About WoLF PSORT
WoLF PSORT predicts the subcellular localization sites of proteins
based on their amino acid sequences. The method, which is a major
extension to the venerable PSORTII program, makes predictions based on
both known sorting signal motifs and some correlative sequence
features such as amino acid content. Like PSORT and PSORTII, WoLF PSORT
displays some information about detected sorting signals which is useful
in helping users determine the reliability of the prediction in specific
cases.
Our experiments (paper in preparation) show that the overall
prediction accuracy of WoLF PSORT is over 80%. For common localization
sites (e.g. cytosol, nucleus, mitochondria, etc) WoLF PSORT makes
better than majority classifier predictions even for queries that do
not have strong sequence similarity to any sequence in the
dataset. Thus WoLF PSORT is a useful complement to tools such as
BLAST.
The current dataset used to train WoLF PSORT contains over 12,000
animal sequences and more than 2,000 plant and fungi sequences
respectively. It was gathered mainly from Uniprot but several hundred
Arabidopsis thaliana sequences from the Gene Ontology database
were also included.
Developers
WoLF PSORT was being developed by
- Paul HORTON and Keun-Joon PARK at CBRC
- Takeshi OBAYASHI
- Kenta NAKAI
What's in a name
"WoLF" does not necessarily stand for anything. A rather dramatic
mnemonic would be "Where Life Functions". Originally it was going to
be "Learned Weight Features" but I wanted the acronym to be a
pronouncable English word. Waldo Lives Forever.
Acknowledgements
- WoLF PSORT Relies heavily on features inherited from PSORT(Nakai & Kanehisa)
- WoLF PSORT also uses some sequence features from iPSORT (Bannai
et. al).
- Dr. Ohta provided valuable advice on the best way to extract localization
data from GO.
- The original server design was done by C.J.Collier. (But he is not to blame for subsequent hacking...)
Contact:
Functional Analysis in silico | NAKAI Lab
8F General Research Bldg., 4-6-1 Shirokanedai Minato-ku Tokyo 108-8639, Japan
E-mail: fais "AT" hgc.jp (relace "AT" to @)