Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins
The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distribu...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | International Journal of Genomics |
| Online Access: | http://dx.doi.org/10.1155/2018/9784161 |
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| author | Hao-Bo Guo Yue Ma Gerald A. Tuskan Xiaohan Yang Hong Guo |
| author_facet | Hao-Bo Guo Yue Ma Gerald A. Tuskan Xiaohan Yang Hong Guo |
| author_sort | Hao-Bo Guo |
| collection | DOAJ |
| description | The existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here) from the protein distribution densities in the LD space defined by ln(L) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level. |
| format | Article |
| id | doaj-art-c5385a941d8b4aab80bd5d199c2df6a1 |
| institution | Kabale University |
| issn | 2314-436X 2314-4378 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Genomics |
| spelling | doaj-art-c5385a941d8b4aab80bd5d199c2df6a12025-02-03T06:13:48ZengWileyInternational Journal of Genomics2314-436X2314-43782018-01-01201810.1155/2018/97841619784161Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of ProteinsHao-Bo Guo0Yue Ma1Gerald A. Tuskan2Xiaohan Yang3Hong Guo4Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USADepartment of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USABiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 3783, USABiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 3783, USADepartment of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USAThe existence of complete genome sequences makes it important to develop different approaches for classification of large-scale data sets and to make extraction of biological insights easier. Here, we propose an approach for classification of complete proteomes/protein sets based on protein distributions on some basic attributes. We demonstrate the usefulness of this approach by determining protein distributions in terms of two attributes: protein lengths and protein intrinsic disorder contents (ID). The protein distributions based on L and ID are surveyed for representative proteome organisms and protein sets from the three domains of life. The two-dimensional maps (designated as fingerprints here) from the protein distribution densities in the LD space defined by ln(L) and ID are then constructed. The fingerprints for different organisms and protein sets are found to be distinct with each other, and they can therefore be used for comparative studies. As a test case, phylogenetic trees have been constructed based on the protein distribution densities in the fingerprints of proteomes of organisms without performing any protein sequence comparison and alignments. The phylogenetic trees generated are biologically meaningful, demonstrating that the protein distributions in the LD space may serve as unique phylogenetic signals of the organisms at the proteome level.http://dx.doi.org/10.1155/2018/9784161 |
| spellingShingle | Hao-Bo Guo Yue Ma Gerald A. Tuskan Xiaohan Yang Hong Guo Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins International Journal of Genomics |
| title | Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins |
| title_full | Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins |
| title_fullStr | Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins |
| title_full_unstemmed | Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins |
| title_short | Classification of Complete Proteomes of Different Organisms and Protein Sets Based on Their Protein Distributions in Terms of Some Key Attributes of Proteins |
| title_sort | classification of complete proteomes of different organisms and protein sets based on their protein distributions in terms of some key attributes of proteins |
| url | http://dx.doi.org/10.1155/2018/9784161 |
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