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

NucPred

Fetching Q9D2G5 from www.uniprot.org...

The NucPred score for your sequence is 0.68 (see score help below)

   1  MALSKGLRLLARLDPTGPSSVLLEARGRGDCLLFEAGAVATLAPEEKEVI    50
  51  KGLYSKLTDAYGCLGELRLQSGGVPLSFLVLVTGCMSVGRIPDAEIYKIT   100
 101  ATELYPLQEEAKEEDRLPTLKKILSSGVFYFAWPNDGACFDLTIRAQKQG   150
 151  DDGSEWGTSFFWNQLLHVPLRQHQVNCHNWLLKVICGVVTIRTVYASHKQ   200
 201  AKACLISRISCERAGARFLTRGVNDDGHVSNFVETEQTIYMDDGVSSFVQ   250
 251  IRGSVPLFWEQPGLQVGSHHLRLHRGLEANAPAFERHMVLLKEQYGKQVV   300
 301  VNLLGSRGGEEVLNRAFKKLLWASCHAGDTPMINFDFHQFAKGRKLEKLE   350
 351  NLLRPQLQLHWEDFGVFAKGENVSPRFQKGTLRMNCLDCLDRTNTVQCFI   400
 401  ALEVLHLQLESLGLNSKPIIDRFVESFKAMWSLNGHSLSKVFTGSRALEG   450
 451  KAKVGKLKDGARSMSRTIQSNFFDGVKQEAIKLLLVGDVYNEESTDKGRM   500
 501  LLDNTALLATPRILKAMTERQSEFTNFKRIQIAVGTWNVNGGKQFRSNLL   550
 551  GTAELTDWLLDAPQLSGAVDSQDDGSPADVFAIGFEEMVELSAGNIVNAS   600
 601  TTNRKMWGEQLQKAISRSHRYILLTSAQLVGVCLYIFVRPYHVPFIRDVA   650
 651  IDTVKTGMGGKAGNKGAVGIRFQLHSTSFCFVCSHLTAGQSQVKERNEDY   700
 701  REITHKLSFPSGRNIFSHDYVFWCGDFNYRIDLTYEEVFYFVKRQDWKKL   750
 751  MEFDQLQLQKSSGKIFKDFHEGAVNFGPTYKYDVGSAAYDTSDKCRTPAW   800
 801  TDRVLWWRKKHPYDKTAGELNLLDSDLDGDPQIRHTWSPGTLKYYGRAEL   850
 851  QASDHRPVLAIVEVEVQEVDVGARERVFQEVSSVQGPLDATVVVNLQSPT   900
 901  LEEKNEFPEDLRTELMQTLGNYGTIILVRINQGQMLVTFADSHSALSVLD   950
 951  VDGMKVKGRAVKIRPKTKDWLEGLREELLRKRDSMAPVSPTANSCLLEEN  1000
1001  FDFSSLDYESEGDVLEEDEDYLVDGFGQPVVSDSELGGDNSSDTMSSLTP  1050
1051  ASKSPALAKKKQHPTYKAGLMVKKSASDASISSGTHGQYSILQTAKLLPG  1100
1101  APQQPPKARTGISKPYNVKQIKTTNAQEAEAAIRCLLEASGGVPESAPGA  1150
1151  IPLRNQGSSKPEATLGPPALPRRPAPRVPTMKKPTLRRTGKPMLPEENFE  1200
1201  PQPVHFTMASQEMNLETPPPITATPIPPVPKPRTLQPGKGVEGRPSSGKP  1250
1251  EPDEAPSVTGTVESPPPEAQEAPSLAPKVPPRRKKSAPAAFHLQVLQNNS  1300
1301  QVLQGLTCSSSSPPSLKPDTHPLCLQVALGTSSARSPETHGPRVTEPEAA  1350
1351  SFHGNYPDPFWSLLHHPKLLNNTWLSKSSEPLDVGSRNPERTHTEPAQVN  1400
1401  ASLAERGLPPDHGGKDLSHWVTASNKDKRTTLGV                  1434

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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