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

NucPred

Fetching Q9XSJ7 from www.uniprot.org...

The NucPred score for your sequence is 0.33 (see score help below)

   1  MFSFVDLRLLLLLAATALLTHGQEEGQEEDIPPVTCVQNGLRYYDRDVWK    50
  51  PEACRICVCDNGNVLCDDVICDETKNCPGAQVPPGECCPVCPDGEASPTD   100
 101  QETTGVEGPKGDTGPRGPRGPAGPPGRDGIPGQPGLPGPPGPPGPPGPPG   150
 151  LGGNFAPQMSYGYDEKSTGGISVPGPMGPSGPRGLPGPPGAPGPQGFQGP   200
 201  PGEPGEPGASGPMGPRGPPGPPGKNGDDGEAGKPGRPGERGPPGPQGARG   250
 251  LPGTAGLPGMKGHRGFSGLDGAKGDAGPAGPKGEPGSPGENGAPGQMGPR   300
 301  GLPGERGRPGAPGPAGARGNDGATGAAGPPGPTGPAGPPGFPGAVGAKGE   350
 351  AGPQGARGSEGPQGVRGEPGPPGPAGAAGPAGNPGADGQPGAKGANGAPG   400
 401  IAGAPGFPGARGPSGPQGPSGPPGPKGNSGEPGAPGNKGDTGAKGEPGPT   450
 451  GIQGPPGPAGEEGKRGARGEPGPTGLPGPPGERGGPGSRGFPGADGVAGP   500
 501  KGPAGERGSPGPAGPKGSPGEAGRPGEAGLPGAKGLTGSPGSPGPDGKTG   550
 551  PPGPAGQDGRPGPPGPPGARGQAGVMGFPGPKGAAGEPGKAGERGVPGPP   600
 601  GAVGPAGKDGEAGAQGPPGPAGPAGERGEQGPAGSPGFQGLPGPAGPPGE   650
 651  AGKPGEQGVPGDLGAPGPSGARGERGFPGERGVQGPPGPAGPRGANGAPG   700
 701  NDGAKGDAGAPGAPGSQGAPGLQGMPGERGAAGLPGPKGDRGDAGPKGAD   750
 751  GSPGKDGVRGLTGPIGPPGPAGAPGDKGEAGPSGPAGPTGARGAPGDRGE   800
 801  PGPPGPAGFAGPPGADGQPGAKGEPGDAGAKGDAGPPGPAGPTGPPGPIG   850
 851  NVGAPGPKGARGSAGPPGATGFPGAAGRVGPPGPSGNAGPPGPPGPAGKE   900
 901  GGKGARGETGPAGRPGEVGPPGPPGPAGEKGSPGADGPAGAPGTPGPQGI   950
 951  AGQRGVVGLPGQRGERGFPGLPGPSGEPGKQGPSGTSGERGPPGPMGPPG  1000
1001  LAGPPGESGREGSPGAEGSPGRDGSPGPKGDRGETGPAGPPGAPGAPGAP  1050
1051  GPVGPAGKNGDRGETGPAGPAGPIGPVGARGPAGPQGPRGDKGETGEQGD  1100
1101  RGIKGHRGFSGLQGPPGPPGSPGEQGPSGASGPAGPRGPPGSAGSPGKDG  1150
1151  LNGLPGPIGPPGPRGRTGDAGPVGPPGPPGPPGPPGPPSGGFDFSFLPQP  1200
1201  PQEKAHDGGRYYRADDANVVRDRDLEVDTTLKSLSQQIENIRSPEGSRKN  1250
1251  PARTCRDLKMCHSDWKSGEYWIDPNQGCNLDAIKVFCNMETGETCVYPTQ  1300
1301  PQVAQKNWYISKNPKEKRHVWYGESMTDGFQFEYGGQGSDPADVAIQLTF  1350
1351  LRLMSTEASQNITYHCKNSVAYMDQQTGNLKKALLLQGSNEIEIRAEGNS  1400
1401  RFTYSVTYDGCTSHTGAWGKTVIEYKTTKTSRLPIIDVAPLDVGAPDQEF  1450
1451  GMDIGPVCFL                                          1460

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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