 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P53886 from www.uniprot.org...
The NucPred score for your sequence is 0.67 (see score help below)
1 MTSKPSTRNDYLPRETHNGEYTGDSPEWQLQINITNKIGGINGDIWLSRD 50
51 GRSVKWCIEDQCLRQFTYNQKIIKAGYIDFEKTPDCFVVVLSDIAHVYML 100
101 KNGGSTTVCFPFQIGNAFWYANGVILERETSASFMDGGYDLKPIEFDLKH 150
151 KYITLTDPMAPFGLISITNTFKGGINSASGNKTDILQDFQLVLFPSDKDK 200
201 CIAVFLDRNSKVLRFYYSRILSSDQSRKGELTISSTKKTGLDAAGNSQKS 250
251 GGISKDLRKFSHLTRRSTSINSNSHDFNAAERVLSGNVGNASGRTDIFAL 300
301 PSSCSRRSLSATLDRMGNNIAPTNRAAPSGFFDSSSANTATHSNITPVSQ 350
351 PMQQQQQEYLNQTATSSKDIVLTEISSLKLPDDIIFTSRRLSSILSKLKF 400
401 LSLRFERREGLLIFHEPTHFCKIWLIDLLPDVLDSIPFKIYGNSPQNMIR 450
451 LENLKLKEPSRIQAMYIHELLESCLILVSEGQNKEEYKACLYDPFVKITS 500
501 PSKNISEELTKQNSLPSLQKLFPYPETSFTKLCFEAVKYITSPAFNISFI 550
551 FLWQSAYSILLSRANDDVVGGLKMEHDAFSLVLSLLILPIPSSSAQEYQE 600
601 YKEIYERDLFQHLKQDSEITSSVLPRIVIGLHLIREEYSLNVLCRNEHAL 650
651 LGQFLRFATAAMGWPDLWQSYYVPKMDSESKTFLHPREQNSTFFHPLDEP 700
701 PSITKSLYSITENSSIPLCPFISFSRLVATDTQVELRITPRSFKILGLYE 750
751 LVHSPNFLPDYVLGILSSFKVDKDELQTYPLGILVPLQNILKILEDKLSE 800
801 VRDNLELLDRADLQRCSAIINSIRSDSKEVLKRGQRDSYMLCKVPLAKNR 850
851 SSLSKKPSDIYSILSEIVKSASQVPLDGSAMRMSNIQDDEDIDEGRSLKL 900
901 NAGLIFSEDKRFTHVVSLLAYYRPTKTQFFTTKTEYAQILAQKKYFAKIM 950
951 ALRTCTNGVGWGAVAYATEKPISTQKWVIQPLNLISVFPDDTKITVKAPE 1000
1001 DIAHDIVEWGQFHAGVSSGLRISKKATGITGSWIAFNKPKELDAYHGGFL 1050
1051 LGLGLNGHLKNLEEWHIYNYLSPRNTHISIGLLLGMSSSMKGSMDSKLIK 1100
1101 VISVHLVAFLPSGSSDLNIDLKLQTAGIIGMGMLYLNSRHKRMSDSIFAQ 1150
1151 LVSLLNVNDEMVADEEYRLAAGISLGLINLGAGQTKLRKWDSSLLGLGDD 1200
1201 LPEDVYDSSDVEQNVMYEDLTTKLLEIVTSTYDVENDWIPENSQIGAVIA 1250
1251 IMFLFLKSNNFGISNMLKVDLKEILKANINTRPELLMYREWASNMILWEF 1300
1301 IGDDLSFIMKDVDIGVKFSELNTDLLPIYYTMAGRILAMGIRFASTGNLK 1350
1351 IRNILLSLVDKFLPLYQYPGKQNLDFRLTISVINVLTNVIVVSLSMVMCA 1400
1401 SGDLEVLRRVKYLHEVASGPYSDLFQEIPSSKSDVSGVTQVTSNTNTPGN 1450
1451 SDRERVDETAASLDDERSSNGSDISDPTAYLEDKKDIDDHYGKFISTNLA 1500
1501 LGFLFLGSGQYALNTSTLESIAFLSMSVLPTYTTPHPLQELKHFWSMAVE 1550
1551 PRCLVIKDISTGDAVNNVPIELVVEEDVEKEEVIREISTPCLLPDFSKIK 1600
1601 SIRVKMHGYFPLEVNFTKDYSASDFFSGGTIIYIQRKSESVFENKASFRN 1650
1651 VEDIHVALKRKAAESKNYSRLNLKNEQGNTTSSQLVESLGIQDLTMVELD 1700
1701 TLLSAGNNTALTDSESYNLGLLCSDKNSGDILDCQLELWYKSFGPHDE 1748
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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