Title |
Stemformatics: Visualisation and sharing of stem cell gene expression
|
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Published in |
Stem Cell Research, December 2012
|
DOI | 10.1016/j.scr.2012.12.003 |
Pubmed ID | |
Authors |
Christine A. Wells, Rowland Mosbergen, Othmar Korn, Jarny Choi, Nick Seidenman, Nicholas A. Matigian, Alejandra M. Vitale, Jill Shepherd |
Abstract |
Genome-scale technologies are increasingly adopted by the stem cell research community, because of the potential to uncover the molecular events most informative about a stem cell state. These technologies also present enormous challenges around the sharing and visualisation of data derived from different laboratories or under different experimental conditions. Stemformatics is an easy to use, publicly accessible portal that hosts a large collection of exemplar stem cell data. It provides fast visualisation of gene expression across a range of mouse and human datasets, with transparent links back to the original studies. One difficulty in the analysis of stem cell signatures is the paucity of public pathways/gene lists relevant to stem cell or developmental biology. Stemformatics provides a simple mechanism to create, share and analyse gene sets, providing a repository of community-annotated stem cell gene lists that are informative about pathways, lineage commitment, and common technical artefacts. Stemformatics can be accessed at stemformatics.org. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Australia | 1 | 20% |
United States | 1 | 20% |
India | 1 | 20% |
Unknown | 2 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 3 | 60% |
Members of the public | 2 | 40% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 2% |
Unknown | 62 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 17 | 27% |
Student > Ph. D. Student | 11 | 17% |
Student > Master | 7 | 11% |
Professor > Associate Professor | 6 | 10% |
Student > Bachelor | 6 | 10% |
Other | 7 | 11% |
Unknown | 9 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 20 | 32% |
Biochemistry, Genetics and Molecular Biology | 10 | 16% |
Medicine and Dentistry | 6 | 10% |
Computer Science | 5 | 8% |
Engineering | 4 | 6% |
Other | 8 | 13% |
Unknown | 10 | 16% |