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

NucPred

Fetching Q12774 from www.uniprot.org...

The NucPred score for your sequence is 0.88 (see score help below)

   1  MEAEEAQRGASPPISAIEEFSIIPEAPMRSSQVSALGLEAQEDEDPSYKW    50
  51  REEHRLSATQQSELRDVCDYAIETMPSFPKEGSADVEPNQESLVAEACDT   100
 101  PEHWEAVPQSLAGRQARTLAPPELWACPIQSEHLDMAPFSSDLGSEEEEV   150
 151  EFWPGLTSLTLGSGQAEEEEETSSDNSGQTRYYSPCEEHPAETNQNEGSE   200
 201  SGTIRQGEELPPEELQESQGLLHPQEVQVLEEQGQQEAGFRGEGTLREDV   250
 251  CADGLLGEEQMIEQVNDEKGEQKQKQEQVQDVMLGRQGERMGLTGEPEGL   300
 301  NDGEWEQEDMERKAQGQGGPEQGEERKRELQVPEENRADSQDEKSQTFLG   350
 351  KSEEVTGKQEDHGIKEKGVPVSGQEAKEPESWDGGRLGAVGRARSREEEN   400
 401  EHHGPSMPALIAPEDSPHCDLFPGASYLMTQIPGTQTESRAEELSPAALS   450
 451  PSLEPIRCSHQPISLLGSFLTEESPDKEIDQNSQQEESRLRKGTVSSQGT   500
 501  EVVFASASVTPPRTPDSAPPSPAEAYPITPASVSARPPVAFPRRETSCAA   550
 551  RAPETASAPLSMDDPSPCGTSEMCPAALYGFPSTGTSPPRPPANSTGTVQ   600
 601  HLRSDSFPGSHRTEQTPDLVGMLLSYSHSELPQRPPKPAIYSSVTPRRDR   650
 651  RSGRDYSTVSASPTALSTLKQDSQESISNLERPSSPPSIQPWVSPHNPAF   700
 701  ATESPAYGSSPSFVSMEDVRIHEPLPPPPPQRRDTHPSVVETDGHARVVV   750
 751  PTLKQHSHPPPLALGSGLHAPHKGPLPQASDPAVARQHRPLPSTPDSSHH   800
 801  AQATPRWRYNKPLPPTPDLPQPHLPPISAPGSSRIYRPLPPLPIIDPPTE   850
 851  PPPLPPKSRGRSRSTRGGHMNSGGHAKTRPACQDWTVPLPASAGRTSWPP   900
 901  ATARSTESFTSTSRSKSEVSPGMAFSNMTNFLCPSSPTTPWTPELQGPTS   950
 951  KDEAGVSEHPEAPAREPLRRTTPQQGASGPGRSPVGQARQPEKPSHLHLE  1000
1001  KASSWPHRRDSGRPPGDSSGQAVAPSEGANKHKGWSRQGLRRPSILPEGS  1050
1051  SDSRGPAVEKHPGPSDTVVFREKKPKEVMGGFSRRCSKLINSSQLLYQEY  1100
1101  SDVVLNKEIQSQQRLESLSETPGPSSPRQPRKALVSSESYLQRLSMASSG  1150
1151  SLWQEIPVVRNSTVLLSMTHEDQKLQEVKFELIVSEASYLRSLNIAVDHF  1200
1201  QLSTSLRATLSNQEHQWLFSRLQDVRDVSATFLSDLEENFENNIFSFQVC  1250
1251  DVVLNHAPDFRRVYLPYVTNQTYQERTFQSLMNSNSNFREVLEKLESDPV  1300
1301  CQRLSLKSFLILPFQRITRLKLLLQNILKRTQPGSSEEAEATKAHHALEQ  1350
1351  LIRDCNNNVQSMRRTEELIYLSQKIEFECKIFPLISQSRWLVKSGELTAL  1400
1401  EFSASPGLRRKLNTRPVHLHLFNDCLLLSRPREGSRFLVFDHAPFSSIRG  1450
1451  EKCEMKLHGPHKNLFRLFLRQNTQGAQAEFLFRTETQSEKLRWISALAMP  1500
1501  REELDLLECYNSPQVQCLRAYKPRENDELALEKADVVMVTQQSSDGWLEG  1550
1551  VRLSDGERGWFPVQQVEFISNPEVRAQNLKEAHRVKTAKLQLVEQQA     1597

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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