 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P13539 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MTDSQMADFGAAAEYLRKSEKERLEAQTRPFDIRTECFVPDDKEEFVKAK 50
51 IVSREGGKVTAETENGKTVTVKEDQVMQQNPPKFDKIEDMAMLTFLHEPA 100
101 VLYNLKERYAAWMIYTYSGLFCVTVNPYKWLPVYNAEVVAAYRGKKRSEA 150
151 PAHIFSISDNAYQYMLTDRENQSILITGESGAGKTVNTKRVIQYFASIAA 200
201 IGDRSKKDNPNANKGTLEDQIIQANPALEAFGNAKTVRNDNSSRFGKFIR 250
251 IHFGATGKLASADIETYLLEKSRVIFQLKAERNYHIFYQILSNKKPELLD 300
301 MLLVTNNPYDYAFVSQGEVSVASIDDSEELLATDSAFDVLGFTAEEKAGV 350
351 YKLTGAIMHYGNMKFKQKQREEQAEPDGTEDADKSAYLMGLNSADLLKGL 400
401 CHPRVKVGNEYVTKGQSVQQVYYSIGALGKSVYEKMFNWMVTRINATLET 450
451 KQPRQYFIGVLDIAGFEIFDFNSFEQLCINFTNEKLQQFFNHHMFVLEQE 500
501 EYKKEGIEWEFIDFGMDLQACIDLIEKPMGIMSILEEECMFPKATDMTFK 550
551 AKLYDNHLGKSNNFQKPRNVKGKQEAHFSLVHYAGTVDYNILGWLEKNKD 600
601 PLNETVVGLYQKSSLKLMATLFSTYASADAGDSGKGKGGKKKGSSFQTVS 650
651 ALHRENLNKLMTNLRTTHPHFVRCIIPNERKAPGVMDNPLVMHQLRCNGV 700
701 LEGIRICRKGFPNRILYGDFRQRYRILNPAAIPEGQFIDSRKGAEKLLSS 750
751 LDIDHNQYKFGHTKVFFKAGLLGLLEEMRDERLSRIITRIQAQARGQLMR 800
801 IEFKKMVERRDALLVIQWNIRAFMGVKNWPWMKLYFKIKPLLKSAETEKE 850
851 MANMKEEFGRVKESLEKSEARRKELEEKMVSLLQEKNDLQFQVQAEQDNL 900
901 NDAEERCDQLIKNKIQLEAKVKEMTERLEDEEEMNAELTSKKRKLEDECS 950
951 ELKKDIDDLELTLAKVEKEKHATENKVKNLTEEMAGLDEIIAKLTKEKKA 1000
1001 LQEAHQQALDDLQAEEDKVNTLTKSKVKLEQQVDDLEGSLEQEKKVRMDL 1050
1051 ERAKRKLEGDLNVTQESIMDLENDKLQLEEKLKKKEFDISQQNSKIEDEQ 1100
1101 ALALQLQKKLKENQARIEELEEELEAERTARAKVEKLRSDLTRELEEISE 1150
1151 RLEEAGGATSVQIEMNKKREAEFQKMRRDLEEATLQHEATAAALRKKHAD 1200
1201 SVAELGEQIDNLQRVKQKLEKEKSEFKLELDDVTSNMEQIIKAKANLEKV 1250
1251 SRTLEDQANEYRVKLEESQRSLNDFTTQRAKLQTENGELARQLEEKEALI 1300
1301 SQLTRGKLSYTQQMEDLKRQLEEEGKAKNALAHALQSARHDCDLLREQYE 1350
1351 EEMEAKAELQRVLSKANSEVAQWRTKYETDAIQRTEELEEAKKKLAQRLQ 1400
1401 DAEEAVEAVNAKCSSLEKTKHRLQNEIEDLMVDVERSNAAAAALDKKQRN 1450
1451 FDKILAEWKQKYEESQSELESSQKEARSLSTELFKLKNAYEESLEHLETF 1500
1501 KRENKNLQEEISDLTEQLGEGGKNVHELEKVRKQLEVEKMELQSALEEAE 1550
1551 ASLEHEEGKILRAQLEFNQIKAEIERKLAEKDEEMEQAKRNHLRVVDSLQ 1600
1601 TSLDAETRSRNEALRVKKKMEGDLNEMEIQLSQANRIASEAQKHLKNAQA 1650
1651 HLKDTQLQLDDALHANDDLKENIAIVERRNTLLQAELEELRAVVEQTERS 1700
1701 RKLAEQELIETSERVQLLHSQNTSLINQKKKMEADLTQLQTEVEEAVQEC 1750
1751 RNAEEKAKKAITDAAMMAEELKKEQDTSAHLERMKKNMEQTIKDLQHRLD 1800
1801 EAEQIALKGGKKQLQKLEARVRELENELEAEQKRNAESVKGMRKSERRIK 1850
1851 ELTYQTEEDKKNLVRLQDLVDKLQLKVKAYKRQAEEAEEQANTNLSKFRK 1900
1901 VQHELDEAEERADIAESQVNKLRAKSRDIGAKQKMHDEE 1939
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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