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enDNA-Prot specifications


Unique identifier OMICS_11966
Name enDNA-Prot
Interface Web user interface
Restrictions to use None
Input data Protein sequences
Input format FASTA
Computer skills Basic
Stability Stable
Maintained No


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enDNA-Prot citations


Protein Sequence Comparison and DNA binding Protein Identification with Generalized PseAAC and Graphical Representation

PMCID: 5930480
PMID: 29380690
DOI: 10.2174/1386207321666180130100838

[…] his demonstrates that our SVM model performs equally well on independent dataset. For convenience of comparison, results of some existing methods including DNAbinder [], DNA-Prot [], iDNA-Prot [] and enDNA-Prot [] are also listed in Table . DNAbinder developed by Kumar et al. [] can extract evolutionary information in form of position specific scoring matrix (PSSM) from the corresponding protein s […]


DNABP: Identification of DNA Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues

PLoS One
PMCID: 5132331
PMID: 27907159
DOI: 10.1371/journal.pone.0167345

[…] nd selection, compared with the other three methods.In this research, we constructed DNABP model based on the Mainset dataset which is different from the benchmark dataset Xu et al. used to establish enDNA-Prot model []. Then the question is that whether a DNABP model constructed based on the benchmark dataset would achieve better performance than the enDNA-Prot model. Therefore, a new DNABP model […]


Identification of DNA binding proteins using multi features fusion and binary firefly optimization algorithm

BMC Bioinformatics
PMCID: 5002159
PMID: 27565741
DOI: 10.1186/s12859-016-1201-8

[…] to evaluate iDbP and compare with previous studies. As the services of DBPPred and DBDThreader were not availiable. The comparison on Zou’s benchmark dataset was performed among iDNA-Prot, DNAbinder, enDNA-Prot, nDNA-Prot, Zou’s method and our iDbP. As shown in Table , the iDbP yielded the best performance with the SN of 0.908, SP of 0.911, ACC of 0.910 and MCC of 0.803.Theoretically, protein stru […]

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enDNA-Prot institution(s)
School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China; Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong, China; Shanghai Key Laboratory of Intelligent Information Processing, Shanghai, China; Gordon Life Science Institute, Belmont, MA, USA; PKU-HKUST ShenZhen-Hong Kong Institution, Shenzhen, Guangdong, China; Peking University Shenzhen Graduate School, Shenzhen, Guangdong, China; School of Engineering & Applied Science, Aston University, Birmingham, UK; School of Information Science and Technology, Xiamen University, Xiamen, Fujian, China
enDNA-Prot funding source(s)
This work was supported by the National Natural Science Foundation of China (no. 61300112, 61370165), the Natural Science Foundation of Guangdong Province (no. S2012040007390, S2013010014475), the Scientific Research Innovation Foundation in Harbin Institute of Technology (HIT.NSRIF.2013103), the Shanghai Key Laboratory of Intelligent Information Processing, China (no. IIPL-2012-002), the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry, MOE Specialized Research Fund for the Doctoral Program of Higher Education 20122302120070, Open Projects Program of National Laboratory of Pattern Recognition, Shenzhen Foundational Research Funding JCYJ20120613152557576, Shenzhen International Co-Operation Research Funding GJHZ20120613110641217, Strategic Emerging Industry Development Special Funds of Shenzhen (ZDSY20120613125401420 and JCYJ20120613151940045), and the Key Basic Research Foundation of Shenzhen (JC201005260118A).

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