| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q99MI1 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MYGSARSVGKVEPSSQSPGRSPRLPRSPRLGHRRTNSTGGSSGNSVGGGS 50
51 GKTLSMENIQSLNAAYATSGPMYLSDHENVGAETPKSTMTLGRSGGRLPY 100
101 GVRMTAMGSSPNIASSGVASDTIAFGEHHLPPVSMASTVPHSLRQARDNT 150
151 IMDLQTQLKEVLRENDLLRKDVEVKESKLSSSMNSIKTFWSPELKKERAL 200
201 RKDEASKITIWKEQYRVVQEENQHMQMTIQALQDELRIQRDLNQLFQQDS 250
251 SSRTGEPCVAELTEENFQRLHAEHERQAKELFLLRKTLEEMELRIETQKQ 300
301 TLNARDESIKKLLEMLQSKGLSAKATEEDHERTRRLAEAEMHVHHLESLL 350
351 EQKEKENNMLREEMHRRFENAPDSAKTKALQTVIEMKDSKISSMERGLRD 400
401 LEEEIQMLKSNGALSSEEREEEMKQMEVYRSHSKFMKNKVEQLKEELSSK 450
451 DAQGEELKKRAAGLQSEIGQVKQELSRKDTELLALQTKLETLTNQFSDSK 500
501 QHIEVLKESLTAKEQRAAILQTEVDALRLRLEEKETMLNKKTKQIQDMAE 550
551 EKGTQAGEIHDLKDMLDVKERKVNVLQKKIENLQEQLRDKEKQMSSLKER 600
601 VKSLQADTTNTDTALTTLEEALADKERTIERLKEQRDRDEREKQEEIDTY 650
651 KKDLKDLREKVSLLQGDLSEKEASLLDIKEHASSLASSGLKKDSRLKTLE 700
701 IALEQKKEECLKMESQLKKAHEATLEARASPEMSDRIQQLEREISRYKDE 750
751 SSKAQTEVDRLLEILKEVENEKNDKDKKIAELESLTSRQVKDQNKKVANL 800
801 KHKEQVEKKKSAQMLEEARRREDSLSDSSQQLQDSLRKKDDRIEELEEAL 850
851 RESVQITAEREMVLAQEESARTNAEKQVEELLMAMEKVKQELESMKAKLS 900
901 STQQSLAEKETHLTNLRAERRKHLEEVLEMKQEALLAAISEKDANIALLE 950
951 LSSSKKKTQEEVAALKREKDRLVQQLKQQTQNRMKLMADNYEDDHFRSSR 1000
1001 SNQTNHKPSPDQIIQPLLELDQNRSKLKLYIGHLTALCHDRDPLILRGLT 1050
1051 PPASYNADGEQAAWENELQQMTQEQLQNELEKVEGDNAELQEFANTILQQ 1100
1101 IADHCPDILEQVVNALEESS 1120
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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