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BiDaS: a web-based Monte Carlo BioData Simulator based on sequence/feature characteristics
- Source :
- Nucleic Acids Research
- Publication Year :
- 2013
- Publisher :
- Oxford University Press (OUP), 2013.
-
Abstract
- BiDaS is a web-application that can generate massive Monte Carlo simulated sequence or numerical feature data sets (e.g. dinucleotide content, composition, transition, distribution properties) based on small user-provided data sets. BiDaS server enables users to analyze their data and generate large amounts of: (i) Simulated DNA/RNA and aminoacid (AA) sequences following practically identical sequence and/or extracted feature distributions with the original data. (ii) Simulated numerical features, presenting identical distributions, while preserving the exact 2D or 3D between-feature correlations observed in the original data sets. The server can project the provided sequences to multidimensional feature spaces based on: (i) 38 DNA/RNA features describing conformational and physicochemical nucleotide sequence features from the B-DNA-VIDEO database, (ii) 122 DNA/RNA features based on conformational and thermodynamic dinucleotide properties from the DiProDB database and (iii) Pseudo-aminoacid composition of the initial sequences. To the best of our knowledge, this is the first available web-server that allows users to generate vast numbers of biological data sets with realistic characteristics, while keeping between-feature associations. These data sets can be used for a wide variety of current biological problems, such as the in-depth study of gene, transcript, peptide and protein groups/families; the creation of large data sets from just a few available members and the strengthening of machine learning classifiers. All simulations use advanced Monte Carlo sampling techniques. The BiDaS web-application is available at http://bioserver-3.bioacademy.gr/Bioserver/BiDaS/.
- Subjects :
- Genetics
Internet
Sequence
Biological data
Feature data
Sequence Analysis, RNA
Sequence analysis
Monte Carlo method
Proteins
Articles
DNA
Sequence Analysis, DNA
Biology
Sequence Analysis, Protein
Protein methods
Feature (computer vision)
Content (measure theory)
Nucleic Acid Conformation
RNA
Computer Simulation
Monte Carlo Method
Sequence Analysis
Algorithm
Software
Subjects
Details
- ISSN :
- 13624962 and 03051048
- Volume :
- 41
- Database :
- OpenAIRE
- Journal :
- Nucleic Acids Research
- Accession number :
- edsair.doi.dedup.....474679d8098f0946542206ccd84314e7
- Full Text :
- https://doi.org/10.1093/nar/gkt420