Title |
Gene co-citation networks associated with worker sterility in honey bees
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Published in |
BMC Systems Biology, March 2014
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DOI | 10.1186/1752-0509-8-38 |
Pubmed ID | |
Authors |
Emma Kate Mullen, Mark Daley, Alanna Gabrielle Backx, Graham James Thompson |
Abstract |
The evolution of reproductive self-sacrifice is well understood from kin theory, yet our understanding of how actual genes influence the expression of reproductive altruism is only beginning to take shape. As a model in the molecular study of social behaviour, the honey bee Apis mellifera has yielded hundreds of genes associated in their expression with differences in reproductive status of females, including genes directly associated with sterility, yet there has not been an attempt to link these candidates into functional networks that explain how workers regulate sterility in the presence of queen pheromone. In this study we use available microarray data and a co-citation analysis to describe what gene interactions might regulate a worker's response to ovary suppressing queen pheromone. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 33% |
Japan | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 33% |
Scientists | 1 | 33% |
Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Iran, Islamic Republic of | 1 | 2% |
United States | 1 | 2% |
Germany | 1 | 2% |
Unknown | 38 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 11 | 27% |
Student > Master | 7 | 17% |
Student > Doctoral Student | 6 | 15% |
Researcher | 6 | 15% |
Student > Ph. D. Student | 3 | 7% |
Other | 2 | 5% |
Unknown | 6 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 16 | 39% |
Biochemistry, Genetics and Molecular Biology | 9 | 22% |
Medicine and Dentistry | 2 | 5% |
Social Sciences | 2 | 5% |
Computer Science | 2 | 5% |
Other | 3 | 7% |
Unknown | 7 | 17% |