repDNA statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.

Subscribe
info

Citations per year

Citations chart
info

Popular tool citations

chevron_left Unclassified tools chevron_right
Popular tools chart
info

Tool usage distribution map

Tool usage distribution map
info

Associated diseases

Associated diseases

repDNA specifications

Information


Unique identifier OMICS_24336
Name repDNA
Alternative name representations of DNAs
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages Python
Computer skills Advanced
Version 1.1.4
Stability Stable
Maintained Yes

Download


Versioning


Add your version

Documentation


Maintainers


  • person_outline Bin Liu <>
  • person_outline Kuo-Chen Chou <>

Publication for representations of DNAs

repDNA in pipeline

2018
PMCID: 5773712
PMID: 29348418
DOI: 10.1038/s41598-018-19491-y

[…] such as psfm-dbt, 2l-pirna, pse-analysis, protdec-ltr, protdec-ltr2.0, etc. some powerful protein analysis methods have been proposed for the formulation of biological sequences, such as pse-in-one, repdna, based on different functions to produce feature vector for biological sequences. hmmtop was developed for the prediction of localization of helical transmembrane. kuo-chen chou devised […]


To access a full list of citations, you will need to upgrade to our premium service.

repDNA in publications

 (9)
PMCID: 5773712
PMID: 29348418
DOI: 10.1038/s41598-018-19491-y

[…] such as psfm-dbt, 2l-pirna, pse-analysis, protdec-ltr, protdec-ltr2.0, etc. some powerful protein analysis methods have been proposed for the formulation of biological sequences, such as pse-in-one, repdna, based on different functions to produce feature vector for biological sequences. hmmtop was developed for the prediction of localization of helical transmembrane. kuo-chen chou devised […]

PMCID: 5704239
PMID: 29149087
DOI: 10.3390/genes8110326

[…] tools incorporated traditional machine learning techniques such as support vector machine (svm), neural networks and k-nearest neighbor (knn). in [], the authors developed a python package called “repdna” to produce the features representing physicochemical properties and the sequence-order effects of dnas and nucleotides. fifteen types of features built from dna sequences can be calculated […]

PMCID: 5549711
PMID: 28792503
DOI: 10.1371/journal.pone.0181426

[…] (mcd) [], and multi-scale local feature representation (mld) []. fortunately enough, recent advances in developing numerous web servers for extracting features from biological sequences, such as repdna [], reprna [] and pse-in-one [] for dna, rna and protein sequence respectively, make the procedure quickly and effectively., sample classification is another important issue for predicting […]

PMCID: 5620272
PMID: 28978132
DOI: 10.18632/oncotarget.19590

[…] transcripts and do not fit into known classes of small rnas []. many computational methods and tools have been proposed and widely used for predicting and analyzing ncrnas, such as 2l-pirna, reprna/repdna, pse-in-one [–]., increasing evidence suggests that mirnas and lncrnas play crucial roles in a variety of biological processes, such as the proliferation, development and differentiation [, ]. […]

PMCID: 5444793
PMID: 28542398
DOI: 10.1371/journal.pone.0178217

[…] of betti numbers obtained from binarized ct images at the various threshold levels. the method of the current study is similar to those used in bioinformatics, such as pse-in-one, pse-analysis, repdna, and idhs-el [–]. these studies and the current study focused on how to create the feature vector which can be easily and effectively combined with machine learning algorithm., the current […]


To access a full list of publications, you will need to upgrade to our premium service.

repDNA 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; Gordon Life Science Institute, Belmont, MA, USA; Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, Saudi Arabia
repDNA funding source(s)
Supported by the National Natural Science Foundation of China [grant no 61300112, 61370010 and 61272383] and the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry.

repDNA reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review repDNA