| Title |
The Cell Collective: Toward an open and collaborative approach to systems biology
|
|---|---|
| Published in |
BMC Systems Biology, August 2012
|
| DOI | 10.1186/1752-0509-6-96 |
| Pubmed ID | |
| Authors |
Tomáš Helikar, Bryan Kowal, Sean McClenathan, Mitchell Bruckner, Thaine Rowley, Alex Madrahimov, Ben Wicks, Manish Shrestha, Kahani Limbu, Jim A Rogers |
| Abstract |
Despite decades of new discoveries in biomedical research, the overwhelming complexity of cells has been a significant barrier to a fundamental understanding of how cells work as a whole. As such, the holistic study of biochemical pathways requires computer modeling. Due to the complexity of cells, it is not feasible for one person or group to model the cell in its entirety. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 25% |
| United Kingdom | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 126 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 4% |
| Switzerland | 1 | <1% |
| Brazil | 1 | <1% |
| Latvia | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Singapore | 1 | <1% |
| Unknown | 116 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 31 | 25% |
| Researcher | 25 | 20% |
| Student > Bachelor | 18 | 14% |
| Student > Master | 9 | 7% |
| Professor | 8 | 6% |
| Other | 18 | 14% |
| Unknown | 17 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 39 | 31% |
| Biochemistry, Genetics and Molecular Biology | 23 | 18% |
| Computer Science | 10 | 8% |
| Physics and Astronomy | 5 | 4% |
| Chemistry | 4 | 3% |
| Other | 24 | 19% |
| Unknown | 21 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 02 October 2012.
All research outputs
#3,246,087
of 25,373,627 outputs
Outputs from BMC Systems Biology
#80
of 1,132 outputs
Outputs of similar age
#21,764
of 184,459 outputs
Outputs of similar age from BMC Systems Biology
#3
of 36 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 92% 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 184,459 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.