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

NucPred

Fetching O15027 from www.uniprot.org...

The NucPred score for your sequence is 0.79 (see score help below)

   1  MQPPPQTVPSGMAGPPPAGNPRSVFWASSPYRRRANNNAAVAPTTCPLQP    50
  51  VTDPFAFSRQALQSTPLGSSSKSSPPVLQGPAPAGFSQHPGLLVPHTHAR   100
 101  DSSQGPCEPLPGPLTQPRAHASPFSGALTPSAPPGPEMNRSAEVGPSSEP   150
 151  EVQTLPYLPHYIPGVDPETSHGGHPHGNMPGLDRPLSRQNPHDGVVTPAA   200
 201  SPSLPQPGLQMPGQWGPVQGGPQPSGQHRSPCPEGPVPSGVPCATSVPHF   250
 251  PTPSILHQGPGHEQHSPLVAPPAALPSDGRDEVSHLQSGSHLANNSDPES   300
 301  TFRQNPRIVNHWASPELRQNPGVKNEHRPASALVNPLARGDSPENRTHHP   350
 351  LGAGAGSGCAPLEADSGASGALAMFFQGGETENEENLSSEKAGLSGQADF   400
 401  DDFCSSPGLGRPPAPTHVGAGSLCQALLPGPSNEAAGDVWGDTASTGVPD   450
 451  ASGSQYENVENLEFVQNQEVLPSEPLNLDPSSPSDQFRYGPLPGPAVPRH   500
 501  GAVCHTGAPDATLHTVHPDSVSSSYSSRSHGRLSGSARPQELVGTFIQQE   550
 551  VGKPEDEASGSFFKQIDSSPVGGETDETTVSQNYRGSVSQPSTPSPPKPT   600
 601  GIFQTSANSSFEPVKSHLVGVKPFEADRANVVGEVRETCVRQKQCRPAAA   650
 651  LPDASPGNLEQPPDNMETLCAPQVCPLPLNSTTEAVHMLPHAGAPPLDTV   700
 701  YPAPEKRPSARTQGPVKCESPATTLWAQSELPDFGGNVLLAPAAPALYVC   750
 751  AKPQPPVVQPPEEAMSGQQSRNPSSAAPVQSRGGIGASENLENPPKMGEE   800
 801  EALQSQASSGYASLLSSPPTESLQNPPVLIAQPDHSYNLAQPINFSVSLS   850
 851  NSHEKNQSWREALVGDRPAVSSWALGGDSGENTSLSGIPTSSVLSLSLPS   900
 901  SVAQSNFPQGSGASEMVSNQPANLLVQPPSQPVPENLVPESQKDRKAGSA   950
 951  LPGFANSPAGSTSVVLVPPAHGTLVPDGNKANHSSHQEDTYGALDFTLSR  1000
1001  TLENPVNVYNPSHSDSLASQQSVASHPRQSGPGAPNLDRFYQQVTKDAQG  1050
1051  QPGLERAQQELVPPQQQASPPQLPKAMFSELSNPESLPAQGQAQNSAQSP  1100
1101  ASLVLVDAGQQLPPRPPQSSSVSLVSSGSGQAAVPSEQPWPQPVPALAPG  1150
1151  PPPQDLAAYYYYRPLYDAYQPQYSLPYPPEPGAASLYYQDVYSLYEPRYR  1200
1201  PYDGAASAYAQNYRYPEPERPSSRASHSSERPPPRQGYPEGYYSSKSGWS  1250
1251  SQSDYYASYYSSQYDYGDPGHWDRYHYSARVRDPRTYDRRYWCDAEYDAY  1300
1301  RREHSAFGDRPEKRDNNWRYDPRFTGSFDDDPDPHRDPYGEEVDRRSVHS  1350
1351  EHSARSLHSAHSLASRRSSLSSHSHQSQIYRSHNVAAGSYEAPLPPGSFH  1400
1401  GDFAYGTYRSNFSSGPGFPEYGYPADTVWPAMEQVSSRPTSPEKFSVPHV  1450
1451  CARFGPGGQLIKVIPNLPSEGQPALVEVHSMEALLQHTSEQEEMRAFPGP  1500
1501  LAKDDTHKVDVINFAQNKAMKCLQNENLIDKESASLLWNFIVLLCRQNGT  1550
1551  VVGTDIAELLLRDHRTVWLPGKSPNEANLIDFTNEAVEQVEEEESGEAQL  1600
1601  SFLTGGPAAAASSLERETERFRELLLYGRKKDALESAMKNGLWGHALLLA  1650
1651  SKMDSRTHARVMTRFANSLPINDPLQTVYQLMSGRMPAASTCCGDEKWGD  1700
1701  WRPHLAMVLSNLNNNMDVESRTMATMGDTLASRGLLDAAHFCYLMAQAGF  1750
1751  GVYTKKTTKLVLIGSNHSLPFLKFATNEAIQRTEAYEYAQSLGAETCPLP  1800
1801  SFQVFKFIYSCRLAEMGLATQAFHYCEAIAKSILTQPHLYSPVLISQLVQ  1850
1851  MASQLRLFDPQLKEKPEEESLAAPTWLVHLQQVERQIKEGAGVWHQDGAL  1900
1901  PQQCPGTPSSEMEQLDRPGLSQPGALGIANPLLAVPAPSPEHSSPSVRLL  1950
1951  PSAPQTLPDGPLASPARVPMFPVPLPPGPLEPGPGCVTPGPALGFLEPSG  2000
2001  PGLPPGVPPLQERRHLLQEARSPDPGIVPQEAPVGNSLSELSEENFDGKF  2050
2051  ANLTPSRTVPDSEAPPGWDRADSGPTQPPLSLSPAPETKRPGQAAKKETK  2100
2101  EPKKGESWFFRWLPGKKKTEAYLPDDKNKSIVWDEKKNQWVNLNEPEEEK  2150
2151  KAPPPPPTSMPKTVQAAPPALPGPPGAPVNMYSRRAAGTRARYVDVLNPS  2200
2201  GTQRSEPALAPADFVAPLAPLPIPSNLFVPTPDAEEPQLPDGTGREGPAA  2250
2251  ARGLANPEPAPEPKVLSSAASLPGSELPSSRPEGSQGGELSRCSSMSSLS  2300
2301  REVSQHFNQAPGDLPAAGGPPSGAMPFYNPAQLAQACATSGSSRLGRIGQ  2350
2351  RKHLVLN                                             2357

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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