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

NucPred

Fetching Q60PC0 from www.uniprot.org...

The NucPred score for your sequence is 0.96 (see score help below)

   1  MLGASSSEEEDDDFQDDHESQLPIAQVKKRSLLSGAMTPRSSSPAPSDSV    50
  51  SQTNSLKRNNSSSQARRKDSVHSQTPARSPMKMNSPSPMPQARTMSNVTR   100
 101  PVLQNSQELDGEEIEETEGSGTMVASDDGGPSLSKEEQERIKAEKEEEEH   150
 151  KKNLQMYVFIARCVAYPFNGQQTGDMARRQMKVNKPELARIRERFAQFLR   200
 201  GETNIAADEAFTKAIQSYTEVFLKSERVQKVVHAGGFSQHDFREVFRLII   250
 251  EKRVRSLPDIEGLSKDTVLNSWLAKFDAIIKGDETDQNRNARGRSRNPNS   300
 301  AMSADAVLGKEQLYDVFQQILGVKKFEHQIIFNSLQLDNPDEQAAAIRRE   350
 351  FATREEALKDPMKMKRLTPKFVVKDMETLYMDEVRMSINTLIGNLETVPV   400
 401  TTRGQTVGKRKDKSRSRSIEDLSLFNSLKRRTSSGSLNKGDSDDGDVTLT   450
 451  KSDVSLALSMEVVVMEVQGLKSIQPNKIVYCVMDVDGHKLATDHAEASKP   500
 501  KWDTQGDFTTKTPLPTVKVKLYTEVKSLVSFDDKELGKIMITPTPNCSRN   550
 551  PEWYTMTLPKNSQDSSLKIRIAIRIEKPPNLKYSGHCWCIGRNSWKKWKK   600
 601  RFFCLVQVSQYAFAVCSFREKKADPTEFIQLDGFTIDYMPESDPELSAQG   650
 651  GKHFFTAIKEGDELKFATDDENERHLWVQALYRATGQAYKPVPPKQSTIA   700
 701  PKAQGFQDKASKHGMDALIQADSINFDHDHLYSDIQRLTLDFRINEPICS   750
 751  LGWFSPGQAFVLEEYSARYMVRGCFRHVTLLSNLLDKADDGLLIDPALIH   800
 801  YSFAFCASHVHGNRCMPDRQGPEGVGTVTLEEKEKFQEIKERLRVLLEKQ   850
 851  ITNFRYCFPFGRPEGALKGTLGLLERVLMKDVVSPVPPEEVRAVIRKCLE   900
 901  DAALVNYTRICNEAKIEQRMGNDVSPAQRIEDMIRVTEFCIDLLKENEEH   950
 951  HGEAFSWFSDLLSDHSEIFWSLYSVDLDSALEVQPHDSWDSFPLFQMLND  1000
1001  FLLSEPNLKGGIFHNKLVQQFQPLVVRYIDLMEHSIAQAIDKGFLKEKWE  1050
1051  SRKEGCATSEDIYWKMDALHTFVIDLNWPEEDFRKYLQTKMKTLTSDLIS  1100
1101  KVSDCTFTAFDSWMQKAKKSTDYMLPSEVCVQINVMFSSKSRAVRVTVDS  1150
1151  GEYKYQSKLDETLETMLKTMESCIQEKLLGVLESVLSRLARYDEGNPIGA  1200
1201  ILNIAPKPASIFNKLKTMAGDTSVQSSSSTRQPLTAQQSSGQIGNSYVTF  1250
1251  FHGCTELLRQVIIDEIWVNGLFEHWYDNQMKAINDWLTERLQQSLSATQF  1300
1301  ISLSNIVKKVYQDFAMQGIDEERLNSKTYQSISRRLQLEESNSHIQEGIR  1350
1351  RLKT                                                1354

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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