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2017 ; 18
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gab.com Text
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English Wikipedia
PSFM-DBT: Identifying DNA-Binding Proteins by Combing Position Specific Frequency
Matrix and Distance-Bigram Transformation
#MMPMID28841194
Zhang J
; Liu B
Int J Mol Sci
2017[Aug]; 18
(9
): ä PMID28841194
show ga
DNA-binding proteins play crucial roles in various biological processes, such as
DNA replication and repair, transcriptional regulation and many other biological
activities associated with DNA. Experimental recognition techniques for
DNA-binding proteins identification are both time consuming and expensive.
Effective methods for identifying these proteins only based on protein sequences
are highly required. The key for sequence-based methods is to effectively
represent protein sequences. It has been reported by various previous studies
that evolutionary information is crucial for DNA-binding protein identification.
In this study, we employed four methods to extract the evolutionary information
from Position Specific Frequency Matrix (PSFM), including Residue Probing
Transformation (RPT), Evolutionary Difference Transformation (EDT),
Distance-Bigram Transformation (DBT), and Trigram Transformation (TT). The PSFMs
were converted into fixed length feature vectors by these four methods, and then
respectively combined with Support Vector Machines (SVMs); four predictors for
identifying these proteins were constructed, including PSFM-RPT, PSFM-EDT,
PSFM-DBT, and PSFM-TT. Experimental results on a widely used benchmark dataset
PDB1075 and an independent dataset PDB186 showed that these four methods achieved
state-of-the-art-performance, and PSFM-DBT outperformed other existing methods in
this field. For practical applications, a user-friendly webserver of PSFM-DBT was
established, which is available at http://bioinformatics.hitsz.edu.cn/PSFM-DBT/.