| Title |
Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface
|
|---|---|
| Published in |
BMC Bioinformatics, May 2011
|
| DOI | 10.1186/1471-2105-12-196 |
| Pubmed ID | |
| Authors |
Jacek Sroka, Łukasz Bieniasz-Krzywiec, Szymon Gwóźdź, Dariusz Leniowski, Jakub Łącki, Mateusz Markowski, Claudio Avignone-Rossa, Michael E Bushell, Johnjoe McFadden, Andrzej M Kierzek |
| Abstract |
Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Iran, Islamic Republic of | 2 | 3% |
| United States | 1 | 1% |
| Singapore | 1 | 1% |
| Portugal | 1 | 1% |
| Latvia | 1 | 1% |
| Luxembourg | 1 | 1% |
| United Kingdom | 1 | 1% |
| France | 1 | 1% |
| Germany | 1 | 1% |
| Other | 2 | 3% |
| Unknown | 67 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 19% |
| Student > Ph. D. Student | 13 | 16% |
| Student > Master | 13 | 16% |
| Professor | 8 | 10% |
| Professor > Associate Professor | 7 | 9% |
| Other | 15 | 19% |
| Unknown | 8 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 26 | 33% |
| Computer Science | 14 | 18% |
| Biochemistry, Genetics and Molecular Biology | 7 | 9% |
| Social Sciences | 5 | 6% |
| Engineering | 4 | 5% |
| Other | 12 | 15% |
| Unknown | 11 | 14% |