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

NucPred

Fetching Q9P7Q7 from www.uniprot.org...

The NucPred score for your sequence is 0.93 (see score help below)

   1  MRPPDDQINNNVGSNSHLEKLKEAMDHQLQKSSKIVGSFTNSQNSSVGSV    50
  51  HSPILESPTSLNRQHRNSFSFNNVSSPSLEDERLINFPRVNPNRLMTSKR   100
 101  PNELFKTSSMSSDCYSPQKSRESLNSLCHSPAPSVSSCGNALNNDNTSAS   150
 151  HSLTDEQPFETDSSANLFKQLQEKRNRTIGNVYEMACLLVFKTGLMNFWK   200
 201  NIIDFFAQQFFSTQISVVEPRDLSDIYNTPWQLRCYYDGGSHYDPYSNPI   250
 251  SVNDNLASSSYVTVVASDGSKGIIYKDPASLKHEGDLLIDSKVVQTVLER   300
 301  ATLLVYTRKQQHIVKNTKVHDNDYFSSIPNVDDIRSIKNSWKVFHDEKLN   350
 351  ELKKQVEISASAAQLNGLYPQKKRAFVSHFSQNRKPYSQSDISKAQSSSF   400
 401  SEEPSNIYDEYEQNLLSPWSRSPVASPSIQTDPNRNPFFQNCLQESSFAT   450
 451  ESSTEKSASESVSETAVNDDCKGMNFSGNRRQEDHLNDFTSFPTETAVSI   500
 501  VHVPLMFPCSDQTSSRGRAPIAILSFKSNLVPYPENLIASIERLIPFIFS   550
 551  SYSNSQSVPLLPCPTQRHLLFNTSSTDNTKELSMSASSENSDCPHKEGEC   600
 601  VGSFCNINAKGSSLNNIPKLPRFVPVPSEFFKKNQRSWVTLKKHRLLARL   650
 651  KSRISKKNSKVNENLRFSLNDGENYSNETITLKKDEIVLDKSKSYACCTS   700
 701  ESHKYVQGHCGGQAPPFPLLKVIIDSIPVHVFTADPGSGKLTWVNRKTLL   750
 751  YCGLNMNEQIELQFSRIHPDDLPNFLNDWKSSLFSGSGFYHEIRLQRFDN   800
 801  VYRYFICRAVPLRDCTGSVLHFFGTMTDVHDQKLAERELQKQSAIAANEN   850
 851  SYRSLAEASPQIVFAANGKNGIIYANAQWLSYSGLSLESSLGLGFLSAVY   900
 901  HADRKKCLLPESLEGTFNNQDESNGTKTFAAEIRFRSTDGHYRWHLVKSV   950
 951  CVNNSADTSTNLWLGTCTDIHDHKMLEEKLQESNIEAQRIVRSKMQYLSN  1000
1001  MSHEIRTPLIGITGMVSFLLETQMSAEQLSYARIIQQSAKSLLTVINDIL  1050
1051  DLSKVRAGMMKLTSQRFSVRAMMEDANETLGTLAFSKGIELNYTVDIDVP  1100
1101  DIVFGDNMRMRQVALNVIGNAIKFTNVGEVFTRCSVEKIDYSTNTVVLKW  1150
1151  ECIDTGQGFNRDDQLQMFKPFSQVESSTLPRHGGSGLGLVISKELVELHN  1200
1201  GSMSCQSRRGVGTRFMWTATFTMDKTPLKFEPPDGCCPVCFCPYEKSKQS  1250
1251  TEDYYCADDGNDKSATNFVKLAVNKADPGRESNRRKLESDKNVQSNKYVN  1300
1301  PFASESEFCRCGASADPYTVLFWRLYRNKPSGIKLDKSALAVVVSHTKYS  1350
1351  SEAIGNMLQSIIDISSFKDIVRYGNTYEAFEELLENPMQSKVTHIILNLP  1400
1401  DIEAYVLFVKSLQLCSLYKDTKFILVTSTRQKESLSKIFSDSEDCNSESI  1450
1451  HYVLKLVKPSKFFPLFYSDSEEKGKIGALNDMTRKAAMEQKADAETLRYN  1500
1501  LAKSGFSVLLAEDNIINIKVISRYLERIGVKFKVTMDGLQCVEEWKREKP  1550
1551  NFYSLILMDLQMPVMDGYQACNEIRKYELENDYPKVPIVALSANALPHVV  1600
1601  LSCKDSGFDSYLAKPITLQHLSLIISGILNYTNQSKLHK             1639

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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