Description

A Deep Learning Model for Transmembrane Topology Prediction and Classification

Input

Name (Type)
Description
Pattern

meta (map)

Groovy Map containing sample information
e.g. [ id:‘test’, single_end

]

fasta (file)

Database of sequences in FASTA format

*.{fasta,fa,fasta.gz,fa.gz}

Output

Name (Type)
Description
Pattern

meta (map)

Groovy Map containing sample information
e.g. [ id:‘test’, single_end

]

gff3 (file)

Predicted topologies (inside, outside, TMhelix) in general Feature Format Version 3

biolib_results/TMRs.gff3

line3 (file)

Predicted topologies and information of protein sequences in three lines (name, sequence, topology)

biolib_results/predicted_topologies.3line

md (file)

Markdown results file

biolib_results/deeptmhmm_results.md

csv (file)

CSV file with per-residue predictions for the likelihood of each amino acid being in structural regions such as Beta-sheet, Periplasm, Membrane, Inside, Outside or Signal (only when querying against genomic fasta)

biolib_results/*_probs.csv

png (file)

Most likely topology probability line plots (only when querying against genomic fasta)

biolib_results/plot.png

versions (file)

File containing software versions

versions.yml

Tools

deeptmhmm
MIT

Deep Learning model for Transmembrane Helices protein domain prediction through the BioLib Python Client