 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q62924 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MQKMQCHLRRPLHSSSSFSSQAVMMTKPMQEHKKEYTAQQALFRPSGIVT 50
51 SIPVPLAGSALLPYHVSSTLYQSKSLSSSEHNKANGGSPQEHIAMESSAE 100
101 EVDCFKNTCLPSELSPCSQNDFKPTNGDIDMQSPSKLMSGSMIISNFSTA 150
151 MVHTIVNETLESMTSFKATKPVDTNADYLTKTIKGKPVLSLCDQAAPQQN 200
201 KASSKDMFAEHLSKSIIKHSLDKSKSVLPNIDKKPVSKEHMLVLGEESQL 250
251 TLGETPKFLDFSDNSPQYCVPECKDSVGFGFSLEALPPCSMMTSQKSDLK 300
301 GVMKDKVVTRHNLTNTAFEPLSFGQESSFRPSQTLSSAVLTCVDSLHVED 350
351 KQKIRDRNVIPDTPPSTPLVPSQTSSEWDIKKLTKQLKGELAKEFAPATP 400
401 PSTPHNSSVGSLSENEQTTIEKEEFMLKLMRSLSEEVESSEGEEHPEMDV 450
451 KSEHSGKKGQFADALATHIISLATEVAASHLDHEITQEFKVQNSHLTVPS 500
501 QRSMLPALSHSDESIQTCSFASDMAAGVIAEAEKVANTRSCMLFGHERTI 550
551 CHVEGDRGKAEEKLDVEDIAHPREVETCVLSLPSCMPGLTYKYPSCESVT 600
601 DEYAGHIIQVLKQEGGNSELIMDQYASRLAYRSVKSGVREAAKTVKVKCS 650
651 LKLFPMHTSHVKTNKELLFSSKEHHQEVDKKRQRKKYGSHPCKYQTCDRT 700
701 QDPCRNELSELYRFSASLASSITRDVKKQLTAPKVDLPKSSTDCCLFEKS 750
751 ECVDNRENVTGPEFSKSCQPLQNHGLCQNTSSLSGYSCGESAHTVEQYAR 800
801 KVVGDTLELSLGPAVFLNSETTTSPDRITYAEKLSPLINEACRYCDLKES 850
851 HGCIRNSAQLFSKQGPCASAKPSSHSKLSSIRQKSRIFHLDVPQIHLNLD 900
901 KRAVLAEKIVAEAIEKAERELSNTSLAADSGIGQDGISFAESLTTEIMTT 950
951 AMTNAGHAVSSSKEVEDFQSTESLGSQQMNLSVGEDSTGSWSNLSFEDDH 1000
1001 QDESSSFHHLSESSNGNSSSWSSLGLEGDLYENNLSFPTSDSDGPDDRES 1050
1051 EQEDGAEGLQPSGKTLLIVNIDVEPGAVDPQLRVILQWLIPRRRKLENFI 1100
1101 FSTLQRRSLSYFQSSYRREDGKWAMSCRL 1129
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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