--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/sappDocker/tmhmm.xml	Wed Jun 29 01:36:58 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 interpreter="docker">java -jar /tmhmm/target/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>
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