GSIMULATOR statistics

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Citations per year

Number of citations per year for the bioinformatics software tool GSIMULATOR
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Tool usage distribution map

This map represents all the scientific publications referring to GSIMULATOR per scientific context
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GSIMULATOR specifications

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Unique identifier OMICS_33721
Name GSIMULATOR
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Stability No
Maintained Yes

Versioning


No version available

Publication for GSIMULATOR

GSIMULATOR citations

 (3)
library_books

Realistic artificial DNA sequences as negative controls for computational genomics

2014
Nucleic Acids Res
PMCID: 4081056
PMID: 24803667
DOI: 10.1093/nar/gku356

[…] n bases in the human genome are considered intergenic and non-functional ().Previous efforts in DNA sequence simulation have mainly focused on analysis of coding regions. Programs such as Seq-Gen (), Gsimulator () and many others start from a gene sequence and perform an artificial evolution process, adding mutations and modeling the conservation of the coding portion. All these programs are speci […]

library_books

Evolutionary Modeling and Prediction of Non Coding RNAs in Drosophila

2009
PLoS One
PMCID: 2721679
PMID: 19668382
DOI: 10.1371/journal.pone.0006478

[…] en simgenome would be more appropriate. The reality is somewhere in between; for D. melanogaster, where most (but not all) exons are now believed to be known with confidence, it is probably closer to gsimulator.Due to the large number of false positives in these screens, we are interested primarily in the sensitivity of the grammars when the false positive rate is lowest, i.e. the left-hand side o […]

library_books

Tools for simulating evolution of aligned genomic regions with integrated parameter estimation

2008
Genome Biol
PMCID: 2760874
PMID: 18840304
DOI: 10.1186/gb-2008-9-10-r147

[…] ng the Γ + I model for rate heterogeneity [], also providing some example parameters for this model (γ = 1, ι = 0.1), which we used for these simulations.Figure compares DAWG with the most realistic GSIMULATOR and richest SIMGENOME models. The figure shows that the context-dependence modeled by GSIMULATOR and the genomic features modeled by SIMGENOME result in much tighter false-positive estimate […]


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GSIMULATOR institution(s)
Computer Science Division, University of California, Berkeley, CA, USA; Biophysics Graduate Group, University of California, Berkeley, CA, USA; Department of Bioengineering, University of California, Berkeley, CA, USA
GSIMULATOR funding source(s)
Supported by NIH/NHGRI grant GM076705 and by an NSF Graduate Research Fellowship.

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