Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Quin F Wills"'
Autor:
Josine L Min, George Nicholson, Ingileif Halgrimsdottir, Kristian Almstrup, Andreas Petri, Amy Barrett, Mary Travers, Nigel W Rayner, Reedik Mägi, Fredrik H Pettersson, John Broxholme, Matt J Neville, Quin F Wills, Jane Cheeseman, GIANT Consortium, MolPAGE Consortium, Maxine Allen, Chris C Holmes, Tim D Spector, Jan Fleckner, Mark I McCarthy, Fredrik Karpe, Cecilia M Lindgren, Krina T Zondervan
Publikováno v:
PLoS Genetics, Vol 8, Iss 2, p e1002505 (2012)
Metabolic Syndrome (MetS) is highly prevalent and has considerable public health impact, but its underlying genetic factors remain elusive. To identify gene networks involved in MetS, we conducted whole-genome expression and genotype profiling on abd
Externí odkaz:
https://doaj.org/article/48c00fdd38354c18b5237e49bea1cf97
Autor:
Mattias Rantalainen, Blanca M Herrera, George Nicholson, Rory Bowden, Quin F Wills, Josine L Min, Matt J Neville, Amy Barrett, Maxine Allen, Nigel W Rayner, Jan Fleckner, Mark I McCarthy, Krina T Zondervan, Fredrik Karpe, Chris C Holmes, Cecilia M Lindgren
Publikováno v:
PLoS ONE, Vol 6, Iss 11, p e27338 (2011)
To understand how miRNAs contribute to the molecular phenotype of adipose tissues and related traits, we performed global miRNA expression profiling in subcutaneous abdominal and gluteal adipose tissue of 70 human subjects and characterised which miR
Externí odkaz:
https://doaj.org/article/d2cb4510af2f40deb759996a4e17e510
Autor:
Yudi Pawitan, Liewei Wang, Quin F. Wills, Mattias Rantalainen, Trung Nghia Vu, Krishna R. Kalari, Nifang Niu
Publikováno v:
Bioinformatics
Motivation RNA sequencing of single cells enables characterization of transcriptional heterogeneity in seemingly homogeneous cell populations. Single-cell sequencing has been applied in a wide range of researches fields. However, few studies have foc
Autor:
Nifang Niu, Richard M. Weinshilboum, Quin F. Wills, Krishna R. Kalari, Junmei Cairns, Ravishankar K. Iyer, Alan J. Gaglio, Liewei Wang, Arjun P. Athreya
Publikováno v:
Oncotarget
// Arjun P. Athreya 1, * , Krishna R. Kalari 2, * , Junmei Cairns 3, * , Alan J. Gaglio 4 , Quin F. Wills 5, 7 , Nifang Niu 6 , Richard Weinshilboum 3 , Ravishankar K. Iyer 1 , Liewei Wang 3 1 Department of Electrical and Computer Engineering, Univer
Autor:
Quin F. Wills, Mattias Rantalainen, Liewei Wang, Yudi Pawitan, Nifang Niu, Krishna R. Kalari, Trung Nghia Vu
Publikováno v:
Bioinformatics. 32:2128-2135
Motivation: Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a propor
Autor:
Ziliang Ao, Tobias Boothe, James D. Johnson, Timothy J. Kieffer, Garth L. Warnock, Ali Asadi, Quin F. Wills
Publikováno v:
Islets
Worldwide efforts are underway to replace or repair lost or dysfunctional pancreatic β-cells to cure diabetes. However, it is unclear what the final product of these efforts should be, as β-cells are thought to be heterogeneous. To enable the analy
Autor:
Quin F. Wills, Alba Rodriguez-Meira, Adam J. Mead, Christopher Yau, Christopher A.G. Booth, Benjamin J. Povinelli, Nikolaos Barkas, Sten Eirik W. Jacobsen, Kieran R. Campbell
Publikováno v:
Experimental Hematology. 64:S95-S96
MotivationSingle-cell RNA sequencing (scRNA-seq) is increasingly used to study gene expression at the level of individual cells. However, preparing raw sequence data for further analysis is not a straightforward process. Biases, artifacts, and other
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f31a526335caed754e81dfcdaca750a2
https://doi.org/10.1101/069633
https://doi.org/10.1101/069633
Autor:
Helen Lockstone, Dominique Gauguier, Jennifer M. Taylor, Christina Fernandez, Cecilia M. Lindgren, Amy Barrett, Jiannis Ragoussis, Mark I. McCarthy, Blanca M. Herrera, Pamela J. Kaisaki, Quin F. Wills, Carme Camps
Publikováno v:
BMC Medical Genomics, Vol 2, Iss 1, p 54 (2009)
BMC Medical Genomics
BMC Medical Genomics, BioMed Central, 2009, 2 (1), pp.54. ⟨10.1186/1755-8794-2-54⟩
BMC Medical Genomics, 2009, 2 (1), pp.54. ⟨10.1186/1755-8794-2-54⟩
BMC Medical Genomics, BioMed Central, 2009, 2 (1), pp.54. 〈10.1186/1755-8794-2-54〉
BMC Medical Genomics
BMC Medical Genomics, BioMed Central, 2009, 2 (1), pp.54. ⟨10.1186/1755-8794-2-54⟩
BMC Medical Genomics, 2009, 2 (1), pp.54. ⟨10.1186/1755-8794-2-54⟩
BMC Medical Genomics, BioMed Central, 2009, 2 (1), pp.54. 〈10.1186/1755-8794-2-54〉
Background MicroRNAs (miRNAs) are non-coding RNA molecules involved in post-transcriptional control of gene expression of a wide number of genes, including those involved in glucose homeostasis. Type 2 diabetes (T2D) is characterized by hyperglycaemi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36f15428cf9761839a1b2cd3c4a488e0
https://ora.ox.ac.uk/objects/uuid:75108e34-dbd1-4547-bd83-016976ebb573
https://ora.ox.ac.uk/objects/uuid:75108e34-dbd1-4547-bd83-016976ebb573
Single-cell gene expression analysis reveals genetic associations masked in whole-tissue experiments
Autor:
Darren W. Sexton, Quin F. Wills, Tariq Enver, Kenneth J. Livak, Christopher Holmes, Andrew J. Goldson, Alex J. Tipping
Gene expression in multiple individual cells from a tissue or culture sample varies according to cell-cycle, genetic, epigenetic and stochastic differences between the cells. However, single-cell differences have been largely neglected in the analysi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::430973603b9e8933672d38f35eff6842
https://ora.ox.ac.uk/objects/uuid:2f6d962f-2f99-466a-9e9c-067199251717
https://ora.ox.ac.uk/objects/uuid:2f6d962f-2f99-466a-9e9c-067199251717