Mercurial > repos > jjkoehorst > sapp
diff tmhmm.xml @ 35:fa736576c7ed draft
planemo upload commit 16d0bc526ad02361a7c13231d4c50479c42d8d0f-dirty
author | jjkoehorst |
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date | Mon, 04 Jul 2016 10:37:59 -0400 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/tmhmm.xml Mon Jul 04 10:37:59 2016 -0400 @@ -0,0 +1,92 @@ +<tool id="DTmhmm" name="Transmembrane detection" version="1.0.0"> + <description/> + <requirements> + <container type="docker">jjkoehorst/sappdocker:TMHMM</container> + </requirements> + <command>java -jar /tmhmm/tmhmm-0.0.1-SNAPSHOT-jar-with-dependencies.jar + -input $input -output $output -format TURTLE + </command> + <inputs> + <param format="ttl" label="genome ttl with orf prediction" name="input" type="data"/> + </inputs> + <outputs> + <data format="ttl" label="TMHMM: ${input.name}" name="output"/> + </outputs> + <help>Be aware that this can only be used for academic users; other + users are + requested to contact CBS Software Package Manager at + software@cbs.dtu.dk. + We are investigating alternative prediction + applications, please contact + us if you are aware of such method. + </help> + <citations> + <citation type="bibtex">@article{Krogh2001, + abstract = {We describe and + validate a new membrane protein topology + prediction method, TMHMM, + based on a hidden Markov model. We present + a detailed analysis of + TMHMM's performance, and show that it + correctly predicts 97-98 \% of + the transmembrane helices. + Additionally, TMHMM can discriminate + between soluble and membrane + proteins with both specificity and + sensitivity better than 99 \%, + although the accuracy drops when signal + peptides are present. This + high degree of accuracy allowed us to + predict reliably integral + membrane proteins in a large collection of + genomes. Based on these + predictions, we estimate that 20-30 \% of all + genes in most genomes + encode membrane proteins, which is in agreement + with previous + estimates. We further discovered that proteins with + N(in)-C(in) + topologies are strongly preferred in all examined + organisms, except + Caenorhabditis elegans, where the large number of + 7TM receptors + increases the counts for N(out)-C(in) topologies. We + discuss the + possible relevance of this finding for our understanding + of membrane + protein assembly mechanisms. A TMHMM prediction service is + available + at http://www.cbs.dtu.dk/services/TMHMM/.}, + author = {Krogh, + A and Larsson, B and von Heijne, G and Sonnhammer, E L}, + doi = + {10.1006/jmbi.2000.4315}, + issn = {0022-2836}, + journal = {Journal of + molecular biology}, + keywords = {Animals,Bacterial Proteins,Bacterial + Proteins: + chemistry,Computational Biology,Computational Biology: + methods,Databases as Topic,Fungal Proteins,Fungal Proteins: + chemistry,Genome,Internet,Markov Chains,Membrane Proteins,Membrane + Proteins: chemistry,Plant Proteins,Plant Proteins: + chemistry,Porins,Porins: chemistry,Protein Sorting Signals,Protein + Structure, Secondary,Reproducibility of Results,Research + Design,Sensitivity and Specificity,Software,Solubility}, + month = jan, + number = {3}, + pages = {567--80}, + pmid = {11152613}, + title = {{Predicting + transmembrane protein topology with a hidden Markov + model: application + to complete genomes.}}, + url = + {http://www.sciencedirect.com/science/article/pii/S0022283600943158}, + volume = {305}, + year = {2001} + } + + </citation> + </citations> +</tool>