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Open Access Highly Accessed Research article

Metabolic classification of microbial genomes using functional probes

Chi-Ching Lee12, Wei-Cheng Lo3, Szu-Ming Lai1, Yi-Ping Phoebe Chen4, Chuan Yi Tang257 and Ping-Chiang Lyu167*

Author Affiliations

1 Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan

2 Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan

3 Department of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan

4 Department of Computer Science and Computer Engineering, La Trobe University, Melbourne, Australia

5 Department of Computer Science and Information Engineering, Providence University, Taichung, Taiwan

6 Department of Medical Science, National Tsing Hua University, Hsinchu, Taiwan

7 Graduate Institute of Molecular Systems Biomedicine, China Medical University, Taichung, Taiwan

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BMC Genomics 2012, 13:157  doi:10.1186/1471-2164-13-157

Published: 27 April 2012

Additional files

Additional file 1:

Large-scale proteomic tree. There are 843 microbes included in this large-scale proteomic tree. The blue dotted line indicates that Archaea (lower part) and Bacteria (upper part) are separated by the probe-set clustering. Organisms of different phyla are labeled with different colors. The color codes are shown at the upper right corner of this figure.

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Additional file 2:

The HGT+/- proteomic trees. This experiment involves the 415 microorganisms recorded in the HGT database that are known to possess horizontally transferred genes [44]. (a) Tree HGT+: the proteomic tree constructed using whole genomes. (b) HGT-: the proteomic tree constructed with horizontally transferred genes removed. For clarity, Tree HGT+ is divided into several large clusters, each of which is painted with a unique color. The color of a species in Tree HGT- is given according to the color of the species in Tree HGT+. Clearly, the color patterns of both trees are very similar. Indeed, the correlation coefficient between these two trees is very high (0.93), indicating a high similarity in topology between these trees.

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Open Data