 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P09848 from www.uniprot.org...
The NucPred score for your sequence is 0.47 (see score help below)
1 MELSWHVVFIALLSFSCWGSDWESDRNFISTAGPLTNDLLHNLSGLLGDQ 50
51 SSNFVAGDKDMYVCHQPLPTFLPEYFSSLHASQITHYKVFLSWAQLLPAG 100
101 STQNPDEKTVQCYRRLLKALKTARLQPMVILHHQTLPASTLRRTEAFADL 150
151 FADYATFAFHSFGDLVGIWFTFSDLEEVIKELPHQESRASQLQTLSDAHR 200
201 KAYEIYHESYAFQGGKLSVVLRAEDIPELLLEPPISALAQDTVDFLSLDL 250
251 SYECQNEASLRQKLSKLQTIEPKVKVFIFNLKLPDCPSTMKNPASLLFSL 300
301 FEAINKDQVLTIGFDINEFLSCSSSSKKSMSCSLTGSLALQPDQQQDHET 350
351 TDSSPASAYQRIWEAFANQSRAERDAFLQDTFPEGFLWGASTGAFNVEGG 400
401 WAEGGRGVSIWDPRRPLNTTEGQATLEVASDSYHKVASDVALLCGLRAQV 450
451 YKFSISWSRIFPMGHGSSPSLPGVAYYNKLIDRLQDAGIEPMATLFHWDL 500
501 PQALQDHGGWQNESVVDAFLDYAAFCFSTFGDRVKLWVTFHEPWVMSYAG 550
551 YGTGQHPPGISDPGVASFKVAHLVLKAHARTWHHYNSHHRPQQQGHVGIV 600
601 LNSDWAEPLSPERPEDLRASERFLHFMLGWFAHPVFVDGDYPATLRTQIQ 650
651 QMNRQCSHPVAQLPEFTEAEKQLLKGSADFLGLSHYTSRLISNAPQNTCI 700
701 PSYDTIGGFSQHVNHVWPQTSSSWIRVVPWGIRRLLQFVSLEYTRGKVPI 750
751 YLAGNGMPIGESENLFDDSLRVDYFNQYINEVLKAIKEDSVDVRSYIARS 800
801 LIDGFEGPSGYSQRFGLHHVNFSDSSKSRTPRKSAYFFTSIIEKNGFLTK 850
851 GAKRLLPPNTVNLPSKVRAFTFPSEVPSKAKVVWEKFSSQPKFERDLFYH 900
901 GTFRDDFLWGVSSSAYQIEGAWDADGKGPSIWDNFTHTPGSNVKDNATGD 950
951 IACDSYHQLDADLNMLRALKVKAYRFSISWSRIFPTGRNSSINSHGVDYY 1000
1001 NRLINGLVASNIFPMVTLFHWDLPQALQDIGGWENPALIDLFDSYADFCF 1050
1051 QTFGDRVKFWMTFNEPMYLAWLGYGSGEFPPGVKDPGWAPYRIAHAVIKA 1100
1101 HARVYHTYDEKYRQEQKGVISLSLSTHWAEPKSPGVPRDVEAADRMLQFS 1150
1151 LGWFAHPIFRNGDYPDTMKWKVGNRSELQHLATSRLPSFTEEEKRFIRAT 1200
1201 ADVFCLNTYYSRIVQHKTPRLNPPSYEDDQEMAEEEDPSWPSTAMNRAAP 1250
1251 WGTRRLLNWIKEEYGDIPIYITENGVGLTNPNTEDTDRIFYHKTYINEAL 1300
1301 KAYRLDGIDLRGYVAWSLMDNFEWLNGYTVKFGLYHVDFNNTNRPRTARA 1350
1351 SARYYTEVITNNGMPLAREDEFLYGRFPEGFIWSAASAAYQIEGAWRADG 1400
1401 KGLSIWDTFSHTPLRVENDAIGDVACDSYHKIAEDLVTLQNLGVSHYRFS 1450
1451 ISWSRILPDGTTRYINEAGLNYYVRLIDTLLAASIQPQVTIYHWDLPQTL 1500
1501 QDVGGWENETIVQRFKEYADVLFQRLGDKVKFWITLNEPFVIAYQGYGYG 1550
1551 TAAPGVSNRPGTAPYIVGHNLIKAHAEAWHLYNDVYRASQGGVISITISS 1600
1601 DWAEPRDPSNQEDVEAARRYVQFMGGWFAHPIFKNGDYNEVMKTRIRDRS 1650
1651 LAAGLNKSRLPEFTESEKRRINGTYDFFGFNHYTTVLAYNLNYATAISSF 1700
1701 DADRGVASIADRSWPDSGSFWLKMTPFGFRRILNWLKEEYNDPPIYVTEN 1750
1751 GVSQREETDLNDTARIYYLRTYINEALKAVQDKVDLRGYTVWSAMDNFEW 1800
1801 ATGFSERFGLHFVNYSDPSLPRIPKASAKFYASVVRCNGFPDPATGPHAC 1850
1851 LHQPDAGPTISPVRQEEVQFLGLMLGTTEAQTALYVLFSLVLLGVCGLAF 1900
1901 LSYKYCKRSKQGKTQRSQQELSPVSSF 1927
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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