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

NucPred

Fetching Q875X4 from www.uniprot.org...

The NucPred score for your sequence is 0.82 (see score help below)

   1  MSFEVGTRCWYPNSEAGWIGCEVTKNDFQDGTYHIELTSETGLVIPIETK    50
  51  HLESNNAMENNHEFLPVLRNPPILEATHDLTTLSYLNEPAVLHAIKERYN   100
 101  QRNIYTYSGIVLIATNPFDKVEELYSSEMIQAYARKNRDEMAPHIFAIAE   150
 151  EAYREMINNDQNQTIIVSGESGAGKTVSAKYIMRFFASVEEEHFNKEGDS   200
 201  KHQEEMSDIEVKILATNPVMEAFGNAKTTRNDNSSRFGKYLQILFDSNKN   250
 251  IIGSSIKTYLLERSRLVFQPTSERNYHIFYQMLSGLSSDMKKQLYLTNAE   300
 301  DFFYLNQGGESTINGIDDSLEYSTTIESLSTVGIDTEVQLQIFKILAALL   350
 351  HIGNIEIKKTRTDATLSSTDPSLQKACELLGLDPLTFSKWITKKQINTRS   400
 401  EKIISNLSFNQALVARDSVAKFIYSSLFDWLVGNINNVLCTSQVSETINS   450
 451  FIGVLDIYGFEHFEQNSFEQFCINYANEKLQQEFNHHVFKLEQEEYVKEE   500
 501  IEWSFIEFSDNQPCIDLIENKLGILSLLDEESRLPAGSDESWTTKLYQTF   550
 551  NKPPSNTVFGKPRFGQNKFIISHYAVDVTYEVDGFIEKNKDTISESQLEV   600
 601  LKATTNPTLATIFEFSEAENKTNITEQAGTIQRKTINRKPTLGSIFKRSL   650
 651  VELMETINSTNVHYIRCIKPNTEKEAWKFDNLMVLSQLRACGVLETIKIS   700
 701  CAGFPSRWAFEEFIQRYYLLAPTDQWGRVTADMEMSLEDMVAFCDLILSE   750
 751  KIDSKDKYQIGKTKIFFKAGVLAYLEKIRSDKVTELAVLIQKHIRAKYYR   800
 801  SLYLQAMLSIKNCQSLIRGVQSRQRVDFEMKTDAATLLQTLHRSTRVRSQ   850
 851  VFETLKNILEVQTAIRRVLVSNFIQREFESRSAIMIQSKIRANSPKHRYQ   900
 901  TLKTGTILIQALVRRKQSQEKLKQLKIQAESAASLKNSAAGIQKELIGFI   950
 951  EELISNIKENDAKTTEYKSLLKHTSLPVVTGTNERTAAYISTKNQVEEDK  1000
1001  VTIRTILTKYETLKDLCRKELKSLESLEKGVNDEKFASSLQSSLELIKRD  1050
1051  ISDLRINAIEKDNERTSTSSELKDGTDCTDNAVVQILTKRQGDLINDLVN  1100
1101  VVFLEFQIPQRGRTKDCEHFYPVKLLISIVNLMNKFGLRKSSHSILKQTV  1150
1151  QDLIGKISSMDAKKCVTFGLYWIISLHKLSSLPQEPAVLNKLQDKFYKTW  1200
1201  LKQCFNQMKTVDSILILFDTISEFTLFFQGTTELLTNIITALLQHINAKW  1250
1251  FNDLLIKQNTLSWTHGLEKDSEIKKVLDWCNSHKIRNSTEYLRNVNQACK  1300
1301  LLQLRISNISDFQLVCEFCYDLSSLQMHALLTKYRPTQFEKPIPVDVLNH  1350
1351  LSNTARRERTTMKRELTLDAGTETYSVENLFQGHPIEASDEHDDINQLIN  1400
1401  QLPSDKDFPVIKELGSLLA                                 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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