Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Ross E. Curtis"'
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
Autor:
Marie V. Coignet, Eurie L. Hong, Sarah South, Miao Zhang, Harendra Guturu, Pei Jingwen, Jialiang Gu, Brooke Rhead, Michael Gaddis, Cecily Vaughn, Luong Ruiz, Nathan Berkowitz, Cat Foo, Ashley Elrick, Christine Maldonado, Ahna R. Girshick, Heather H. Harris, Ke Bi, Marjan Champine, Evan McCartney-Melstad, Spencer C. Knight, Keith Noto, Barry Starr, Milos Pavlovic, David A. Turrisini, Robert Burton, Kristin A. Rand, Ross E. Curtis, Shea King, Andrey Smelter, Karen Delgado, Yambazi Banda, Asher K. Haug Baltzell, Alisa Sedghifar, Raghavendran Partha, Yong Wang, Abby Drokhlyansky, Genevieve H.L. Roberts, Chodon Sass, Jenna Petersen, Patty Miller, Danny S. Park, Catherine A. Ball, Shannon R. McCurdy
INTRODUCTION PARAGRAPHMultiple large COVID-19 genome-wide association studies (GWAS) have identified reproducible genetic associations indicating that some infection susceptibility and severity risk is heritable.1-5 Most of these studies ascertained
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a680e1c5a57d19fa29d6b35999852a32
https://doi.org/10.1101/2021.01.24.21250324
https://doi.org/10.1101/2021.01.24.21250324
Autor:
Ahna R. Girshick, Ross E. Curtis
Publikováno v:
KDD
The last ten years have seen an exponential growth of direct-to-consumer genomics. One popular feature of these tests is the report of a distant ancestral inference profile-a breakdown of the regions of the world where the test-taker's ancestors may
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1a05b42f5efbb862c8124567146068af
https://doi.org/10.1145/3097983.3098042
https://doi.org/10.1145/3097983.3098042
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
Autor:
Peter Kinnaird, Kriti Puniyani, Junming Yin, Eric P. Xing, Wei Wu, Seunghak Lee, Ross E. Curtis, Georg P. Schoenherr
Publikováno v:
PLoS ONE, Vol 9, Iss 6, p e97524 (2014)
PLoS ONE
PLoS ONE
With the continuous improvement in genotyping and molecular phenotyping technology and the decreasing typing cost, it is expected that in a few years, more and more clinical studies of complex diseases will recruit thousands of individuals for pan-om
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3dd020e007025d993bc3f03da8613506
http://europepmc.org/articles/PMC4048179?pdf=render
http://europepmc.org/articles/PMC4048179?pdf=render
Publikováno v:
BMC Genomics
Background Association analysis using genome-wide expression quantitative trait locus (eQTL) data investigates the effect that genetic variation has on cellular pathways and leads to the discovery of candidate regulators. Traditional analysis of eQTL
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cd72bb9c0ffa674962e15655f966538a
Publikováno v:
BMC Bioinformatics, Vol 13, Iss 1, p 204 (2012)
BMC Bioinformatics
BMC Bioinformatics
Background Many biological processes are context-dependent or temporally specific. As a result, relationships between molecular constituents evolve across time and environments. While cutting-edge machine learning techniques can recover these network
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7f3a00bac380c50d88686c04830600f
Publikováno v:
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.
Despite the success of genome-wide association studies in detecting novel disease variants, we are still far from a complete understanding of the mechanisms through which variants cause disease. Most of previous studies have considered only genome-ph
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::364fb4a7074ab9fe5490e6963b553f0e
https://pubmed.ncbi.nlm.nih.gov/22174288
https://pubmed.ncbi.nlm.nih.gov/22174288
Publikováno v:
BioVis
Association mapping studies promise to link DNA mutations to gene expression data, possibly leading to innovative treatments for diseases. One challenge in large-scale association mapping studies is exploring the results of the computational analysis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d15b0684c23fd805b0bc0f4a193a2d3
Publikováno v:
Bioinformatics
Motivation: Estimating gene regulatory networks over biological lineages is central to a deeper understanding of how cells evolve during development and differentiation. However, one challenge in estimating such evolving networks is that their host c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e3c3b22cc4b9e7154ab2639057fecab