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

NucPred

Fetching P13568 from www.uniprot.org...

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

   1  MGKEQKEKKDGNLSIKEEVEKELNKKSTAELFRKIKNEKISFFLPFKCLP    50
  51  AQHRKLLFISFVCAVLSGGTLPFFISVFGVILKNMNLGDDINPIILSLVS   100
 101  IGLVQFILSMISSYCMDVITSKILKTLKLEYLRSVFYQDGQFHDNNPGSK   150
 151  LRSDLDFYLEQVSSGIGTKFITIFTYASSFLGLYIWSLIKNARLTLCITC   200
 201  VFPLIYVCGVICNKKVKLNKKTSLLYNNNTMSIIEEALMGIRTVASYCGE   250
 251  KTILNKFNLSETFYSKYILKANFVEALHIGLINGLILVSYAFGFWYGTRI   300
 301  IINSATNQYPNNDFNGASVISILLGVLISMFMLTIILPNITEYMKALEAT   350
 351  NSLYEIINRKPLVENNDDGETLPNIKKIEFKNVRFHYDTRKDVEIYKDLS   400
 401  FTLKEGKTYAFVGESGCGKSTILKLIERLYDPTEGDIIVNDSHNLKDINL   450
 451  KWWRSKIGVVSQDPLLFSNSIKNNIKYSLYSLKDLEAMENYYEENTNDTY   500
 501  ENKNFSLISNSMTSNELLEMKKEYQTIKDSDVVDVSKKVLIHDFVSSLPD   550
 551  KYDTLVGSNASKLSGGQKQRISIARAIMRNPKILILDEATSSLDNKSEYL   600
 601  VQKTINNLKGNENRITIIIAHRLSTIRYANTIFVLSNRERSDNNNNNNND   650
 651  DNNNNNNNNNNKINNEGSYIIEQGTHDSLMKNKNGIYHLMINNQKISSNK   700
 701  SSNNGNDNGSDNKSSAYKDSDTGNDADNMNSLSIHENENISNNRNCKNTA   750
 751  ENEKEEKVPFFKRMFRRKKKAPNNLRIIYKEIFSYKKDVTIIFFSILVAG   800
 801  GLYPVFALLYARYVSTLFDFANLEYNSNKYSIYILLIAIAMFISETLKNY   850
 851  YNNKIGEKVEKTMKRRLFENILYQEMSFFDQDKNTPGVLSAHINRDVHLL   900
 901  KTGLVNNIVIFSHFIMLFLVSMVMSFYFCPIVAAVLTFIYFINMRVFAVR   950
 951  ARLTKSKEIEKKENMSSGVFAFSSDDEMFKDPSFLIQEAFYNMHTVINYG  1000
1001  LEDYFCNLIEKAIDYKNKGQKRRIIVNAALWGFSQSAQLFINSFAYWFGS  1050
1051  FLIKRGTILVDDFMKSLFTFIFTGSYAGKLMSLKGDSENAKLSFEKYYPL  1100
1101  MIRKSNIDVRDDGGIRINKNLIKGKVDIKDVNFRYISRPNVPIYKNLSFT  1150
1151  CDSKKTTAIVGETGSGKSTFMNLLLRFYDLKNDHIILKNDMTNFQDYQNN  1200
1201  NNNSLVLKNVNEFSNQSGSAEDYTVFNNNGEILLDDINICDYNLRDLRNL  1250
1251  FSIVSQEPMLFNMSIYENIKFGREDATLEDVKRVSKFAAIDEFIESLPNK  1300
1301  YDTNVGPYGKSLSGGQKQRIAIARALLREPKILLLDEATSSLDSNSEKLI  1350
1351  EKTIVDIKDKADKTIITIAHRIASIKRSDKIVVFNNPDRNGTFVQSHGTH  1400
1401  DELLSAQDGIYKKYVKLAK                                 1419

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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