https://github.com/michbur/signalhsmm

Prediction of signal peptides
https://github.com/michbur/signalhsmm

Last synced: 9 days ago
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Prediction of signal peptides

• Host: GitHub
• URL: https://github.com/michbur/signalhsmm
• Owner: michbur
• Created: 2014-07-14T12:52:38.000Z (over 10 years ago)
• Default Branch: master
• Last Pushed: 2020-05-04T14:03:36.000Z (over 4 years ago)
• Last Synced: 2024-10-28T17:32:32.084Z (21 days ago)
• Language: R
• Size: 3.62 MB
• Stars: 2
• Watchers: 3
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG

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README

        
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Predict Presence of Signal Peptides

-------------------------

signalHsmm predicts presence of signal peptides in eukaryotic proteins using hidden semi-Markov models. The implemented algorithm can be accessed as a web-based service http://smorfland.uni.wroc.pl/shiny/signalHsmm/.

Local instance of signalHsmm

------------------------

signalHsmm can be also used locally as the R package. It can be installed from CRAN using:

```R

install.packages("signalHsmm")

```

You can install the latest development version of the package directly from github:

```R

source("https://install-github.me/michbur/signalHsmm")

```

After the installation, the GUI can be accessed locally:

```R

library(signalHsmm)

gui_signalHsmm()

```

All signalHsmm functionalities can be also invoked in the batch mode, for example:

```R

run_signalHsmm(benchmark_dat[1:10])

```

Citation

------------------------

#### Plain text

Burdukiewicz M, Sobczyk P, Chilimoniuk J, Gagat P, Mackiewicz P. Prediction of Signal Peptides in Proteins from Malaria Parasites. International Journal of Molecular Sciences. 2018; 19(12):3709. 
[Publication](https://www.mdpi.com/1422-0067/19/12/3709)

#### BibTeX

@article{Burdukiewicz_2018, 

title={Prediction of Signal Peptides in Proteins from Malaria Parasites}, 

volume={19}, 

ISSN={1422-0067}, 

url={http://dx.doi.org/10.3390/ijms19123709}, 

DOI={10.3390/ijms19123709}, 

number={12}, 

journal={International Journal of Molecular Sciences}, 

publisher={MDPI AG}, 

author={Burdukiewicz, Michał and Sobczyk, Piotr and Chilimoniuk, Jarosław and Gagat, Przemysław and Mackiewicz, Paweł}, 

year={2018}, 

month={Nov}, 

pages={3709}}