 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P51840 from www.uniprot.org...
The NucPred score for your sequence is 0.31 (see score help below)
1 MSAWLLPAGGFPGAGFCIPAWQSRSSLSRVLRWPGPGLPGLLLLLLLPSP 50
51 SAFSAVFKVGVLGPWACDPIFARARPDLAARLATDRLNRDLALDGGPWFE 100
101 VTLLPEPCLTPGSLGAVSSALTRVSGLVGPVNPAACRPAELLAQEAGVAL 150
151 VPWGCPGTRAAGTTAPAVTPAADALYVLLKAFRWARVALITAPQDLWVEA 200
201 GRALSTALRARGLPVALVTSMVPSDLSGAREALRRIRDGPRVRVVIMVMH 250
251 SVLLGGEEQRYLLEAAEELGLTDGSLVFLPFDTLHYALSPGPEALAAFVN 300
301 SSKLRRAHDAVLTLTRRCPPGGSVQDSLRRAQEHQELPLDLDLKQVSPLF 350
351 GTIYDAVFLLAGGVTRARAAVGGGWVSGASVARQMREAQVFGFCGILGRT 400
401 EEPSFVLLDTDAAGERLFTTHLLDPVLGSLRSAGTPVHFPRGAPAPGPDP 450
451 SCWFDPDVICNGGVEPGLVFVGFLLVIVVGLTGAFLAHYLRHRLLHMQMV 500
501 SGPNKIILTLEDVTFLHPQGGSSRKVAQGSRSSLATRSTSDIRSVPSQPQ 550
551 ESTNIGLYEGDWVWLKKFPGEHHMAIRPATKMAFSKLRELRHENVALYLG 600
601 LFLAGTADSPATPGEGILAVVSEHCARGSLHDLLAQRDIKLDWMFKSSLL 650
651 LDLIKGMRYLHHRGVAHGRLKSRNCVVDGRFVLKVTDHGHGRLLEAQRVL 700
701 PEPPSAEDQLWTAPELLRDPALERRGTLAGDVFSLGIIMQEVVCRSTPYA 750
751 MLELTPEEVIQRVRSPPPLCRPLVSMDQAPMECIQLMAQCWAEHPELRPS 800
801 MDLTFDLFKGINKGRKTNIIDSMLRMLEQYSSNLEDLIRERTEELEQEKQ 850
851 KTDRLLTQMLPPSVAEALKMGTSVEPEYFEEVTLYFSDIVGFTTISAMSE 900
901 PIEVVDLLNDLYTLFDAIIGSHDVYKVETIGDAYMVASGLPQRNGQRHAA 950
951 EIANMSLDILSAVGSFRMRHMPEVPVRIRIGLHSGPCVAGVVGLTMPRYC 1000
1001 LFGDTVNTASRMESTGLPYRIHVNMSTVRILRALDQGFQMECRGRTELKG 1050
1051 KGVEDTYWLVGRVGFNKPIPKPPDLQPGASNHGISLQEIPPERRKKLEKA 1100
1101 RPGQFTGK 1108
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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