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

NucPred

Fetching O88917 from www.uniprot.org...

The NucPred score for your sequence is 0.22 (see score help below)

   1  MARLAAALWSLCVTTVLVTSATQGLSRAGLPFGLMRRELACEGYPIELRC    50
  51  PGSDVIMVENANYGRTDDKICDADPFQMENVQCYLPDAFKIMSQRCNNRT   100
 101  QCVVVAGSDAFPDPCPGTYKYLEVQYDCVPYKVEQKVFVCPGTLQKVLEP   150
 151  TSTHESEHQSGAWCKDPLQAGDRIYVMPWIPYRTDTLTEYASWEDYVAAR   200
 201  HTTTYRLPNRVDGTGFVVYDGAVFYNKERTRNIVKYDLRTRIKSGETVIN   250
 251  TANYHDTSPYRWGGKTDIDLAVDENGLWVIYATEGNNGRLVVSQLNPYTL   300
 301  RFEGTWETGYDKRSASNAFMVCGVLYVLRSVYVDDDSEAAGNRVDYAFNT   350
 351  NANREEPVSLAFPNPYQFVSSVDYNPRDNQLYVWNNYFVVRYSLEFGPPD   400
 401  PSAGPATSPPLSTTTTARPTPLTSTASPAATTPLRRAPLTTHPVGAINQL   450
 451  GPDLPPATAPAPSTRRPPAPNLHVSPELFCEPREVRRVQWPATQQGMLVE   500
 501  RPCPKGTRGIASFQCLPALGLWNPRGPDLSNCTSPWVNQVAQKIKSGENA   550
 551  ANIASELARHTRGSIYAGDVSSSVKLMEQLLDILDAQLQALRPIERESAG   600
 601  KNYNKMHKRERTCKDYIKAVVETVDNLLRPEALESWKDMNATEQVHTATM   650
 651  LLDVLEEGAFLLADNVREPARFLAAKQNVVLEVTVLSTEGQVQELVFPQE   700
 701  YASESSIQLSANTIKQNSRNGVVKVVFILYNNLGLFLSTENATVKLAGEA   750
 751  GTGGPGGASLVVNSQVIAASINKESSRVFLMDPVIFTVAHLEAKNHFNAN   800
 801  CSFWNYSERSMLGYWSTQGCRLVESNKTHTTCACSHLTNFAVLMAHREIY   850
 851  QGRINELLLSVITWVGIVISLVCLAICISTFCFLRGLQTDRNTIHKNLCI   900
 901  NLFLAELLFLVGIDKTQYEVACPIFAGLLHYFFLAAFSWLCLEGVHLYLL   950
 951  LVEVFESEYSRTKYYYLGGYCFPALVVGIAAAIDYRSYGTEKACWLRVDN  1000
1001  YFIWSFIGPVSFVIVVNLVFLMVTLHKMIRSSSVLKPDSSRLDNIKSWAL  1050
1051  GAIALLFLLGLTWAFGLLFINKESVVMAYLFTTFNAFQGVFIFVFHCALQ  1100
1101  KKVHKEYSKCLRHSYCCIRSPPGGAHGSLKTSAMRSNTRYYTGTQVPGQG  1150
1151  RHIHQVSLGPRGRSALPESQKDPGGQSGPGDPLTFGLCPSRIRRMWNDTV  1200
1201  RKQTESSFMAGDINSTPTLNRGTMGNHLLTNPVLQPRGGTSPYNTLIAES  1250
1251  VGFNPSSPPVFNSPGSYREPKHPLGGREACGMDTLPLNGNFNNSYSLRSG  1300
1301  DFPPGDGGPEPPRGRNLADAAAFEKMIISELVHNNLRGASGGAKGPPPEP  1350
1351  PVPPVPGVSEDEAGGPGGADRAEIELLYKALEEPLLLPRAQSVLYQSDLD  1400
1401  ESESCTAEDGATSRPLSSPPGRDSLYASGANLRDSPSYPDSSPEGPNEAL  1450
1451  PPPPPAPPGPPEIYYTSRPPALVARNPLQGYYQVRRPSHEGYLAAPSLEG  1500
1501  PGPDGDGQMQLVTSL                                     1515

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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