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

NucPred

Fetching P22219 from www.uniprot.org...

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

   1  MGAQLSLVVQASPSIAIFSYIDVLEEVHYVSQLNSSRFLKTCKALDPNGE    50
  51  IVIKVFIKPKDQYSLRPFLQRIRAQSFKLGQLPHVLNYSKLIETNRAGYM   100
 101  IRQHLKNNLYDRLSLRPYLQDIELKFIAFQLLNALKDIHNLNIVHGDIKT   150
 151  ENILVTSWNWCILTDFAAFIKPVYLPEDNPGEFLFYFDTSKRRTCYLAPE   200
 201  RFNSKLYQDGKSNNGRLTKEMDIFSLGCVIAEIFAEGRPIFNLSQLFKYK   250
 251  SNSYDVNREFLMEEMNSTDLRNLVLDMIQLDPSKRLSCDELLNKYRGIFF   300
 301  PDYFYTFIYDYFRNLVTMTTSTPISDNTCTNSTLEDNVKLLDETTEKIYR   350
 351  DFSQICHCLDFPLIKDGGEIGSDPPILESYKIEIEISRFLNTNLYFPQNY   400
 401  HLVLQQFTKVSEKIKSVKEECALLFISYLSHSIRSIVSTATKLKNLELLA   450
 451  VFAQFVSDENKIDRVVPYFVCCFEDSDQDVQALSLLTLIQVLTSVRKLNQ   500
 501  LNENIFVDYLLPRLKRLLISNRQNTNYLRIVFANCLSDLAIIINRFQEFT   550
 551  FAQHCNDNSMDNNTEIMESSTKYSAKLIQSVEDLTVSFLTDNDTYVKMAL   600
 601  LQNILPLCKFFGRERTNDIILSHLITYLNDKDPALRVSLIQTISGISILL   650
 651  GTVTLEQYILPLLIQTITDSEELVVISVLQSLKSLFKTGLIRKKYYIDIS   700
 701  KTTSPLLLHPNNWIRQFTLMIIIEIINKLSKAEVYCILYPIIRPFFEFDV   750
 751  EFNFKSMISCCKQPVSRSVYNLLCSWSVRASKSLFWKKIITNHVDSFGNN   800
 801  RIEFITKNYSSKNYGFNKRDTKSSSSLKGIKTSSTVYSHDNKEIPLTAED   850
 851  RNWIDKFHIIGLTEKDIWKIVALRGYVIRTARVMAANPDFPYNNSNYRPL   900
 901  VQNSPPNLNLTNIMPRNIFFDVEFAEESTSEGQDSNLENQQIYKYDESEK   950
 951  DSNKLNINGSKQLSTVMDINGSLIFKNKSIATTTSNLKNVFVQLEPTSYH  1000
1001  MHSPNHGLKDNANVKPERKVVVSNSYEGDVESIEKFLSTFKILPPLRDYK  1050
1051  EFGPIQEIVRSPNMGNLRGKLIATLMENEPNSITSSAVSPGETPYLITGS  1100
1101  DQGVIKIWNLKEIIVGEVYSSSLTYDCSSTVTQITMIPNFDAFAVSSKDG  1150
1151  QIIVLKVNHYQQESEVKFLNCECIRKINLKNFGKNEYAVRMRAFVNEEKS  1200
1201  LLVALTNLSRVIIFDIRTLERLQIIENSPRHGAVSSICIDEECCVLILGT  1250
1251  TRGIIDIWDIRFNVLIRSWSFGDHAPITHVEVCQFYGKNSVIVVGGSSKT  1300
1301  FLTIWNFVKGHCQYAFINSDEQPSMEHFLPIEKGLEELNFCGIRSLNALS  1350
1351  TISVSNDKILLTDEATSSIVMFSLNELSSSKAVISPSRFSDVFIPTQVTA  1400
1401  NLTMLLRKMKRTSTHSVDDSLYHHDIINSISTCEVDETPLLVACDNSGLI  1450
1451  GIFQ                                                1454

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.)

Go back to the NucPred Home Page.