Title |
Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model
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Published in |
BMC Medical Genomics, September 2014
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DOI | 10.1186/1755-8794-7-57 |
Pubmed ID | |
Authors |
Lisette J A Kogelman, Susanna Cirera, Daria V Zhernakova, Merete Fredholm, Lude Franke, Haja N Kadarmideen |
Abstract |
Obesity is a complex metabolic condition in strong association with various diseases, like type 2 diabetes, resulting in major public health and economic implications. Obesity is the result of environmental and genetic factors and their interactions, including genome-wide genetic interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model for human obesity, offering the possibility to study in-depth organ-level transcriptomic regulations of obesity, unfeasible in humans. Our aim was to reveal adipose tissue co-expression networks, pathways and transcriptional regulations of obesity using RNA Sequencing based systems biology approaches in a porcine model. |
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Geographical breakdown
Country | Count | As % |
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Denmark | 1 | 33% |
United States | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Netherlands | 1 | <1% |
France | 1 | <1% |
Brazil | 1 | <1% |
Finland | 1 | <1% |
United Kingdom | 1 | <1% |
Sri Lanka | 1 | <1% |
Unknown | 161 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 40 | 24% |
Researcher | 23 | 14% |
Student > Bachelor | 23 | 14% |
Student > Master | 21 | 13% |
Student > Postgraduate | 8 | 5% |
Other | 23 | 14% |
Unknown | 29 | 17% |
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Biochemistry, Genetics and Molecular Biology | 33 | 20% |
Medicine and Dentistry | 15 | 9% |
Engineering | 6 | 4% |
Computer Science | 6 | 4% |
Other | 23 | 14% |
Unknown | 32 | 19% |