 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q13751 from www.uniprot.org...
The NucPred score for your sequence is 0.75 (see score help below)
1 MRPFFLLCFALPGLLHAQQACSRGACYPPVGDLLVGRTRFLRASSTCGLT 50
51 KPETYCTQYGEWQMKCCKCDSRQPHNYYSHRVENVASSSGPMRWWQSQND 100
101 VNPVSLQLDLDRRFQLQEVMMEFQGPMPAGMLIERSSDFGKTWRVYQYLA 150
151 ADCTSTFPRVRQGRPQSWQDVRCQSLPQRPNARLNGGKVQLNLMDLVSGI 200
201 PATQSQKIQEVGEITNLRVNFTRLAPVPQRGYHPPSAYYAVSQLRLQGSC 250
251 FCHGHADRCAPKPGASAGPSTAVQVHDVCVCQHNTAGPNCERCAPFYNNR 300
301 PWRPAEGQDAHECQRCDCNGHSETCHFDPAVFAASQGAYGGVCDNCRDHT 350
351 EGKNCERCQLHYFRNRRPGASIQETCISCECDPDGAVPGAPCDPVTGQCV 400
401 CKEHVQGERCDLCKPGFTGLTYANPQGCHRCDCNILGSRRDMPCDEESGR 450
451 CLCLPNVVGPKCDQCAPYHWKLASGQGCEPCACDPHNSLSPQCNQFTGQC 500
501 PCREGFGGLMCSAAAIRQCPDRTYGDVATGCRACDCDFRGTEGPGCDKAS 550
551 GRCLCRPGLTGPRCDQCQRGYCNRYPVCVACHPCFQTYDADLREQALRFG 600
601 RLRNATASLWSGPGLEDRGLASRILDAKSKIEQIRAVLSSPAVTEQEVAQ 650
651 VASAILSLRRTLQGLQLDLPLEEETLSLPRDLESLDRSFNGLLTMYQRKR 700
701 EQFEKISSADPSGAFRMLSTAYEQSAQAAQQVSDSSRLLDQLRDSRREAE 750
751 RLVRQAGGGGGTGSPKLVALRLEMSSLPDLTPTFNKLCGNSRQMACTPIS 800
801 CPGELCPQDNGTACGSRCRGVLPRAGGAFLMAGQVAEQLRGFNAQLQRTR 850
851 QMIRAAEESASQIQSSAQRLETQVSASRSQMEEDVRRTRLLIQQVRDFLT 900
901 DPDTDAATIQEVSEAVLALWLPTDSATVLQKMNEIQAIAARLPNVDLVLS 950
951 QTKQDIARARRLQAEAEEARSRAHAVEGQVEDVVGNLRQGTVALQEAQDT 1000
1001 MQGTSRSLRLIQDRVAEVQQVLRPAEKLVTSMTKQLGDFWTRMEELRHQA 1050
1051 RQQGAEAVQAQQLAEGASEQALSAQEGFERIKQKYAELKDRLGQSSMLGE 1100
1101 QGARIQSVKTEAEELFGETMEMMDRMKDMELELLRGSQAIMLRSADLTGL 1150
1151 EKRVEQIRDHINGRVLYYATCK 1172
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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