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

NucPred

Fetching Q28833 from www.uniprot.org...

The NucPred score for your sequence is 0.54 (see score help below)

   1  DGCSCPEGQLLDDGRCVESAECSCVHSGKRYPPGASLSRDCNTCICRNSL    50
  51  WVCSNEDCPGECLVTGQSHFKSFDNRHFTFSGVCQYLLARDCQDHTFSVI   100
 101  IETVQCADDPDAVCTRSVTVRLPSPHNSLVKLKHGGGVAMDGWDVQIPFL   150
 151  QGDLRIQHTVMASVHLSYGEDLQIDWDGRGRLLVKLSPVYAGRTCGLCGN   200
 201  YNGNQGDDFLTPAGLVEPLVEHFGNAWKLHGDCEDLRKQPTDPCSFNPRL   250
 251  TRFAEEACAILTSPKFQACHDAVGPLPYLQNCHYDVCSCSDGRDCLCDAV   300
 301  ATYAAACARRGVHIGWREPGFCALSCPPGQVYLQCGTPCNLTCRSLSYPD   350
 351  EECAEDCLEGCFCPPGLYLDGSGDCVPKAQCPCYHDGEIFQPEDIFSDHH   400
 401  TMCYCEDGFMHCSRAGAPGSLQPEVVLSSPLSHRSKRSLSCRPPMVKLVC   450
 451  PADNPRAEGLECAKTCQNYDLECVSTGCVSGCLCPPGMVRHENRCVALQR   500
 501  CPCFHQGREYAPGETVKVDCNTCVCRDRKWSCTDHVCDASCSALGLAHYL   550
 551  TFDGLKYLFPGECQYVLVQDYCGSNPGTFRILLGNEGCGYPSLKCRKRVT   600
 601  ILVDGGEIELFDGEVMVKKPLKDETHFEVVESGRFITVLLGSGLSVVWDR   650
 651  HLGISVFLKQTYQEQVCGLCGNFDGVQNNDLTGSSLQVEEDPVDFGNSWK   700
 701  VSPQCADTRKVPLDTSPATCHNNVMKQTMVDSSCRILTSDIFQDCNKLVD   750
 751  PEPYLDVCIYDTCSCESIGDCACFCDTIAAYARVCAQHGKVVTWRTATLC   800
 801  PQNCEERNLREDGYQCEWRYNSCAPACPVTCQHPEPLACPVSCVEGCHAH   850
 851  CPPGKILDELLQTCVSPEDCPVCEAAGRRLAPGKKIILNPRDPAHCQICH   900
 901  CDGVNLTCEACAEPVPPTEGPVSPTTPYEEDTPEPPLHDFFCSKLLDLVF   950
 951  LLDGSDKLSEADFEALKVFVVGMMEHLHISQKHIRVAVVEYHDGPHAYIS  1000
1001  LQDRKRPSELRRIASQVKYAGSEVASISEVLKYTLFQIFGRVDRPEASRI  1050
1051  ALLLMASQEPRRLAQNLARYLQGLKKKKVTVIPVGIGPHVSLKQIRLIEK  1100
1101  QAPENKAFVVSGVDELEQRKNEIISYLCDLAPEVPAPTRRPLVAQVTVAP  1150
1151  ELPGVSTLEPKKRMALDVVFVLEGSDKVGEANFNRSTEFVEEVIRRMDVG  1200
1201  RDSVHVTVLQYSYVVAVEHSFREAQSKGEVLQRVREIRFQGGNRTNTGLA  1250
1251  LQYLSEHSFSASQGDREEAPNLVYMVTGNPASDEIKRMPGDIQVVPIGVG  1300
1301  PDVDMQELERLSWPNAPIFIQDFETLPREAPDLVLQRCCSGEGPHLPTQA  1350
1351  PVPDCSQPLGVVLLLDGSSSLPASYFDEMKSFTKAFISKANIGPQLTQVS  1400
1401  VLQYGSITTIDLPWNMPLEKAHLRGLVDLMQREGGPSQIGDALGFAVRYV  1450
1451  MSQVHGARPEASKAVVIVVTDTSTDSVDAAAAAARSNRVAVFPIGIGDRY  1500
1501  DEAQLRTLAGPGASSNVVKLQRIEDLPTLVTLGNSFLHKLCSGFVRVCID  1550
1551  EDGSERKPGDVWTLPDQCHTVTCLPDGQTLLKSHRVNCDQGLQPSCPSNQ  1600
1601  PPIRVEEACGCRWTCPCVCTGSSTRHIVTFDGQNFKLMGNCSYVLFHNKE  1650
1651  QDLEVILHNGACGAGARQACMKSIEVKHNGLSVELHRDMEVVVNGRQVSV  1700
1701  PYVGGNMEVGIYGTIMYEVRFNHLGHILTFTPQNNEFQLQLSPKTFASKM  1750
1751  YGLCGICDENGANDFMLRDGTVTTDWKTMVQEWAVQQPGQMCQPVPKEQC  1800
1801  PVSGGYQCQVLLSALFAECHKVLAPAAYFAICQQDSCHQEQVCEAVASYA  1850
1851  HLCRTKGVCVDWRTPDFCAVSCPPSLVYNHCEHGCPRHCEGNSSSCGDHP  1900
1901  SEGCFCPPHQVMLGSSCVPEEACTQCVDDDGIRHQFLETWVPDHQPCQIC  1950
1951  TCLSGRRVNCTLQPCPTARAPACGLCEVARLRQEAHQCCPEYECVCDLVS  2000
2001  CDLPPVPHCEGGLQPTLTNPGECRPNFTCACRKEECPRGPLPSCPPHRTP  2050
2051  ALRKTQCCDEYECACNCVNTTLSCPLGYLASTVTNDCGCTTTTCLPDKVC  2100
2101  VHRGTVYPVGQFWEEGCDVCTCTDLEDAVMGLRVAQCAQKPCEDSCRPGF  2150
2151  TYVLHEGECCGKCLPSACKVVIGSFRGDSVSYWKSVGSHWASPENPCLIN  2200
2201  ECVRVKEEVFVQQRNVSCPMLDVPTCPVGFQLSCKTSGCCPTCRCEPVEA  2250
2251  CLLNGTIIGAGESLMIDVCTTCRCMLQEGVVFGFKLECKKTTCEACPLGY  2300
2301  KEEKMPGECCGRCLPTACTIQLRGGQIMTLKRDETLQDGCDSHFCRVNER  2350
2351  GEYIWEKRITGCPPFDQHKCLAAGGKIMKIPGTCCDTCEEPECKDMTARL  2400
2401  QYVKVGNCRSEEEVDIHYCQGKCTSKAVYSIDTEDVEDQCACCSPTRTEP  2450
2451  MQVPLRCTNGSTIYHEVLNAIQCKCSPRKCSK                    2482

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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