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

NucPred

Fetching P97433 from www.uniprot.org...

The NucPred score for your sequence is 0.86 (see score help below)

   1  MELSCSEVPLYGQKTVYAKFGKNVYLPEDAEFYFVYGGSHQRHVVIADRV    50
  51  QDNVLQSSIPGHWLQETVTVSVCLCSEGYSPVTMGSGSVTYVDNMACRLA   100
 101  RLLVTQADRLTACSHQTLLTPFALTVEALPALDEELVLALTQLELPLGWT   150
 151  VLGNSSLEVSLHRESLLHLAVRWALPKLFHFLLCLPGGVKALKLPNEEAT   200
 201  TPLDLALQGGHSTLVEDITNFQGSHSPGFSRLRLNEEATLQFVHSSETLT   250
 251  LTVNHTAEHLLEADIKLFRKYFWDRAFLVKALEQEAKTEKATMPSGAAET   300
 301  EEEVRNLESGRSPSEEEEDAKSIKSQVDGPSEHEDQDRLPLDRSFDGLKK   350
 351  SKHVPASLAAGQLSDVLNGGDEVYANCMVIDQVGDLDINYINLEGLSTHT   400
 401  SPESGRSMLGPQACMHTLPPDTSPCGRPLIENSEGTLDAAASQSFVTPSS   450
 451  SRTSNLNLSFGLHGFEKEQSHLKKRSSSLDALVADSEGEGGSEPPICYAV   500
 501  GSQSSPRTGLPSGDELDSFETNTEPDCNISRTESLSLSSTLHSKESLLSG   550
 551  IRSRSYSCSSPKISSGKSRLVRDFTVCSTSEEQRSYSFQEPPGEKRIQEE   600
 601  EWDEYVIPAKSESEKYKVSRTFSFLMNRMTSPRNKSKMKNKDTKEKEKMN   650
 651  RHQFVPGTFSGVLQCSGCDKTLLGKESLQCANCKANTHKGCKDAVPPCTK   700
 701  KFQEKYNKNKPQSILGSSSVRDVPAPGLSLHPSSSMPIGLPAGRKEFAAQ   750
 751  VHPLSRSVPGTTLESFRRAVTSLESEGDSWRSRSHSDELFQSMGSSPSTE   800
 801  SFMMEDVVDSSLWIDLSSDAQEFEAESWSLVVDPSFCSRQEKDVIKRQDV   850
 851  IFELMQTEVHHIQTLLIMSEVFRKGMKEELQLDHSTVDKIFPCLDELLET   900
 901  HRHFFFSMKERRQESCAGSDRNFVINQIGDILVQQFSEENASKMKRIYGE   950
 951  FCSHHKEAMSLFKELQQNKKFQNFIKIRNSNLLARRRGIPECILLVTQRI  1000
1001  TKYPVLVERILQYTKERTEEHRDLCKALGLIKDMIAAVDLKVSEYEKNQK  1050
1051  WLEILNKIENKTYTKLKNGHVFRKQALLSQERALLHDGLVYWKTATGRFK  1100
1101  DILALLLTDVLLFLQEKDQKYIFAAVDQKPSVISLQKLIAREVANEERGM  1150
1151  FLISASSAGPEMYEIHTNSKEERNNWMRRIQQAVESCPEEEGGRTSESDE  1200
1201  ERRKAEARVAKIQQCQEILSNQDQQICTYLEEKLHIYAELGELSGFEDVH  1250
1251  LEPHLLIKPDPGEPPQAASLLAAALREAESLQVAVKASKMGDVSQSSEES  1300
1301  PGGTVLMDTPSTQDVPASPTASLVTEGTEGRGCWDVDPGLQGVVTDLAVS  1350
1351  DAGEKVEYRSFSGSSQSEIIQAIQNLTRLLYSLQAALTIQDSHIEIHKLV  1400
1401  LQQRESLAPSHSFRGGPLQDQEKSRYLEKQREELANIHKLQHQFQQEQRR  1450
1451  WHRTCDQQQREQEAQESWLQARERECQSQEELLLRHRSELDHQLQEYQQS  1500
1501  LERLREGQRMVERERQKMRVQQGLLGHCKHSRQRSLPAVFSPGSKEVTEL  1550
1551  NRAESLCHENSFFINEAFGHMSLNTSNKPNPSGVPWDAHPLEGSHFDLAR  1600
1601  TSESPTELKIDISQPPDVNSELWTTGPGHQRPALQENSKESYKNVADLDS  1650
1651  FQSESSSPQDSNQRGPQPQTLTTEAKLSLPMAAGHGGDAGDGAEENILYL  1700

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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