 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P54674 from www.uniprot.org...
The NucPred score for your sequence is 0.81 (see score help below)
1 MKMSEGIISPLSLSSESSEQQQAAIRKFSNGSNGSGGGGGSNLSVNSSNS 50
51 GSNNSIRKSSTLMYNGPLPSINDGKELLLENSKPKVVELVNTFNHKPLST 100
101 IHSVHNEIPPPAIEKEKKEIINTISNSGVTKYMTALEILDSTINTPLNRS 150
151 RSGSIGSKPICNNLTSSSSSSSTTATTPSPTTTSNNNNNNNNNNNNNNNN 200
201 NNNNNNNNNNNNNNNNNNNNNNNNNNTTSTTTTTTSILISSSPPPSSSSS 250
251 SSSNDEQFNNNNNNNNSNSGGSSRMITSKSQIKPLIVTSNTAATTTTTTT 300
301 TNTSAPTTPTNRVQSSLDDLLFNLPTIPSNVPTVNGGPKISAVPKKVSSS 350
351 KLLIPPSSNVSSSSNITLSLSSSSPSSSSSSSTSTVVPIVQLSSSNSTNS 400
401 PSTSLPTTPRLSQPTTSYTQLIPSQQQQQPTESNSSSNTNTTTTSSSSSS 450
451 SSSSLTISSPQPSNNSIRISAFGRSSTQFTISSNGIPSSPGQVSNKDYNN 500
501 IGNLSNSSGERVKNKQYSMLNISKKTILDESDISSSPRSIGSPNSIRASI 550
551 SSQLPPSLSSIGGGGGGGSGPNVVSNKPLVVKKPSTSEHIKKENIWRQTM 600
601 IPLTKEDHIKVVFEGIPGKRVIQKFLIDKTPIEIKSKFFEDLKDGDLLNG 650
651 LTQLPSLIPEHYELKVLSVNSTISNETLPLRRQTLMQACNISRLFPKLHL 700
701 ILKSESTTILDGASTTTTTTTTTTTTTANQSSNIITKSNSSLDLTINNSN 750
751 EIIDVKGHIQAELEIFELIGTSFTRVLDQGQEVVSFRRDFAQFRLSNFTS 800
801 TRNDLSQMIYVSSEPLPLTIPNKITIMVLLPGDGKIIKRVDCCPNSSVGD 850
851 VKKEIFKKFAMIDRVHTQGKTQDDFVLKVTGFREYILCIHELGNLTSRQR 900
901 FYPTGSGGDFSLMDYDYIRQCVGKNQTVELSLTNNSILSLNQVSEKVSFI 950
951 DKILETSDFDDYDEDLDSINSNSFDDLKQSIQQQQQQQIQTVINIKETNK 1000
1001 ENKDSNKENKDSSSNNNNNNNNNNNNNNNNNNNNNNNNNNNGNNNGNNSN 1050
1051 NNSNSNISRGSIDSEGNGSGSGNGSEQPTLIGVQNFSLPNNSKLPINIVK 1100
1101 RLFRVNIAGLRNLNFNNNEDARNKFADGKNNQPNVFVMAELYYGGELLTN 1150
1151 PVFTPIAQLASYGDGSVEFPNWEKGIAFTIPIRYLPRAARASFTVYVTTI 1200
1201 SEALESQMDEVVSKSIPIGWSNCLLMNHKGMLRMGPTAFRLWDDGRRANP 1250
1251 IGTCVDNQAAKQPIILLVEFESFIRPIVYVDTALQSMMVNDSSSISSNGV 1300
1301 ESPSIVSFSSSAASSSPLPSSPLPSPVGLKKLDLDEARRLKALMDSDPLV 1350
1351 QLSAEDKKLVYGYRHIYKSKPKALAKFLLSVNWIDPDQVTDAYRQMNDWA 1400
1401 LLKPVQALEILDAKFADEHVRNFAIKIINSFSDAEFSDFLLQLTQVLKYE 1450
1451 PYHNSDLTHILIQRALSNRSRIGHFFFWFLKSEMHTPEIEERYGLLLEGY 1500
1501 LRSCGTHRQDLIKQNQVLKSLHTVAMAVKQTNGSSERKKVLMEGLSKIKF 1550
1551 PDTFQLPLDPRWEAKGLIIDKCRYMDSKKLPLWLVFENVEPHAKPLTVIF 1600
1601 KVGDDLRQDILTLQVLRIMDKFWKNSGMDLRLQPYKCIATGDGIGMLEVV 1650
1651 LNANTIANINKDAGGTGALLEEKTLVNWLKECNKTEAEYNKAVETFILSC 1700
1701 AGYVVATYVMGIGDRHSDNIMITKLGHLFHIDFGHFLGNYKKKYGFKRER 1750
1751 APFIFTPQYMAIVGGKDSENFKRFVTTCCSAYNILRKNTDLFINLFQLML 1800
1801 STGIPELQVAEDIDYLRKALAPGLSDEEAAEEFTKNISVALNTKTVLLND 1850
1851 IFHGWAH 1857
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.