SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching Q92093 from www.uniprot.org...

The NucPred score for your sequence is 0.29 (see score help below)

   1  MRAVVLALTLALVASQSVNFAPDFAASKTYVYKYEALLLGGLPEEGLARA    50
  51  GVKVISKVLISAVAENTYLLKLVNPEIFEYSGVWPKDPFVPAAKLTSALA   100
 101  AQFSIPIKFEYAKGVVGKVLAPTAVSETVLNVHRGILNILQLNIKKTQNV   150
 151  YELQEAGAQGVCKTHYVIREDAKAERIHLTKSKDLNNCQQRIMKDFGLAY   200
 201  TEKCVECRQRGEALMGAATYNYLMKPADNGALILEATVTELHQFTPFNEM   250
 251  SGAAQMEAKQMLTFVEIKKDPIIVPDNNYVHRGSIRYEFATEILQMPIQL   300
 301  LKISNARAQAVKILNHLVTYNTAPVHEDAPLKFLQFIQLLRMASSETINA   350
 351  IWAEFKAKPAYRHWILDAVPSIGSSVAVRFIKEKFLAGDITIFEAAQALV   400
 401  AAVHMVAADLETVKLVESLAFNHKIQTHPVLRELTMLGYGTMVSKYCVEH   450
 451  PNCPAELVKPIHELAVQAVANSKFEELSMVLKALGNAGHPASIKPITKLL   500
 501  PVFGTAAAALPLRVQADAVLALRNIAKREPRMVQEVAVQLFMDKALHPEL   550
 551  RMLACIVLFETKPPMGLVITLASILKTEKNMQVASFTYSHMMSLTRSTAP   600
 601  DFASVAAACNVAVKMLSNKFRRLSCHFSQAIHLDAYSNPLRIGAAASAFY   650
 651  INDAATLFPRTVVAKARTYFAGAAADVLEVGVRTEGIQEALLKLPPAPEN   700
 701  ADRITKMRRVIKALSDWRSLATSKPLASIYVKFFGQEIAFANIDKSIIDQ   750
 751  ALQLANSPSAHALGRNALKALLAGATFQYVKPLLAAEVRRIFPTAVGLPM   800
 801  ELSYYTAAVAKAYVNVRATLTPALPETFHAAQLLKTNIELHAEVRPSIVM   850
 851  HTFAVMGVNTAFIQAAIMARAKVRTIVPAKFAAQLDIANGNFKFEAFPVS   900
 901  PPEHIAAAHIETFAVARNVEDVPAERITPLIPAQGVARSTQQSRDKLTSM   950
 951  IADSAASFAGSLSRSSEILYSDLPSNFKPIIKAIVVHLEETICVERLGVK  1000
1001  ACFEFTSESAAFIRNTLFYNMIGKHSVLISVKPSASEPAIERLEFEVQVG  1050
1051  PKAAEKIIKVITMNEEEEAPEGKTVLLKLKKILLPDLKNGTRASSSSSSS  1100
1101  SSSSSRSSSSRSRSRKSESSSSSSSSSSRISKRDGPDQPYNPNDRKFKKN  1150
1151  HKDSQSTSNVISRSKSSASSFHAIYKQDKFLGNKLAPMVIILFRLVRADH  1200
1201  KIEGYQVTAYLNKATSRLQIIMAALDENDNWKLCADGVLLSKHKVTAKIA  1250
1251  WGAECKDYNTFITAETGLVGPSPAVRLRLSWDKLPKVPKAVWRYVRIVSE  1300
1301  FIPGYIPYYLADLVPMQKDKNNEKQIQFTVVATSERTLDVILKTPKMTLY  1350
1351  KLGVNLPCSLPFESMTDLSPFDDNIVNKIHYLFSEVNAVKCSMVRDTLTT  1400
1401  FNNKKYKINMPLSCYQVLAQDCTTELKFMVLLKKDHASEQNHINVKISDI  1450
1451  DVDLYTEDHGVIVKVNEMEISNDNLPYKDPSGSIKIDRKGKGVSLYAPSH  1500
1501  GLQEVYFDKYSWKIKVVDWMKGQTCGLCGKADGENRQEYRTPSGRLTKSS  1550
1551  VSFAHSWVLPSDSCRDASECLMKLESVKLEKQVIVDDRESKCYSVEPVLR  1600
1601  CLPGCLPVRTTPITIGFHCLPVDSNLNRSEGLSSIYEKSVDLMEKAEAHV  1650
1651  ACRCSEQCM                                           1659

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

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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