Title |
Inference of the Xenopus tropicalis embryonic regulatory network and spatial gene expression patterns
|
---|---|
Published in |
BMC Systems Biology, January 2014
|
DOI | 10.1186/1752-0509-8-3 |
Pubmed ID | |
Authors |
Zhenzhen Zheng, Scott Christley, William T Chiu, Ira L Blitz, Xiaohui Xie, Ken WY Cho, Qing Nie |
Abstract |
During embryogenesis, signaling molecules produced by one cell population direct gene regulatory changes in neighboring cells and influence their developmental fates and spatial organization. One of the earliest events in the development of the vertebrate embryo is the establishment of three germ layers, consisting of the ectoderm, mesoderm and endoderm. Attempts to measure gene expression in vivo in different germ layers and cell types are typically complicated by the heterogeneity of cell types within biological samples (i.e., embryos), as the responses of individual cell types are intermingled into an aggregate observation of heterogeneous cell types. Here, we propose a novel method to elucidate gene regulatory circuits from these aggregate measurements in embryos of the frog Xenopus tropicalis using gene network inference algorithms and then test the ability of the inferred networks to predict spatial gene expression patterns. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 6% |
Netherlands | 1 | 3% |
United Kingdom | 1 | 3% |
Unknown | 27 | 87% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 10 | 32% |
Researcher | 5 | 16% |
Student > Bachelor | 3 | 10% |
Professor > Associate Professor | 3 | 10% |
Student > Master | 3 | 10% |
Other | 3 | 10% |
Unknown | 4 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 13 | 42% |
Physics and Astronomy | 3 | 10% |
Computer Science | 3 | 10% |
Biochemistry, Genetics and Molecular Biology | 2 | 6% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
Other | 5 | 16% |
Unknown | 4 | 13% |