 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q96JK9 from www.uniprot.org...
The NucPred score for your sequence is 0.78 (see score help below)
1 MGDFAAPAAAANGSSICINSSLNSSLGGAGIGVNNTPNSTPAAPSSNHPA 50
51 AGGCGGSGGPGGGSAAVPKHSTVVERLRQRIEGCRRHHVNCENRYQQAQV 100
101 EQLELERRDTVSLYQRTLEQRAKKSGAGTGKQQHPSKPQQDAEAASAEQR 150
151 NHTLIMLQETVKRKLEGARSPLNGDQQNGACDGNFSPTSKRIRKDISAGM 200
201 EAINNLPSNMPLPSASPLHQLDLKPSLPLQNSGTHTPGLLEDLSKNGRLP 250
251 EIKLPVNGCSDLEDSFTILQSKDLKQEPLDDPTCIDTSETSLSNQNKLFS 300
301 DINLNDQEWQELIDELANTVPEDDIQDLFNEDFEEKKEPEFSQPATETPL 350
351 SQESASVKSDPSHSPFAHVSMGSPQARPSSSGPPFSTVSTATSLPSVAST 400
401 PAAPNPASSPANCAVQSPQTPNQAHTPGQAPPRPGNGYLLNPAAVTVAGS 450
451 ASGPVAVPSSDMSPAEQLKQMAAQQQQRAKLMQQKQQQQQQQQQQQQQQQ 500
501 QQQQQQQQQQHSNQTSNWSPLGPPSSPYGAAFTAEKPNSPMMYPQAFNNQ 550
551 NPIVPPMANNLQKTTMNNYLPQNHMNMINQQPNNLGTNSLNKQHNILTYG 600
601 NTKPLTHFNADLSQRMTPPVANPNKNPLMPYIQQQQQQQQQQQQQQQQQQ 650
651 PPPPQLQAPRAHLSEDQKRLLLMKQKGVMNQPMAYAALPSHGQEQHPVGL 700
701 PRTTGPMQSSVPPGSGGMVSGASPAGPGFLGSQPQAAIMKQMLIDQRAQL 750
751 IEQQKQQFLREQRQQQQQQQQQILAEQQLQQSHLPRQHLQPQRNPYPVQQ 800
801 VNQFQGSPQDIAAVRSQAALQSMRTSRLMAQNAGMMGIGPSQNPGTMATA 850
851 AAQSEMGLAPYSTTPTSQPGMYNMSTGMTQMLQHPNQSGMSITHNQAQGP 900
901 RQPASGQGVGMVSGFGQSMLVNSAITQQHPQMKGPVGQALPRPQAPPRLQ 950
951 SLMGTVQQGAQSWQQRSLQGMPGRTSGELGPFNNGASYPLQAGQPRLTKQ 1000
1001 HFPQGLSQSVVDANTGTVRTLNPAAMGRQMMPSLPGQQGTSQARPMVMSG 1050
1051 LSQGVPGMPAFSQPPAQQQIPSGSFAPSSQSQAYERNAPQDVSYNYSGDG 1100
1101 AGGSFPGLPDGADLVDSIIKGGPGDEWMQELDELFGNP 1138
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
What does the NucPred score mean?
| You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper. |
| NucPred score threshold | Specificity | Sensitivity |
| see above | fraction of proteins predicted to be nuclear that actually are nuclear | fraction of true nuclear proteins that are predicted (coverage) |
| 0.10 | 0.45 | 0.88 |
| 0.20 | 0.52 | 0.83 |
| 0.30 | 0.57 | 0.77 |
| 0.40 | 0.63 | 0.69 |
| 0.50 | 0.70 | 0.62 |
| 0.60 | 0.71 | 0.53 |
| 0.70 | 0.81 | 0.44 |
| 0.80 | 0.84 | 0.32 |
| 0.90 | 0.88 | 0.21 |
| 1.00 | 1.00 | 0.02 |
| Sequences which score >= 0.8 with NucPred and which
are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.) |
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