NetGPI is a glycosylphosphatidylinositol anchoring (GPI-anchoring or glypiation), prediction tool. It is a member of our protein sorting prediction tool suite.
NetGPI is a deep learning approach, which is based on recurrent neural networks and incorporates an attention mechanism to "point" out potential ω-sites.
NetGPI expects all entries to be residue sequences, designated for the
secretory pathway and relies on prior evidence for the N-terminal
If you do not have experimental evidence for the signal peptide, for some or all of the desired entries, then we would like to refer you
to SignalP to filter out non-secretory entries.
NetGPI only considers, at maximum, the last 100 C-terminal amino acids. In theory NetGPI can process sequences of any length but for
practical purposes the submission process rejects submissions if they include sequences with more than 10000 residues.
Two output options are provided: A long output format, which includes prediction probability distribution profile graphs over the last 100
amino acids as well as an appended sentinel *; and a short output format, which reports the prediction interpretation as well as the prediction probability distributions in tabular output files.
One annotation is attributed to each protein, the one that has the highest probability. If the highest probability is within the amino-acid sequence,
then the protein is considered GPI-anchored and the amino-acid position at the peak is the predicted ω-site. If the highest probability is at the sentinel,
here represented by *, then the protein is considered non GPI-anchored.
Currently the generation of the probability profile graphs is much slower than the actual prediction and we do not recommend the
long form output option for much more than 100 entries at a time.
The maximum number of proteins is 5000. The maximum number of residues in any given sequence is 10000. The long output format might timeout for more than 100 entries.
For example proteins Click here