 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P15800 from www.uniprot.org...
The NucPred score for your sequence is 0.71 (see score help below)
1 MEWASGKPGRGRQGQPVPWELRLGLLLSVLAATLAQVPSLDVPGCSRGSC 50
51 YPATGDLLVGRADRLTASSTCGLHSPQPYCIVSHLQDEKKCFLCDSRRPF 100
101 SARDNPNSHRIQNVVTSFAPQRRTAWWQSENGVPMVTIQLDLEAEFHFTH 150
151 LIMTFKTFRPAAMLVERSADFGRTWRVYRYFSYDCGADFPGIPLAPPRRW 200
201 DDVVCESRYSEIEPSTEGEVIYRVLDPAIPIPDPYSSRIQNLLKITNLRV 250
251 NLTRLHTLGDNLLDPRREIREKYYYALYELVIRGNCFCYGHASQCAPAPG 300
301 APAHAEGMVHGACICKHNTRGLNCEQCQDFYQDLPWHPAEDGHTHACRKC 350
351 ECNGHSHSCHFDMAVYLASGNVSGGVCDGCQHNTAGRHCELCRPFFYRDP 400
401 TKDMRDPAACRPCDCDPMGSQDGGRCDSHDDPVLGLVSGQCRCKEHVVGT 450
451 RCQQCRDGFFGLSASNPRGCQRCQCNSRGTVPGGTPCDSSSGTCFCKRLV 500
501 TGDGCDRCLPGHWGLSHDLLGCRPCDCDVGGALDPQCDEATGQCPCRPHM 550
551 IGRRCEQVQPGYFRPFLDHLTWEAEGAHGQVLEVVERLVTNRETPSWTGV 600
601 GFVRLREGQEVEFLVTSLPRAMDYDLLLRWEPQVPEQWAELELVVQRPGP 650
651 VSAHSPCGHVLPRDDRIQGMLHPNTRVLVFPRPVCLEPGLSYKLKLKLTG 700
701 TGGRAHPETPYSGSGILIDSLVLQPHVLMLEMFSGGDAAALERRTTFERY 750
751 RCHEEGLMPSKTPLSEACVPLLISASSLVYNGALPCQCDPQGSLSSECNP 800
801 HGGQCRCKPGVVGRRCDACATGYYGFGPAGCQACQCSPDGALSALCEGTS 850
851 GQCLCRTGAFGLRCDHCQRGQWGFPNCRPCVCNGRADECDAHTGACLGCR 900
901 DYTGGEHCERCIAGFHGDPRLPYGGQCRPCPCPEGPGSQRHFATSCHRDG 950
951 YSQQIVCHCRAGYTGLRCEACAPGHFGDPSKPGGRCQLCECSGNIDPTDP 1000
1001 GACDPHTGQCLRCLHHTEGPHCGHCKPGFHGQAARQSCHRCTCNLLGTDP 1050
1051 QRCPSTDLCHCDPSTGQCPCLPHVQGLSCDRCAPNFWNFTSGRGCQPCAC 1100
1101 HPSRARGPTCNEFTGQCHCHAGFGGRTCSECQELHWGDPGLQCRACDCDP 1150
1151 RGIDKPQCHRSTGHCSCRPGVSGVRCDQCARGFSGVFPACHPCHACFGDW 1200
1201 DRVVQDLAARTRRLEQWAQELQQTGVLGAFESSFLNLQGKLGMVQAIVAA 1250
1251 RNTSAASTAKLVEATEGLRHEIGKTTERLTQLEAELTDVQDENFNANHAL 1300
1301 SGLERDGLALNLTLRQLDQHLDILKHSNFLGAYDSIRHAHSQSTEAERRA 1350
1351 NASTFAIPSPVSNSADTRRRAEVLMGAQRENFNRQHLANQQALGRLSTHT 1400
1401 HTLSLTGVNELVCGAPGDAPCATSPCGGAGCRDEDGQPRCGGLGCSGAAA 1450
1451 TADLALGRARHTQAELQRALVEGGGILSRVSETRRQAEEAQQRAQAALDK 1500
1501 ANASRGQVEQANQELRELIQNVKDFLSQEGADPDSIEMVATRVLDISIPA 1550
1551 SPEQIQRLASEIAERVRSLADVDTILAHTMGDVRRAEQLLQDAQRARSRA 1600
1601 EGERQKAETVQAALEEAQRAQGAAQGAIRGAVVDTKNTEQTLQQVQERMA 1650
1651 GTEQSLNSASERARQLHALLEALKLKRAGNSLAASTAEETAGSAQSRARE 1700
1701 AEKQLREQVGDQYQTVRALAERKAEGVLAAQARAEQLRDEARGLLQAAQD 1750
1751 KLQRLQELEGTYEENERELEVKAAQLDGLEARMRSVLQAINLQVQIYNTC 1800
1801 Q 1801
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.) |
Go back to the NucPred Home Page.