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

NucPred

Fetching P36126 from www.uniprot.org...

The NucPred score for your sequence is 0.94 (see score help below)

   1  MSNVSTASGTHFAPPQADRSVTEEVDRVNSRPDELENQEVLRQLPENGNL    50
  51  TSSLQREKRRTPNGKEAERKHALPKSFVDRNLSDVSPNHSLDHIMHSNEH   100
 101  DPRRGSDEENMHRLYNNLHSSNNNVHSKRNSKREEERAPQRRSSSVAYTQ   150
 151  QQFNGWKKEFGHAFKKISAIGRLKSSVNSPTPAGSGHRHNQHQHQQVNEE   200
 201  DLYTQRLASDLLDSLLAGCPASLFASTQFLRDEHGKRRAPLLLAKLDVRV   250
 251  SPLKNDNNILDITNSNHNHRGNNNNNTGENSDRRPSIPRSSSIISISSNV   300
 301  AEFMYSRNENSLFRIHLEYGIDEDRLKWSIIRSYKDIKSLHHKLKIVAFQ   350
 351  QLTISKLYSDNNRYHSLQLPHFPHYKEMVKERNVMEKKAENKPSSAASAP   400
 401  HTSENNNNDNGSNITSLETLSSSEISEFNIDNVKMKHLQDLIDEPDDFSQ   450
 451  PIHLRLERYLRLLNIALCLRPHANRLFEFYELSPLGNLLSRESGFQGKQG   500
 501  YLVIRSTAKAQGWRVSHFGKHAFKDMIDRHTTKWFLVRNSYLTYVSDLSS   550
 551  TTPLDVFLIDWKFKVRFSGNKNNILDNENEINWIIHDPNLEINDELEEFG   600
 601  IENDANNILDKNGKSKTHQKKSNISSKLLLLTLENSERKLKIICKSESSL   650
 651  KQWMSSIIKMSTSTPWSKPNRFGSFAPVRTNSFCKFLVDGRDYFWSLSEA   700
 701  LLMAKDVIYIHDWWLSPELYLRRPVKGNQGFRIDRMLKSCAEKGIKIFIV   750
 751  IYRNVGNIVGTDSLWTKHSMLNLHPNIHIIRSPNQWLQNTYFWAHHEKFV   800
 801  VIDETFAFIGGTDLCYGRYDTFEHVLRDDAESLLDQNFPGKDYSNARIAD   850
 851  FHDLDKPFESMYDRKVIPRMPWHDVQMMTLGEPARDLARHFVQRWNYLLR   900
 901  AKRPSRLTPLLTPPSDLTAEELKSLPMFEILREKSTCETQILRSAGNWSL   950
 951  GLKETECSIQNAYLKLIEQSEHFIYIENQFFITSTVWNGTCVLNKIGDAL  1000
1001  VDRIVKANQEKKPWKAFILIPLMPGFDSPVDTAEASSLRLIMQFQYQSIS  1050
1051  RGEHSTFSKLKKLNIDPAQYIQFFSLRKWSTFAPNERLITEQLYVHAKIL  1100
1101  IADDRRCIIGSANINERSQLGNRDSEVAILIRDTDLIKTKMNGDDYYAGK  1150
1151  FPWELRQRLMREHLGCDVDLVEFVEKKFERFEKFAAKNYEKLHTLSKEGD  1200
1201  SGNNWSDREMIDSAMIELGYREIFGCKFSPQWKSGHGNSVDDGSTQCGIN  1250
1251  EKEVGREDENVYEKFFNSVDYGKSSRKRTPLPKHNFASLGLTFNHRAGIE  1300
1301  NVGIRDHKVLSTDPRLRKNDEHKKEVDGYGPDCWKKESNKKFKADATEQL  1350
1351  KEWALNSLASKVLDDKEMIKSEIPEGFSNYLPNEKDLEMYLTDKTVTNRN  1400
1401  KWSMLKRICYLQYLSHKLDERKTQRLKKIKDMRRHLSSSTESTRNGSNSL  1450
1451  PLNEKSNEGESTNVDQDIEGDEYHRLHEDILKNQELDDGSLDDLLSQIIP  1500
1501  KITNFNSGEIDDAKKEELLKLNFIDPYSFEDPLISSFSEGLWFTIALRNT  1550
1551  LLYKLVFHCQPDNAVQNWKEYGEFTELEQEFQINQEKLIDLEAENINSTT  1600
1601  TNVVDKDREKEKMRKAAELRMKLSGSLLYGFNQKVFDKHTAQRILERIHG  1650
1651  HLVIFPTEWLAKEVESRNWIFNSDRLSPMEIYN                   1683

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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