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

NucPred

Fetching Q9Y8G8 from www.uniprot.org...

The NucPred score for your sequence is 0.90 (see score help below)

   1  MSDADPFDMSDDDDNSVLSHTPPKKQKKAPTTKKGGSKPLADVENESFMD    50
  51  GIEESNNQDKDTNVSEKYQKLTQLEHIIKRPDTYVGSTERTTQHMWVYSS   100
 101  ESEGMEYREVSYVPGLYKIFDEIVVNAADNKQNDKNMDEIRVTIDRESGE   150
 151  ISVWNNGRGIPIEMHSKEKMYVPELIFGHLLTSSNYDDTQMKVTGGRNGF   200
 201  GAKLCNVFSTEFTIETQDSRQKKKYKQTWTENMTKMGKAKITDAKGADYT   250
 251  KVTFKPDYAKFGMTGMDDDFEALVKRRVYDLAGTAKVAVKLNGSRIPIRN   300
 301  FKMYMEMYTKAIRRERGDMGPAGKNEIITCSPDPRWEVGFAVSDGAFQQV   350
 351  SFVNSIAITSGGTHVNYIADQICSKLAEQVKKKNKNGATLKPAQIRNHIF   400
 401  IFVNALIVNPAFTSQTKEQLTTKQSQFGSKCVLEEDFYKKILKTEVMTNI   450
 451  LHFAQQKADQMLKKTDGGRRSRMNNPKLTDANKAGTKEGHHCTLILTEGD   500
 501  SAKGLAMAGRAVVGPDLFGVFPLRGKLLNVRDASFDQIAKNQEIQNIKNF   550
 551  IGLQHKKEYTDTRGLRYGHLMITTDQDHDGSHIKGLLINFLQAQFPSLLK   600
 601  IPEFLIEFITPIVKVWKGDPKNPTKQRSFFTMPEYEAWKEEHGHERGWEH   650
 651  KYYKGLGTSTTEDAQIYFRDLDRHLKEFHTMQDNEVELIELAFSKKKADE   700
 701  RKGNVRQFRPGTFLDHSVDKITYTDFINKELILFSMADNIRSIPSVVDGL   750
 751  KPGQRKVLYTCFRRNLKKDMKVVELAGHVSGTTAYQHGEGSLQQTIVGLA   800
 801  QTFVGSNNVNCLEPSGNFGSRLQGGADCASARYIYTRLWPFARRVFHNHD   850
 851  DPLLTYNEDDGAKIEQEVYVPVVPMILINGADGIGTGWSSSTPNYNPEDI   900
 901  VENLKRMMDGEPLKPMQPWFRGFTGEVTAVGQDRFKFSGIIKETGDKEVE   950
 951  ITELPIRTWTQDFKDKLEDIIKAEKTPSFIKDYKDYNTHTKVHFVIQMDE  1000
1001  KHMKTAIAEGLEEKFKLSKTMTTTNLVAFDPERITKYASVEDIMKEFYAV  1050
1051  RLKYYERRKQYQLSEMQKELDKLSNQARFVQMIIDGKLVISKKKKAVLVA  1100
1101  ELKEKDFKPFPKVKEAVKAGETEPVVEEEEDSESGDTEVLSNSYDYLLGM  1150
1151  PIWSLTQERVEKLRRQIGDKELEIDTLIKLSKEDIWKRDLEDFINEWRFQ  1200
1201  NDEEARRQRKVANMGRRTSSKLMTTGRGGGAAARKRKAALGDDPDDEDFA  1250
1251  APKSKKSAAAKKTESKGGGLLSFLGKSSAKPKPSPADGGDSDDDFDMEIM  1300
1301  PKKSRGAPKSEPKADPKPKDEDEDIVMEDSDIEEIIPKKSRGSSKPSVKP  1350
1351  ESEDGQAKIAEAPKRGRAAAKPKPKPKSEDEEDELDDDDFMEITKAEAAK  1400
1401  PSAQPARSGRKTTKYAELSDSDSDNGDDLLGDVSKMVKGIGSTNGASTSD  1450
1451  SRLLFSERSRPGSSAGLKTTASKASKPSEFDADETDYSKLVPSNTPRRSL  1500
1501  QVKPKDAKVSDDNEPEDDDDEPVKPAAKGKAAAKGKSTAAAANQLLQRLV  1550
1551  VGRRKMLPKPPPRLPCPLPQRRTHRSNPRPRRPRRRS               1587

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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