 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P19812 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MSVADDDLGSLQGHIRRTLRSIHNLPYFRYTRGPTERADMSRALKEFIYR 50
51 YLYFVISNSGENLPTLFNAHPKQKLSNPELTVFPDSLEDAVDIDKITSQQ 100
101 TIPFYKIDESRIGDVHKHTGRNCGRKFKIGEPLYRCHECGCDDTCVLCIH 150
151 CFNPKDHVNHHVCTDICTEFTSGICDCGDEEAWNSPLHCKAEEQENDISE 200
201 DPATNADIKEEDVWNDSVNIALVELVLAEVFDYFIDVFNQNIEPLPTIQK 250
251 DITIKLREMTQQGKMYERAQFLNDLKYENDYMFDGTTTAKTSPSNSPEAS 300
301 PSLAKIDPENYTVIIYNDEYHNYSQATTALRQGVPDNVHIDLLTSRIDGE 350
351 GRAMLKCSQDLSSVLGGFFAVQTNGLSATLTSWSEYLHQETCKYIILWIT 400
401 HCLNIPNSSFQTTFRNMMGKTLCSEYLNATECRDMTPVVEKYFSNKFDKN 450
451 DPYRYIDLSILADGNQIPLGHHKILPESSTHSLSPLINDVETPTSRTYSN 500
501 TRLQHILYFDNRYWKRLRKDIQNVIIPTLASSNLYKPIFCQQVVEIFNHI 550
551 TRSVAYMDREPQLTAIRECVVQLFTCPTNAKNIFENQSFLDIVWSIIDIF 600
601 KEFCKVEGGVLIWQRVQKSNLTKSYSISFKQGLYTVETLLSKVHDPNIPL 650
651 RPKEIISLLTLCKLFNGAWKIKRKEGEHVLHEDQNFISYLEYTTSIYSII 700
701 QTAEKVSEKSKDSIDSKLFLNAIRIISSFLGNRSLTYKLIYDSHEVIKFS 750
751 VSHERVAFMNPLQTMLSFLIEKVSLKDAYEALEDCSDFLKISDFSLRSVV 800
801 LCSQIDVGFWVRNGMSVLHQASYYKNNPELGSYSRDIHLNQLAILWERDD 850
851 IPRIIYNILDRWELLDWFTGEVDYQHTVYEDKISFIIQQFIAFIYQILTE 900
901 RQYFKTFSSLKDRRMDQIKNSIIYNLYMKPLSYSKLLRSVPDYLTEDTTE 950
951 FDEALEEVSVFVEPKGLADNGVFKLKASLYAKVDPLKLLNLENEFESSAT 1000
1001 IIKSHLAKDKDEIAKVVLIPQVSIKQLDKDALNLGAFTRNTVFAKVVYKL 1050
1051 LQVCLDMEDSTFLNELLHLVHGIFRDDELINGKDSIPEAYLSKPICNLLL 1100
1101 SIANAKSDVFSESIVRKADYLLEKMIMKKPNELFESLIASFGNQYVNDYK 1150
1151 DKKLRQGVNLQETEKERKRRLAKKHQARLLAKFNNQQTKFMKEHESEFDE 1200
1201 QDNDVDMVGEKVYESEDFTCALCQDSSSTDFFVIPAYHDHSPIFRPGNIF 1250
1251 NPNEFMPMWDGFYNDDEKQAYIDDDVLEALKENGSCGSRKVFVSCNHHIH 1300
1301 HNCFKRYVQKKRFSSNAFICPLCQTFSNCTLPLCQTSKANTGLSLDMFLE 1350
1351 SELSLDTLSRLFKPFTEENYRTINSIFSLMISQCQGFDKAVRKRANFSHK 1400
1401 DVSLILSVHWANTISMLEIASRLEKPYSISFFRSREQKYKTLKNILVCIM 1450
1451 LFTFVIGKPSMEFEPYPQQPDTVWNQNQLFQYIVRSALFSPVSLRQTVTE 1500
1501 ALTTFSRQFLRDFLQGLSDAEQVTKLYAKASKIGDVLKVSEQMLFALRTI 1550
1551 SDVRMEGLDSESIIYDLAYTFLLKSLLPTIRRCLVFIKVLHELVKDSENE 1600
1601 TLVINGHEVEEELEFEDTAEFVNKALKMITEKESLVDLLTTQESIVSHPY 1650
1651 LENIPYEYCGIIKLIDLSKYLNTYVTQSKEIKLREERSQHMKNADNRLDF 1700
1701 KICLTCGVKVHLRADRHEMTKHLNKNCFKPFGAFLMPNSSEVCLHLTQPP 1750
1751 SNIFISAPYLNSHGEVGRNAMRRGDLTTLNLKRYEHLNRLWINNEIPGYI 1800
1801 SRVMGDEFRVTILSNGFLFAFNREPRPRRIPPTDEDDEDMEEGEDGFFTE 1850
1851 GNDEMDVDDETGQAANLFGVGAEGIAGGGVRDFFQFFENFRNTLQPQGNG 1900
1901 DDDAPQNPPPILQFLGPQFDGATIIRNTNPRNLDEDDSDDNDDSDEREIW 1950
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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