 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P0C0L5 from www.uniprot.org...
The NucPred score for your sequence is 0.82 (see score help below)
1 MRLLWGLIWASSFFTLSLQKPRLLLFSPSVVHLGVPLSVGVQLQDVPRGQ 50
51 VVKGSVFLRNPSRNNVPCSPKVDFTLSSERDFALLSLQVPLKDAKSCGLH 100
101 QLLRGPEVQLVAHSPWLKDSLSRTTNIQGINLLFSSRRGHLFLQTDQPIY 150
151 NPGQRVRYRVFALDQKMRPSTDTITVMVENSHGLRVRKKEVYMPSSIFQD 200
201 DFVIPDISEPGTWKISARFSDGLESNSSTQFEVKKYVLPNFEVKITPGKP 250
251 YILTVPGHLDEMQLDIQARYIYGKPVQGVAYVRFGLLDEDGKKTFFRGLE 300
301 SQTKLVNGQSHISLSKAEFQDALEKLNMGITDLQGLRLYVAAAIIESPGG 350
351 EMEEAELTSWYFVSSPFSLDLSKTKRHLVPGAPFLLQALVREMSGSPASG 400
401 IPVKVSATVSSPGSVPEVQDIQQNTDGSGQVSIPIIIPQTISELQLSVSA 450
451 GSPHPAIARLTVAAPPSGGPGFLSIERPDSRPPRVGDTLNLNLRAVGSGA 500
501 TFSHYYYMILSRGQIVFMNREPKRTLTSVSVFVDHHLAPSFYFVAFYYHG 550
551 DHPVANSLRVDVQAGACEGKLELSVDGAKQYRNGESVKLHLETDSLALVA 600
601 LGALDTALYAAGSKSHKPLNMGKVFEAMNSYDLGCGPGGGDSALQVFQAA 650
651 GLAFSDGDQWTLSRKRLSCPKEKTTRKKRNVNFQKAINEKLGQYASPTAK 700
701 RCCQDGVTRLPMMRSCEQRAARVQQPDCREPFLSCCQFAESLRKKSRDKG 750
751 QAGLQRALEILQEEDLIDEDDIPVRSFFPENWLWRVETVDRFQILTLWLP 800
801 DSLTTWEIHGLSLSKTKGLCVATPVQLRVFREFHLHLRLPMSVRRFEQLE 850
851 LRPVLYNYLDKNLTVSVHVSPVEGLCLAGGGGLAQQVLVPAGSARPVAFS 900
901 VVPTAATAVSLKVVARGSFEFPVGDAVSKVLQIEKEGAIHREELVYELNP 950
951 LDHRGRTLEIPGNSDPNMIPDGDFNSYVRVTASDPLDTLGSEGALSPGGV 1000
1001 ASLLRLPRGCGEQTMIYLAPTLAASRYLDKTEQWSTLPPETKDHAVDLIQ 1050
1051 KGYMRIQQFRKADGSYAAWLSRGSSTWLTAFVLKVLSLAQEQVGGSPEKL 1100
1101 QETSNWLLSQQQADGSFQDLSPVIHRSMQGGLVGNDETVALTAFVTIALH 1150
1151 HGLAVFQDEGAEPLKQRVEASISKASSFLGEKASAGLLGAHAAAITAYAL 1200
1201 TLTKAPADLRGVAHNNLMAMAQETGDNLYWGSVTGSQSNAVSPTPAPRNP 1250
1251 SDPMPQAPALWIETTAYALLHLLLHEGKAEMADQAAAWLTRQGSFQGGFR 1300
1301 STQDTVIALDALSAYWIASHTTEERGLNVTLSSTGRNGFKSHALQLNNRQ 1350
1351 IRGLEEELQFSLGSKINVKVGGNSKGTLKVLRTYNVLDMKNTTCQDLQIE 1400
1401 VTVKGHVEYTMEANEDYEDYEYDELPAKDDPDAPLQPVTPLQLFEGRRNR 1450
1451 RRREAPKVVEEQESRVHYTVCIWRNGKVGLSGMAIADVTLLSGFHALRAD 1500
1501 LEKLTSLSDRYVSHFETEGPHVLLYFDSVPTSRECVGFEAVQEVPVGLVQ 1550
1551 PASATLYDYYNPERRCSVFYGAPSKSRLLATLCSAEVCQCAEGKCPRQRR 1600
1601 ALERGLQDEDGYRMKFACYYPRVEYGFQVKVLREDSRAAFRLFETKITQV 1650
1651 LHFTKDVKAAANQMRNFLVRASCRLRLEPGKEYLIMGLDGATYDLEGHPQ 1700
1701 YLLDSNSWIEEMPSERLCRSTRQRAACAQLNDFLQEYGTQGCQV 1744
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
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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