 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q12772 from www.uniprot.org...
The NucPred score for your sequence is 0.84 (see score help below)
1 MDDSGELGGLETMETLTELGDELTLGDIDEMLQFVSNQVGEFPDLFSEQL 50
51 CSSFPGSGGSGSSSGSSGSSSSSSNGRGSSSGAVDPSVQRSFTQVTLPSF 100
101 SPSAASPQAPTLQVKVSPTSVPTTPRATPILQPRPQPQPQPQTQLQQQTV 150
151 MITPTFSTTPQTRIIQQPLIYQNAATSFQVLQPQVQSLVTSSQVQPVTIQ 200
201 QQVQTVQAQRVLTQTANGTLQTLAPATVQTVAAPQVQQVPVLVQPQIIKT 250
251 DSLVLTTLKTDGSPVMAAVQNPALTALTTPIQTAALQVPTLVGSSGTILT 300
301 TMPVMMGQEKVPIKQVPGGVKQLEPPKEGERRTTHNIIEKRYRSSINDKI 350
351 IELKDLVMGTDAKMHKSGVLRKAIDYIKYLQQVNHKLRQENMVLKLANQK 400
401 NKLLKGIDLGSLVDNEVDLKIEDFNQNVLLMSPPASDSGSQAGFSPYSID 450
451 SEPGSPLLDDAKVKDEPDSPPVALGMVDRSRILLCVLTFLCLSFNPLTSL 500
501 LQWGGAHDSDQHPHSGSGRSVLSFESGSGGWFDWMMPTLLLWLVNGVIVL 550
551 SVFVKLLVHGEPVIRPHSRSSVTFWRHRKQADLDLARGDFAAAAGNLQTC 600
601 LAVLGRALPTSRLDLACSLSWNVIRYSLQKLRLVRWLLKKVFQCRRATPA 650
651 TEAGFEDEAKTSARDAALAYHRLHQLHITGKLPAGSACSDVHMALCAVNL 700
701 AECAEEKIPPSTLVEIHLTAAMGLKTRCGGKLGFLASYFLSRAQSLCGPE 750
751 HSAVPDSLRWLCHPLGQKFFMERSWSVKSAAKESLYCAQRNPADPIAQVH 800
801 QAFCKNLLERAIESLVKPQAKKKAGDQEEESCEFSSALEYLKLLHSFVDS 850
851 VGVMSPPLSRSSVLKSALGPDIICRWWTSAITVAISWLQGDDAAVRSHFT 900
901 KVERIPKALEVTESPLVKAIFHACRAMHASLPGKADGQQSSFCHCERASG 950
951 HLWSSLNVSGATSDPALNHVVQLLTCDLLLSLRTALWQKQASASQAVGET 1000
1001 YHASGAELAGFQRDLGSLRRLAHSFRPAYRKVFLHEATVRLMAGASPTRT 1050
1051 HQLLEHSLRRRTTQSTKHGEVDAWPGQRERATAILLACRHLPLSFLSSPG 1100
1101 QRAVLLAEAARTLEKVGDRRSCNDCQQMIVKLGGGTAIAAS 1141
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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