 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q7TNF8 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MEQLTTLPRLGDLGAMEPWALPAWQHWTQGQGCKPGDASPSIAGTPTALQ 50
51 VKGLRFEESSKPEGAHSPGPVGNTDPEATETGLPKLGQQAESPGYSCSGL 100
101 EEEEAQAYKAKFNIGFGDRPNLELLRALGELQQRCTILKEENQMLRKSSF 150
151 PETEEKVRRLKRKNAELAVIAKRLEERAQKLQETNMRVVSAPVPRPGSSL 200
201 ELCRKALARQRARDLSETASALLAKDKQIAALQRECRELQARLSLVGKEG 250
251 PQWLHMRDFDRLLRESQREVLRLQRQIALRNQREPLRPARSPGPTAPSRV 300
301 GAPAPGAPGEAVLQDDVESPQVVLREPEKQQRVQQLESELCKKRKKCESL 350
351 EQEARKKQRRCEELELQLRAAQNENARLVEENSRLSGRATEKEQVEWENS 400
401 ELKGQLLGVTQERDSALLKSQGLQSKLESLEQVLKHMREVAQRRQQLEVE 450
451 HEQARLSLQEKQEEVRRLQQAQAEAKREHEGAVQLLESTLDSMQARVREL 500
501 EGQCRSQTERFSLLAQELQAFRLHPGPLDLLTSALGCSALGDHPPPHCCC 550
551 SIPQPCQGSGPKDLDLPPGSPGRCTPKSSEPALTTLTGIPRRTAKKAESL 600
601 SNSSRSESIHNSPKSCPTPEVDTASEVEELEVDSVSLLPAAPESHSGGAR 650
651 IQVFLARYSYNPFEGPNENPEAELPLTAGEYIYIYGNMDEDGFFEGELMD 700
701 GRRGLVPSNFVERVSDDDLLSTLPRELADSSHSSGPELSFLSGGGGGCSS 750
751 GGQSSGGRSQPRPEEEAAGDELSLSPPPEGLGEPLAVPYPRHITVLKQLA 800
801 HSVVLAWELPPERVDLRGFHIFVNGELRQALGPGVPPKAVLENMDLRTGP 850
851 LHVSVQALTSKGSSDPLRCCLAVGAGAGVVPSQLRIHRLTATSAEIAWVP 900
901 GNSNLAHAIYLNGEECPPARPSTYWATFCNLRPGTLYQARVEAQIPSQGP 950
951 WEPGWERPEQRAATLQFTTLPAGLPDAPLDVQAEPGPSPGILMISWLPVT 1000
1001 IDAAGTSNGVRVTGYAIYADGQKIMEVASPTAGSVLVEVSQLQLLQACHE 1050
1051 VTVRTMSPHGESSDSIPAPVAPALASACQPARMSCLSPRPSPEVRTPLAS 1100
1101 VSPGLGDTSFPLRHPVPHGTQDFSASLSIEMSKGPQEEPPVPCSQEEAGA 1150
1151 AVRSISEEKRAIEPTLGQEGPEPVAPSLAKQEVECTSGDAGPVPCSTQGE 1200
1201 LTQKKPSIEACHGGDLDSGLKLRSEKEDMSELGVHLVNSLVDHSRNSDLS 1250
1251 DIQEEEEEEEEEEEELGSRPCSSQKQVAGNSIRENGAKPQPDPFCETDSD 1300
1301 EEILEQILELPLQRLCSKKLFSIPEEEEEEEEEEGLEKPGPSRTSQDPSQ 1350
1351 PELALLGPGCDSSQPQGPGLCPLSPELSGVREHLEDVLGVVGGNGRRRGG 1400
1401 GSPEKLPNRKRPQDPREHCSRLLGNGGPQASARPVPPRERGSLPVIEGTR 1450
1451 VGQEPGGRGRPGLSRRCPRGPAPESSLVSCLSPKCLEISIEYDSEDEQEA 1500
1501 GSGGVSINSSCYPTDGEAWGTAAVGRPRGPPKVNPGPNAYLRLPAWEKGE 1550
1551 PERRGRSAIGRTKEPPSRATETGESRGQDNSGRRGPQRRGARVPRSGTTE 1600
1601 LAPPRSPQEAPPHQDLPVRVFVALFDYDPVSMSPNPDAGEEELPFKEGQL 1650
1651 LKVFGDKDADGFYRGESGGRTGYIPCNMVAEVAVDSPAGRQQLLQRGFLP 1700
1701 PNVLTEASGNGPSVYSSAHTPGPPPKPRRSKKVELEGPTQLCPGPPKLIH 1750
1751 SAAQKTSRPMVAAFDYNPRENSPNMDVEAELPFRAGDVITVFGNMDDDGF 1800
1801 YYGELNGQRGLVPSNFLEGPGPESGSLESGTSQAESQRTRRRRVQC 1846
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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