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

NucPred

Fetching P97793 from www.uniprot.org...

The NucPred score for your sequence is 0.43 (see score help below)

   1  MGAAGFLWLLPPLLLAAASYSGAATDQRAGSPASGPPLQPREPLSYSRLQ    50
  51  RKSLAVDFVVPSLFRVYARDLLLPQPRSPSEPEAGGLEARGSLALDCEPL   100
 101  LRLLGPLPGISWADGASSPSPEAGPTLSRVLKGGSVRKLRRAKQLVLELG   150
 151  EETILEGCIGPPEEVAAVGILQFNLSELFSWWILHGEGRLRIRLMPEKKA   200
 201  SEVGREGRLSSAIRASQPRLLFQIFGTGHSSMESPSETPSPPGTFMWNLT   250
 251  WTMKDSFPFLSHRSRYGLECSFDFPCELEYSPPLHNHGNQSWSWRHVPSE   300
 301  EASRMNLLDGPEAEHSQEMPRGSFLLLNTSADSKHTILSPWMRSSSDHCT   350
 351  LAVSVHRHLQPSGRYVAQLLPHNEAGREILLVPTPGKHGWTVLQGRVGRP   400
 401  ANPFRVALEYISSGNRSLSAVDFFALKNCSEGTSPGSKMALQSSFTCWNG   450
 451  TVLQLGQACDFHQDCAQGEDEGQLCSKLPAGFYCNFENGFCGWTQSPLSP   500
 501  HMPRWQVRTLRDAHSQGHQGRALLLSTTDILASEGATVTSATFPAPMKNS   550
 551  PCELRMSWLIRGVLRGNVSLVLVENKTGKEQSRTVWHVATDEGLSLWQHT   600
 601  VLSLLDVTDRFWLQIVTWWGPGSRATVGFDNISISLDCYLTISGEEKMSL   650
 651  NSVPKSRNLFEKNPNKESKSWANISGPTPIFDPTVHWLFTTCGASGPHGP   700
 701  TQAQCNNAYQNSNLSVVVGSEGPLKGVQIWKVPATDTYSISGYGAAGGKG   750
 751  GKNTMMRSHGVSVLGIFNLEKGDTLYILVGQQGEDACPRANQLIQKVCVG   800
 801  ENNVIEEEIRVNRSVHEWAGGGGGGGGATYVFKMKDGVPVPLIIAAGGGG   850
 851  RAYGAKTETFHPERLESNSSVLGLNGNSGAAGGGGGWNDNTSLLWAGKSL   900
 901  LEGAAGGHSCPQAMKKWGWETRGGFGGGGGGCSSGGGGGGYIGGNAASNN   950
 951  DPEMDGEDGVSFISPLGILYTPALKVMEGHGEVNIKHYLNCSHCEVDECH  1000
1001  MDPESHKVICFCDHGTVLADDGVSCIVSPTPEPHLPLSLILSVVTSALVA  1050
1051  ALVLAFSGIMIVYRRKHQELQAMQMELQSPEYKLSKLRTSTIMTDYNPNY  1100
1101  CFAGKTSSISDLKEVPRKNITLIRGLGHGAFGEVYEGQVSGMPNDPSPLQ  1150
1151  VAVKTLPEVCSEQDELDFLMEALIISKFNHQNIVRCIGVSLQALPRFILL  1200
1201  ELMAGGDLKSFLRETRPRPNQPTSLAMLDLLHVARDIACGCQYLEENHFI  1250
1251  HRDIAARNCLLTCPGAGRIAKIGDFGMARDIYRASYYRKGGCAMLPVKWM  1300
1301  PPEAFMEGIFTSKTDTWSFGVLLWEIFSLGYMPYPSKSNQEVLEFVTSGG  1350
1351  RMDPPKNCPGPVYRIMTQCWQHQPEDRPNFAIILERIEYCTQDPDVINTA  1400
1401  LPIEYGPVVEEEEKVPMRPKDPEGMPPLLVSPQPAKHEEASAAPQPAALT  1450
1451  APGPSVKKPPGAGAGAGAGAGAGPVPRGAADRGHVNMAFSQPNPPPELHK  1500
1501  GPGSRNKPTSLWNPTYGSWFTEKPAKKTHPPPGAEPQARAGAAEGGWTGP  1550
1551  GAGPRRAEAALLLEPSALSATMKEVPLFRLRHFPCGNVNYGYQQQGLPLE  1600
1601  ATAAPGDTMLKSKNKVTQPGP                               1621

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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