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SLiMFinder: de novo short linear motif prediction

This server is still in development. Please report any odd/unwanted behaviour.

SLiMFinder Input Options:

Uniprot IDs (see alias list, e.g. LIG_Dynein_DLC8_1):

Alternative fasta input:

Alternative Uniprot ID list upload:

Alternative fasta file upload:

(NOTE: Uploaded files take precedence over entries in text box. Uploaded fasta file will supercede uniprot ID list.)

Masking Options

Disorder masking | Conservation masking.

Output Options

Probability cutoff: | Restrict to top ranked motifs.

Restrict output to motif clouds with at least one motif with no ambiguous positions (cloudfix).

Advanced Options

Other options:

Run

After running, click on the main tab to see overall SLiM predictions. If any SLiMS have been predicted, the occ tab will have details of which proteins (and where) they occur. Please see the REST tab of the SLiMFinder documentation for a full list of results output tabs.

If no SLiMs are returned: [1] Try altering the masking settings. (Disorder masking is recommended. Conservation masking can sometimes help but it depend on the dataset.) [2] Try relaxing the probability cutoff. To see the best motifs, regardless of significance, set probcut=1.0. (You may also want to reduce the topranks=X setting.)


© 2016 RJ Edwards. Contact: richard.edwards@unsw.edu.au.