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We use sequence and structure based similarity detection methods to identify fic domain homologs in doc toxins and the bacterial effector AvrB.
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Success rate, precision and error rates for 398 DUF families of known structure using the five remote similarity detection methods.
The ability of a similarity detection method to report homologous sequences (sensitivity) must be balanced against the spurious detection of nonhomologs or false hits (specificity).
We found shape based similarity search methods (ROCS and EON) performed significantly better than structure based methods.
Graph based similarity methods such as Maximum Common Substructure (MCSS) [12,18] and Maximum Overlapping Set (MOS) [15] similarity based methods put a high weight on the common substructure.
Pathway based similarity measuring method shows higher classification accuracy.
As previously developed pathway based gene expression analysis methods were successfully improve intact gene expression based analysis methods [ 20- 23], pathway based similarity measuring method outperformed conventional method.
Recently Remmert et al. [ 34] performed a bioinformatic proteome analysis using a transitive sequence profile similarity based homology detection method, but only detected four known (two VDAC isoforms, Tom40 and Sam50) and no undiscovered MBOMPs in yeast.
Since the time complexity, path based similarity indexes are difficult to be applied in community detection for high performance.
But these latter methods do not capture any sequence based similarity.
We implemented the CNN based detection method in MATLAB 2016b (The MathWorks, Natick, MA) with MatConvNet56 1.0-beta23.
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