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

Kimberly D Siegmund

Showing results (1-10 of 105) with videos related to

Pageof 11
Sort By:
Human Genetics|April 27, 2011
Statistical approaches for the analysis of DNA methylation microarray dataKimberly D Siegmund
BMC Genomics|June 24, 2016
An evaluation of processing methods for HumanMethylation450 BeadChip dataJie Liu, Kimberly D Siegmund
American Journal of Epidemiology|April 30, 2002
Ascertainment bias in family-based case-control studiesKimberly D Siegmund, Bryan Langholz
Methods (San Diego, Calif.)|July 4, 2002
Analysis of complex methylation dataKimberly D Siegmund, Peter W Laird
Disease Markers|February 28, 2007
Statistical methods for evaluating DNA methylation as a marker for early detection or prognosisTodd A Alonzo, Kimberly D Siegmund
Statistical Applications in Genetics and Molecular Biology|July 4, 2008
Modeling DNA methylation in a population of cancer cellsKimberly D Siegmund, Paul Marjoram, Darryl Shibata
Plos One|July 9, 2011
High DNA methylation pattern intratumoral diversity implies weak selection in many human colorectal cancersKimberly D Siegmund, Paul Marjoram, Simon Tavaré, et al.
Cell Cycle (Georgetown, Tex.)|June 27, 2009
Many colorectal cancers are "flat" clonal expansionsKimberly D Siegmund, Paul Marjoram, Simon Tavaré, et al.
F1000Research|December 11, 2020
<i>iMutSig</i>: a web application to identify the most similar mutational signature using shinyZhi Yang, Priyatama Pandey, Paul Marjoram, et al.
Journal of Theoretical Biology|June 8, 2014
Ancestral inference in tumors: how much can we know?Junsong Zhao, Kimberly D Siegmund, Darryl Shibata, et al.
Pageof 11

Showing results (1-10 of 105) with videos related to

Sort By:
Pageof 11
Human Genetics|April 27, 2011
Statistical approaches for the analysis of DNA methylation microarray dataKimberly D Siegmund
BMC Genomics|June 24, 2016
An evaluation of processing methods for HumanMethylation450 BeadChip dataJie Liu, Kimberly D Siegmund
American Journal of Epidemiology|April 30, 2002
Ascertainment bias in family-based case-control studiesKimberly D Siegmund, Bryan Langholz
Methods (San Diego, Calif.)|July 4, 2002
Analysis of complex methylation dataKimberly D Siegmund, Peter W Laird
Disease Markers|February 28, 2007
Statistical methods for evaluating DNA methylation as a marker for early detection or prognosisTodd A Alonzo, Kimberly D Siegmund
Statistical Applications in Genetics and Molecular Biology|July 4, 2008
Modeling DNA methylation in a population of cancer cellsKimberly D Siegmund, Paul Marjoram, Darryl Shibata
Plos One|July 9, 2011
High DNA methylation pattern intratumoral diversity implies weak selection in many human colorectal cancersKimberly D Siegmund, Paul Marjoram, Simon Tavaré, et al.
Cell Cycle (Georgetown, Tex.)|June 27, 2009
Many colorectal cancers are "flat" clonal expansionsKimberly D Siegmund, Paul Marjoram, Simon Tavaré, et al.
F1000Research|December 11, 2020
<i>iMutSig</i>: a web application to identify the most similar mutational signature using shinyZhi Yang, Priyatama Pandey, Paul Marjoram, et al.
Journal of Theoretical Biology|June 8, 2014
Ancestral inference in tumors: how much can we know?Junsong Zhao, Kimberly D Siegmund, Darryl Shibata, et al.
Pageof 11