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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction and functional analysis of the sweet orange protein-protein interaction network
|
|---|---|
| Published in |
BMC Plant Biology, August 2014
|
| DOI | 10.1186/s12870-014-0213-7 |
| Pubmed ID | |
| Authors |
Yu-Duan Ding, Ji-Wei Chang, Jing Guo, DiJun Chen, Sen Li, Qiang Xu, Xiu-Xin Deng, Yun-Jiang Cheng, Ling-Ling Chen |
| Abstract |
BackgroundSweet orange (Citrus sinensis) is one of the most important fruits world-wide. Because it is a woody plant with a long growth cycle, genetic studies of sweet orange are lagging behind those of other species.ResultsIn this analysis, we employed ortholog identification and domain combination methods to predict the protein-protein interaction (PPI) network for sweet orange. The K-nearest neighbors (KNN) classification method was used to verify and filter the network. The final predicted PPI network, CitrusNet, contained 8,195 proteins with 124,491 interactions. The quality of CitrusNet was evaluated using gene ontology (GO) and Mapman annotations, which confirmed the reliability of the network. In addition, we calculated the expression difference of interacting genes (EDI) in CitrusNet using RNA-seq data from four sweet orange tissues, and also analyzed the EDI distribution and variation in different sub-networks.ConclusionsGene expression in CitrusNet has significant modular features. Target of rapamycin (TOR) protein served as the central node of the hormone-signaling sub-network. All evidence supported the idea that TOR can integrate various hormone signals and affect plant growth. CitrusNet provides valuable resources for the study of biological functions in sweet orange. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 20% |
| France | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
| Members of the public | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Turkey | 1 | 2% |
| Brazil | 1 | 2% |
| India | 1 | 2% |
| Argentina | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 39 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 27% |
| Researcher | 12 | 27% |
| Student > Master | 5 | 11% |
| Student > Bachelor | 2 | 5% |
| Other | 2 | 5% |
| Other | 7 | 16% |
| Unknown | 4 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 57% |
| Biochemistry, Genetics and Molecular Biology | 7 | 16% |
| Medicine and Dentistry | 3 | 7% |
| Computer Science | 2 | 5% |
| Earth and Planetary Sciences | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 5 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 August 2014.
All research outputs
#14,931,785
of 23,881,329 outputs
Outputs from BMC Plant Biology
#1,191
of 3,322 outputs
Outputs of similar age
#121,869
of 232,669 outputs
Outputs of similar age from BMC Plant Biology
#15
of 48 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,322 research outputs from this source. They receive a mean Attention Score of 3.0. This one has gotten more attention than average, scoring higher than 61% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 232,669 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.