by applying different Machine Learning algorithms and evaluating their performanceT Liapikos, C Zisi, D Kodra, et al.
Journal of Chromatography. A|February 23, 2015
Multivariate analysis of chromatographic retention data as a supplementary means for grouping structurally related compoundsS Fasoula, Ch Zisi, I Sampsonidis, et al.
Pageof 5

Showing results (41-50 of 43) with videos related to

Sort By:
Pageof 5
You have reached the last page of results.This site can display upto 43 results.
Journal of Chromatography. B, Biomedical Sciences and Applications|June 8, 2001
Study on the electrochemical detection of the macrolide antibiotics clarithromycin and roxithromycin in reversed-phase high-performance liquid chromatographyA Pappa-Louisi, A Papageorgiou, A Zitrou, et al.
Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences|January 30, 2022
Quantitative structure retention relationship (QSRR) modelling for Analytes' retention prediction in LC-HRMS by applying different Machine Learning algorithms and evaluating their performanceT Liapikos, C Zisi, D Kodra, et al.
Journal of Chromatography. A|February 23, 2015
Multivariate analysis of chromatographic retention data as a supplementary means for grouping structurally related compoundsS Fasoula, Ch Zisi, I Sampsonidis, et al.
Pageof 5