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

NucPred

Fetching O54991 from www.uniprot.org...

The NucPred score for your sequence is 0.19 (see score help below)

   1  MMSLRLFSILLATVVSGAWGWGYYGCNEELVGPLYARSLGASSYYGLFTT    50
  51  ARFARLHGISGWSPRIGDPNPWLQIDLMKKHRIRAVATQGAFNSWDWVTR   100
 101  YMLLYGDRVDSWTPFYQKGHNATFFGNVNDSAVVRHDLHYHFTARYIRIV   150
 151  PLAWNPRGKIGLRLGIYGCPYTSSILYFDGDDAISYRFQRGASQSLWDVF   200
 201  AFSFKTEEKDGLLLHTEGSQGDYVTLELQGAHLLLHMSLGSSPIQPRPGH   250
 251  TTVSLGGVLNDLSWHYVRVDRYGRDANFTLDGYAHHFVLNGDFERLNLEN   300
 301  EIFIGGLVGAARKNLAYRHNFRGCIENVIYNRINIAEMAVMRHSRITFEG   350
 351  NVAFRCLDPVPHPINFGGPHNFVQVPGFPRRGRLAVSFRFRTWDLTGLLL   400
 401  FSHLGDGLGHVELMLSEGQVNVSIAQTGRKKLQFAAGYRLNDGFWHEVNF   450
 451  VAQENHAVISIDDVEGAEVRVSYPLLIRTGTSYFFGGCPKPASRWGCHSN   500
 501  QTAFHGCMELLKVDGQLVNLTLVEFRKLGYFAEVLFDTCGITDRCSPNMC   550
 551  EHDGRCYQSWDDFICYCELTGYKGVTCHEPLYKESCEAYRLSGKYSGNYT   600
 601  IDPDGSGPLKPFVVYCDIRENRAWTVVRHDRLWTTRVTGSSMDRPFLGAI   650
 651  QYWNASWEEVSALANASQHCEQWIEFSCYNSRLLNTAGGYPYSFWIGRNE   700
 701  EQHFYWGGSQPGIQRCACGLDQSCVDPALHCNCDADQPQWRTDKGLLTFV   750
 751  DHLPVTQVVVGDTNRSNSEAQFFLRPLRCYGDRNSWNTISFHTGAALRFP   800
 801  PIRANHSLDVSFYFRTSAPSGVFLENMGGPFCRWRRPYVRVELNTSRDVV   850
 851  FAFDIGNGDENLTVHSDDFEFNDDEWHLVRAEINVKQARLRVDHRPWVLR   900
 901  PMPLQTYIWLVYDQPLYVGSAELKRRPFVGCLRAMRLNGVTLNLEGRANA   950
 951  SEGTFPNCTGHCTHPRFPCFHGGRCVERYSYYTCDCDLTAFDGPYCNHDI  1000
1001  GGFFETGTWMRYNLQSALRSAAREFSHMLSRPVPGYEPGYVPGYDTPGYV  1050
1051  PGYHGPGYRLPEYPRPGRPVPGYRGPVYNVTGEEVSFSFSTNSAPAVLLY  1100
1101  VSSFVRDYMAVLIKEDGTLQLRYQLGTSPYVYQLTTRPVTDGQPHSVNIT  1150
1151  RVYRNLFIQVDYFPLTEQKFSLLVDSQLDSPKALYLGRVMETGVIDPEIQ  1200
1201  RYNTPGFSGCLSGVRFNNVAPLKTHFRTPRPMTAELAEAMRVQGELSESN  1250
1251  CGAMPRLVSEVPPELDPWYLPPDFPYYHDDGWIAILLGFLVAFLLLGLVG  1300
1301  MLVLFYLQNHRYKGSYHTNEPKATHDSHPGGKAPLPPSGPAQAPAPTPAP  1350
1351  TQLPTPAPAPAPAPASGPGPRDQNLPQILEESRSE                 1385

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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