| At line 2 changed one line |
| * Last updated: March 31, 2011 |
| * Last updated: March 18, 2012 |
| At line 6 changed one line |
| Welcome to our website! This is a webpage for our paper "Inferring protein-protein interactions based on sequences and interologs in Mycobacterium tuberculosis". Mycobacterium tuberculosis is a dangerous bacterium for human health. Extensive protein interactions will provide much information on biological processes to understand its living systems. In this paper, we constructed an integrated M. tuberculosis protein interaction network by machine learning and ortholog-based methods. Firstly, we developed a support vector machine (SVM) method to infer the protein interactions of tuberculosis H37Rv by gene sequence information. We tested our predictors in Escherichia coli and mapped the genetic codon features underlying protein interactions to M. tuberculosis. Moreover, the documented interactions of other 14 species are mapped to M. tuberculosis by the interolog method on protein sequence level. The ensemble protein interactions were validated by diverse functional linkages i.e., gene coexpression, evolutionary relationship and functional similarity, extracted from heterogeneous data sources. The accuracy and validation demonstrate the effectiveness and efficiency of our framework. Our methods can be straightforwardly extended to infer the protein interactions of other species. |
| Welcome to our website! This is a webpage for our paper "Inferring a protein interaction map of Mycobacterium tuberculosis based on sequences and interologs". Mycobacterium tuberculosis is a dangerous bacterium for human health. Extensive protein interactions will provide much information on biological processes to understand its living systems. In this paper, we constructed an integrated M. tuberculosis protein interaction network by machine learning and ortholog-based methods. Firstly, we developed a support vector machine (SVM) method to infer the protein interactions of tuberculosis H37Rv by gene sequence information. We tested our predictor in Escherichia coli and mapped the genetic codon features underlying protein interactions to M. tuberculosis. Moreover, the documented interactions of other 14 species are mapped to M. tuberculosis by the interolog method on protein sequence level. The ensemble protein interactions were validated by diverse functional linkages i.e., gene coexpression, evolutionary relationship and functional similarity, extracted from heterogeneous data sources. The accuracy and validation demonstrate the effectiveness and efficiency of our framework. Our methods can be straightforwardly extended to infer the protein interactions of other species. |
| At line 8 changed one line |
| Pay attention to the users: You can use and redistribute the data and software if you accept GNU General Public License (GPL) . |
| Pay attention to the users: You can use and redistribute the data and software if you accept GNU General Public License (GPL). |
| At line 10 changed one line |
| !!!References |
| !!!Reference |
| At line 12 changed one line |
| * Liu ZP, Wang JG, Qiu YQ, Leung RK, Zhang XS, Tsui SK and Chen L: Inferring protein-protein interactions based on sequences and interologs in Mycobacterium tuberculosis. 2011, In submission. |
| * Liu ZP, Wang J, Qiu YQ, Leung RK, Zhang XS, Tsui SK and Chen L: Inferring a protein interaction map of Mycobacterium tuberculosis based on sequences and interologs. BMC Bioinformatics, 13(Suppl 7):S6, 2012. |
| At line 16 changed one line |
| * [http://www.aporc.org/doc-files/MTBPPI/mtbppi.rar] |
| * [mtbppi.rar|MTBPPI/mtbppi.rar] |
| At line 19 changed one line |
| There are [{org.goodjava.plugin.hitcounter.HitCounter}] visitors since March 31, 2011 |
| Category: [Supplementary] |
