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

NucPred

Fetching Q91660 from www.uniprot.org...

The NucPred score for your sequence is 0.94 (see score help below)

   1  MEAQSRSTTASEKKKVENSIVKGHSRTEVSEKAVASSTTSNEDESPGQTY    50
  51  HRERRNAIAMQPQGGQGLGKISEEPSTSSEERASLIKKELHGSITHLPEP   100
 101  SVPYRGTVFAMDPRNGYIDPHYRSDLDLFPAFHPPVPIDARHHEGRYHYE   150
 151  PTPIPPLHVPTALASSPTYPDLPFFRISPHRNPASASDSPFSPPHPYISP   200
 201  YMDYIRSLHSSPSLSMISAARGLSPTDVPHAGISPAEYYHQMALLAGQRS   250
 251  PYADIFPSPATAGAGANALHMEYLHAMESSRFSSPRLSARPSRKRTLSIS   300
 301  PLSDHSFDLQTMIRNSPNSLVTILNNSRSSSSASGSYGHLAASAISPALN   350
 351  FAYQPTPVSLQQMHQQIMSRQHSIGSAFGHSPPLLHPAPTFPSQRTIPGI   400
 401  PSVLNPVQVSIGPSEAAQQNKPTSESAVSSTGDLLHNKRSKVKPEEDHPS   450
 451  PGAVCIQDQPDGMTLVKEEGVKDESKQEAEVVYETNCHWEGCSREFDTQE   500
 501  QLVHHINNDHIHGEKKEFVCRWLDCSREQKPFKAQYMLVVHMRRHTGEKP   550
 551  HKCTFEGCSKAYSRLENLKTHLRSHTGEKPYVCEHEGCNKAFSNASDRAK   600
 601  HQNRTHSNEKPYVCKIPGCTKRYTDPSSLRKHVKTVHGPEAHVTKKQRGD   650
 651  IHPRPPPPREPGSHSQSRSPGQQTQGIHGEHKDLSNTTSKHEECLQVRSV   700
 701  KTEKPMSSQPSPGGKSSCSRQQSPISNYTNSGIELNLNSGGSIGDFSALD   750
 751  ETPIMDSTISTATTGLGLHGRRVMTGTKWMEQIKVEKMKQVNGMLPRLNP   800
 801  VPPHRAPTLPPITGNGVQLNSNISLGGLAPVLPNRNDLSSMDITVLNMLN   850
 851  RRDSNTSTISSAYMSSRRSSGISPCFSSRRSSEASQFEGRVQNLSVAGSY   900
 901  DPISTDASRRSSETSQCDGLPTLLSLTPAQQYRLKAKYAAATGGPPPTPL   950
 951  PNMERMSLKTRMALLGDSRDCRLSPLPSVNVPRRCSDGGVGSYGRRHLLP  1000
1001  NELQVNGMRRASDPVKMVSDNVSNTRVVRFNSLNNVIPPDVPPPMERRNL  1050
1051  SLQNYTRNVYSPCPPSISENVALEAMIMEAEGNFDDEDLLPDDMVQYLNS  1100
1101  RNQRLYETIETDALQNNAGERNGNNFEQSHVTSNVINEQFHSSEQTDLIE  1150
1151  NKNDLPIQWNEVSSGSAEYSPSRLKYGQRFPTQQNQPFGLYNNMMVQQQN  1200
1201  VPKSGLSQQRGYQHHTQNNPQAPQQNLDLYNNSNVWSGQLGRGNQYIDDI  1250
1251  ERSSLGHSATGSLCNSAARGQKLTTNGLPMNTGQQNFGPSTHYSVQSANR  1300
1301  AEVVQNENIINQEFMQQMTAEHLIYGMHLLGVTRSNQTTSGQNGNTTDGT  1350
1351  RSFLSTTQNGGEQQPTLAKNFQSFVNSSGNSRQNLHRNNLPYLQEQIYDT  1400
1401  NQHIFKVNSIKMEMQSHPQQHCANAQNFSGQLYDQTATYPQQIMKSGSEP  1450
1451  GMEANCLLQESNNTNSSKLLSPGANHVTSTVDNIDNSLAGVQIAFAAIID  1500
1501  DGDHASLISGVLSPSIIQNLSRNSSRLTTPRASLTFPAIPVSTSNMAIGD  1550
1551  MSSLLTSLAEESKFLAIMQ                                 1569

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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