Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Joe Wiemels"'
Autor:
Michael Prados, Michelle Moghadassi, Jennette Sison, Rei Miike, Victoria Carlton, Hywel Jones, Joe Patoka, Karl Kelsey, Joe Wiemels, John Wiencke, Alex McMillan, Margaret Wrensch
Supplementary Data Table 2 from Nonsynonymous Coding Single-Nucleotide Polymorphisms Spanning the Genome in Relation to Glioblastoma Survival and Age at Diagnosis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c7d3ca4d2f20593e616f9da35e2ea52
https://doi.org/10.1158/1078-0432.22441716.v1
https://doi.org/10.1158/1078-0432.22441716.v1
Autor:
Michael Prados, Michelle Moghadassi, Jennette Sison, Rei Miike, Victoria Carlton, Hywel Jones, Joe Patoka, Karl Kelsey, Joe Wiemels, John Wiencke, Alex McMillan, Margaret Wrensch
Supplementary Data Table 3 from Nonsynonymous Coding Single-Nucleotide Polymorphisms Spanning the Genome in Relation to Glioblastoma Survival and Age at Diagnosis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d8ef74234235980f8688959cfd99a11
https://doi.org/10.1158/1078-0432.22441713.v1
https://doi.org/10.1158/1078-0432.22441713.v1
Autor:
Michael Prados, Michelle Moghadassi, Jennette Sison, Rei Miike, Victoria Carlton, Hywel Jones, Joe Patoka, Karl Kelsey, Joe Wiemels, John Wiencke, Alex McMillan, Margaret Wrensch
Purpose: Our aim was to discover possible inherited factors associated with glioblastoma age at diagnosis and survival. Although new genotyping technologies allow greatly expanded exploration of such factors, they pose many challenges.Experimental De
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49a225d46a99de55adc477b7622a772c
https://doi.org/10.1158/1078-0432.c.6518670.v1
https://doi.org/10.1158/1078-0432.c.6518670.v1
Autor:
Yuanyuan Xiao, Mark R. Segal, E. Andres Houseman, Joe Wiemels, John Wiencke, Shichun Zheng, Margaret Wrensch, Brock Christensen, Carmen Marsit, Karl Kelsey, Heather Nelson, Margaret Karagas, Ru-Fang Yeh
Publikováno v:
BMEI (1)
We present a statistical framework, MAMS-M, for determining the methylation status of hundreds of cancer related CpG sites. MAMS-M extends and adapts our previous SNP genotyping algorithm, MAMS, to methylation bead array data, exploiting the similari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e7c9c943e2c1b467dcc4ae09a3c8e74
https://doi.org/10.1109/bmei.2008.150
https://doi.org/10.1109/bmei.2008.150
