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comparison sappDocker/tmhmm.xml @ 31:957156367442 draft

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author jjkoehorst
date Wed, 29 Jun 2016 01:36:58 -0400
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1 <tool id="DTmhmm" name="Transmembrane detection" version="1.0.0">
2 <description/>
3 <requirements>
4 <container type="docker">jjkoehorst/sappdocker:TMHMM</container>
5 </requirements>
6 <command interpreter="docker">java -jar /tmhmm/target/tmhmm-0.0.1-SNAPSHOT-jar-with-dependencies.jar
7 -input $input -output $output -format TURTLE
8 </command>
9 <inputs>
10 <param format="ttl" label="genome ttl with orf prediction" name="input" type="data"/>
11 </inputs>
12 <outputs>
13 <data format="ttl" label="TMHMM: ${input.name}" name="output"/>
14 </outputs>
15 <help>Be aware that this can only be used for academic users; other
16 users are
17 requested to contact CBS Software Package Manager at
18 software@cbs.dtu.dk.
19 We are investigating alternative prediction
20 applications, please contact
21 us if you are aware of such method.
22 </help>
23 <citations>
24 <citation type="bibtex">@article{Krogh2001,
25 abstract = {We describe and
26 validate a new membrane protein topology
27 prediction method, TMHMM,
28 based on a hidden Markov model. We present
29 a detailed analysis of
30 TMHMM's performance, and show that it
31 correctly predicts 97-98 \% of
32 the transmembrane helices.
33 Additionally, TMHMM can discriminate
34 between soluble and membrane
35 proteins with both specificity and
36 sensitivity better than 99 \%,
37 although the accuracy drops when signal
38 peptides are present. This
39 high degree of accuracy allowed us to
40 predict reliably integral
41 membrane proteins in a large collection of
42 genomes. Based on these
43 predictions, we estimate that 20-30 \% of all
44 genes in most genomes
45 encode membrane proteins, which is in agreement
46 with previous
47 estimates. We further discovered that proteins with
48 N(in)-C(in)
49 topologies are strongly preferred in all examined
50 organisms, except
51 Caenorhabditis elegans, where the large number of
52 7TM receptors
53 increases the counts for N(out)-C(in) topologies. We
54 discuss the
55 possible relevance of this finding for our understanding
56 of membrane
57 protein assembly mechanisms. A TMHMM prediction service is
58 available
59 at http://www.cbs.dtu.dk/services/TMHMM/.},
60 author = {Krogh,
61 A and Larsson, B and von Heijne, G and Sonnhammer, E L},
62 doi =
63 {10.1006/jmbi.2000.4315},
64 issn = {0022-2836},
65 journal = {Journal of
66 molecular biology},
67 keywords = {Animals,Bacterial Proteins,Bacterial
68 Proteins:
69 chemistry,Computational Biology,Computational Biology:
70 methods,Databases as Topic,Fungal Proteins,Fungal Proteins:
71 chemistry,Genome,Internet,Markov Chains,Membrane Proteins,Membrane
72 Proteins: chemistry,Plant Proteins,Plant Proteins:
73 chemistry,Porins,Porins: chemistry,Protein Sorting Signals,Protein
74 Structure, Secondary,Reproducibility of Results,Research
75 Design,Sensitivity and Specificity,Software,Solubility},
76 month = jan,
77 number = {3},
78 pages = {567--80},
79 pmid = {11152613},
80 title = {{Predicting
81 transmembrane protein topology with a hidden Markov
82 model: application
83 to complete genomes.}},
84 url =
85 {http://www.sciencedirect.com/science/article/pii/S0022283600943158},
86 volume = {305},
87 year = {2001}
88 }
89
90 </citation>
91 </citations>
92 </tool>