Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Theodore Roman"'
Autor:
Eunjung Han, Peter Carbonetto, Ross E. Curtis, Yong Wang, Julie M. Granka, Jake Byrnes, Keith Noto, Amir R. Kermany, Natalie M. Myres, Mathew J. Barber, Kristin A. Rand, Shiya Song, Theodore Roman, Erin Battat, Eyal Elyashiv, Harendra Guturu, Eurie L. Hong, Kenneth G. Chahine, Catherine A. Ball
Publikováno v:
Nature Communications, Vol 8, Iss 1, Pp 1-12 (2017)
Genetic data has led to great advances in our understanding of human evolution and dispersal, but information on more recent events is limited. Here, the authors analyse genotypes from 770,000 US individuals to map the fine-scale population structure
Externí odkaz:
https://doaj.org/article/e99a0ac04ddd404b84d2e573c01d9e36
Publikováno v:
PLoS Computational Biology, Vol 13, Iss 10, p e1005815 (2017)
With increasing appreciation for the extent and importance of intratumor heterogeneity, much attention in cancer research has focused on profiling heterogeneity on a single patient level. Although true single-cell genomic technologies are rapidly imp
Externí odkaz:
https://doaj.org/article/a1208dee2d76487bbd134e0f4911f522
Autor:
Catherine A. Ball, Eunjung Han, Natalie M. Myres, Harendra Guturu, Theodore Roman, Yong Wang, Keith Noto, Eurie L. Hong, Shiya Song, Erin Royston Battat, Peter Carbonetto, Eyal Elyashiv, Jake K. Byrnes, Julie M. Granka, Kenneth G. Chahine, Mathew J. Barber, Amir R. Kermany, Kristin A. Rand, Ross E. Curtis
Publikováno v:
Nature Communications, Vol 8, Iss 1, Pp 1-12 (2017)
Nature Communications
Nature Communications
Despite strides in characterizing human history from genetic polymorphism data, progress in identifying genetic signatures of recent demography has been limited. Here we identify very recent fine-scale population structure in North America from a net
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8707b469032df46886fb347af16a9cd8
https://doi.org/10.1038/ncomms14238
https://doi.org/10.1038/ncomms14238
Publikováno v:
BMC Genomics
Despite the enormous medical impact of cancers and intensive study of their biology, detailed characterization of tumor growth and development remains elusive. This difficulty occurs in large part because of enormous heterogeneity in the molecular me
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fdb2d6918bf373dcd752c3900334281
http://europepmc.org/articles/PMC4895288
http://europepmc.org/articles/PMC4895288
Publikováno v:
BMC Bioinformatics
Background Tumorigenesis is an evolutionary process by which tumor cells acquire mutations through successive diversification and differentiation. There is much interest in reconstructing this process of evolution due to its relevance to identifying
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0efc1579e9eba999124789a393157adb
https://doi.org/10.1186/s12859-015-0694-x
https://doi.org/10.1186/s12859-015-0694-x
Publikováno v:
Cancer Research. 77:974-974
Tumor heterogeneity has been linked to many measures of poor patient outcome. Despite numerous recent methodological advances, though, reliable estimates of clonal and subclonal architecture remain elusive. We present advances in computational deconv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5b622b2c89bf1606d732b108a44dcf6
https://doi.org/10.1158/1538-7445.am2017-974
https://doi.org/10.1158/1538-7445.am2017-974
Publikováno v:
Cancer Research. 76:849-849
We develop new methods for improved computational deconvolution of clonal populations from heterogeneous bulk genomic data. Deconvolution methods have become an important tool in resolving intratumor heterogeneity from bulk tumor genomic data, but pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::297a1c349dab5208afb07ba4dd9a8bf7
https://doi.org/10.1158/1538-7445.am2016-849
https://doi.org/10.1158/1538-7445.am2016-849
Autor:
Theodore Roman, Russell Schwartz
Publikováno v:
Cancer Research. 75:1934-1934
Intratumor heterogeneity has long been a confounding factor in interpreting cancer genomic data, but has also been useful in reconstructing progression processes based on variation between clonal populations in single tumors. We previously developed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f2eb403cd37974bb2e0a1ad923795e7
https://doi.org/10.1158/1538-7445.am2015-1934
https://doi.org/10.1158/1538-7445.am2015-1934