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

NucPred

Fetching Q62910 from www.uniprot.org...

The NucPred score for your sequence is 0.79 (see score help below)

   1  MAFSKGFRIYHKLDPPPFSLIVETRHKEECLMFESGAVAVLSSAEKEAIK    50
  51  GTYAKVLDAYGLLGVLRLNLGDTMLHYLVLVTGCMSVGKIQESEVFRVTS   100
 101  TEFISLRVDASDEDRISEVRKVLNSGNFYFAWSASGVSLDLSLNAHRSMQ   150
 151  EHTTDNRFFWNQSLHLHLKHYGVNCDDWLLRLMCGGVEIRTIYAAHKQAK   200
 201  ACLISRLSCERAGTRFNVRGTNDDGHVANFVETEQVIYLDDCVSSFIQIR   250
 251  GSVPLFWEQPGLQVGSHRVRMSRGFEANAPAFDRHFRTLKDLYGKQIVVN   300
 301  LLGSKEGEHMLSKAFQSHLKASEHASDIHMVSFDYHQMVKGGKAEKLHSV   350
 351  LKPQVQKFLDYGFFYFDGSAVQRCQSGTVRTNCLDCLDRTNSVQAFLGLE   400
 401  MLAKQLEALGLAEKPQLVTRFQEVFRSMWSVNGDSISKIYAGTGALEGKA   450
 451  KLKDGARSVTRTIQNNFFDSSKQEAIDVLLLGNTLNSDLADKARALLTTG   500
 501  SLRVSEQTLQSASSKVLKNMCENFYKYSKPKKIRVCVGTWNVNGGKQFRS   550
 551  IAFKNQTLTDWLLDAPKLAGIQEFQDKRSKPTDIFAIGFEEMVELNAGNI   600
 601  VNASTTNQKLWAVELQKTISRDNKYVLLASEQLVGVCLFVFIRPQHAPFI   650
 651  RDVAVDTVKTGMGGATGNKGAVAIRMLFHTTSLCFVCSHFAAGQSQVKER   700
 701  NEDFVEIARKLSFPMGRMLFSHDYVFWCGDFNYRIDLPNEEVKELIRQQN   750
 751  WDSLIAGDQLINQKNAGQIFRGFLEGKVTFAPTYKYDLFSEDYDTSEKCR   800
 801  TPAWTDRVLWRRRKWPFDRSAEDLDLLNASFQDESKILYTWTPGTLLHYG   850
 851  RAELKTSDHRPVVALIDIDIFEVEAEERQKIYKEVIAVQGPPDGTVLVSI   900
 901  KSSAQENTFFDDALIDELLQQFAHFGEVILIRFVEDKMWVTFLEGSSALN   950
 951  VLSLNGKELLNRTITITLKSPDWIKTLEEEMSLEKISVTLPSSTSSTLLG  1000
1001  EDAEVSADFDMEGDVDDYSAEVEELLPQHLQPSSSSGLGTSPSSSPRTSP  1050
1051  CQSPTAPEYSAPSLPIRPSRAPSRTPGPLSSQGAPVDTQPAAQKESSQTI  1100
1101  EPKRPPPPRPVAPPARPAPPQRPPPPSGARSPAPARKEFGGVGAPPSPGV  1150
1151  TRREMEAPKSPGTARKDNIGRNQPSPQAGLAGPGPSGYGAARPTIPARAG  1200
1201  VISAPQSQARVSAGRLTPESQSKPLETSKGPAVLPEPLKPQAAFPPQPSL  1250
1251  PTPAQKLQDPLVPIAAPMPPSIPQSNLETPPLPPPRSRSSQSLPSDSSPQ  1300
1301  LQQEQPTGQQVKINGACGVKQEPTLKSDPFEDLSLSVLAVSKAQPSAQIS  1350
1351  PVLTPDPKMLIQLPSASQSKVNSLSSVSCMLTMPPVPEQSKSQESVGSSA  1400
1401  NPFPSLPTRNPFTDRTAAPGNPFRVQSQESEATSWLSKEEPVSNSPFPPL  1450
1451  MPLSHDMSKPSSSLDGFEDNFDLQSQSTVKTSNPKGWVTFDEDEDFPTKG  1500
1501  KSRSVYPDSLGNTAASFDDDWSKGTNVSFCVLPARRPPPPPPPVPLLPPG  1550
1551  TTSSAGPSTTLSSKASPTLDFTER                            1574

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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