 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P02564 from www.uniprot.org...
The NucPred score for your sequence is 0.94 (see score help below)
1 MADREMAAFGAGAPFLRKSEKERLEAQTRPFDLKKDVFVPDDKEEFVKAK 50
51 IVSREGGKVTAETENGKTVTVKEDQVMQQNPPKFDKIEDMAMLTFLHEPA 100
101 VLYNLKERYASWMIYTYSGLFCVTVNPYKWLPVYNAQVVAAYRGKKRSEA 150
151 PPHIFSISDNAYQYMLTDRENQSILITGESGAGKTVNTKRVIQYFAVIAA 200
201 IGDRSKKDQTPGKGTLEDQIIQANPALEAFGNAKTVRNDNSSRFGKFIRI 250
251 HFGATGKLASADIETYLLEKSRVIFQLKAERDYHIFYQILSNKKPELLDM 300
301 LLITNNPYDYAFFSQGETTVASIDDSEEHMATDSAFDVLGFTPEEKNSIY 350
351 KLTGAIMHFGNMKFKQKQREEQAEPDGTEEADKSAYLMGLNSADLLKGLC 400
401 HPRVKVGNEYVTKGQNVQQVAYAIGALAKSVYEKMFNWMVTRINATLETK 450
451 QPRQYFIGVLDIAGFEIFDFNSFEQLCINFTNEKLQQFFNHHMFVLEQEE 500
501 YKKEGIEWTFIDFGMDLQACIDLIEKPMGIMSILEEECMFPKATDMTFKA 550
551 KLYDNHLGKSNNFQKPRNIKGKQEAHFSLIHYAGTVDYNILGWLQKNKDP 600
601 LNETVVGLYQKSSLKLLSNLFANYAGADAPVDKGKGKAKKGSSFQTVSAL 650
651 HRENLNKLMTNLRSTHPHFVRCIIPNETKSPGVMDNPLVMHQLRCNGVLE 700
701 GIRICRKGFPNRILYGDFRQRYRILNPAAIPEGQFIDSRKGAEKLLGSLD 750
751 IDHNQYKFGHTKVFFKAGLLGLLEEMRDERLSRIITRIQAQSRGVLSRME 800
801 FKKLLERRDSLLIIQWNIRAFMGVKNWPWMKLYFKIKPLLKSAETEKEMA 850
851 NMKEEFGRVKDALEKSEARRKELEEKMVSLLQEKNDLQLQVQAEQDNLAD 900
901 AEERCDQLIKNKIQLEAKVKEMTERLEDEEEMNAELTAKKRKLEDECSEL 950
951 KRDIDDLELTLAKVEKEKHATENKVKNLTEEMAGLDEIIVKLTKEKKALQ 1000
1001 EAHQQALDDLQAEEDKVNTLTKAKVKLEQQVDDLEGSLDQDKKVRMDLER 1050
1051 AKRKLEGDLKLTQESIMDLENDKQQLDERLKKKDFELNALNARIEDEQAL 1100
1101 GSQLQKKLKELQARIEELEEELEAERTARAKVEKLRSDLSRELEEISERL 1150
1151 EEAGGATSVQIEMNKKREAEFQKMRRDLEEATLQHEATAAALRKKHADSV 1200
1201 AELGEQIDNLQRVKQKLEKEKSEFKLELDDVTSNMEQIIKAKANLEKMCR 1250
1251 TLEDQMNEHRSKAEETQRSVNDLTRQRAKLQTENGELSRQLDEKEALISQ 1300
1301 LTRGKLTYTQQLEDLKRQLEEEVKAKNALAHALQSARHDCDLLREQYEEE 1350
1351 TEAKAELQRVLSKANSEVAQWRTKYETDAIQRTEELEEAKKKLAQRLQDA 1400
1401 EEAVEAVNAKCSSLEKTKHRLQNEIEDLMVDVERSNAAAAALDKKQRNFD 1450
1451 KILVEWKQKYEESQSELESSQKEARSLSTELFKLKNAYEESLEHLETFKR 1500
1501 ENKNLQEEISDLTEQLGSTGKSIHELEKIRKQLEAEKLELQSALEEAEAS 1550
1551 LEHEEGKILRAQLEFNQIKAEIERKLAEKDEEMEQAKRNHLRVVDSLQTS 1600
1601 LDAETRSRNEALRVKKKMEGDLNEMEIQLSHANRMAAEAQKQVKSLQSLL 1650
1651 KDTQIQLDDAVRANDDLKENIAIVERRNNLLQAELEELRAVVEQTERSRK 1700
1701 LAEQELIETSERVQLLHSQNTSLINQKKKMDADLSQLQTEVEEAVQECRN 1750
1751 AEEKAKKAITDAAMMAEELKKEQDTSAHLERMKNNMEQTIKDLQHRLDEA 1800
1801 EQIALKGGKKQLQKLEARVRELENELEAEQKRNAESVKGMRKSERRIKEL 1850
1851 TYQTEEDRKNLLRLQDLVDKLQLKVKAYKRQAEEAEEQANTNLSKFRKVQ 1900
1901 HELDEAEERADIAESQVNKLRAKSRDIGAKGLNEE 1935
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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