 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P13540 from www.uniprot.org...
The NucPred score for your sequence is 0.94 (see score help below)
1 MADREMAAFGAAAFLRKSEKERLEAQTRPFDLKKDVFVPDDKEEFVKAKI 50
51 VSREGGKVTAETENGKTVTVKEDQVMQQNPPKFDKIEDMAMLTFLHEPAV 100
101 LYNLKDGYASWMIYTYSGLFCVTVNPYKWLPVYNAEVVAAYRGKKRSEAP 150
151 AHIFSISDNAYQYMLTDRENQSILITGESGAGKTVNTKRVIQYFAVIAAI 200
201 GDRSKKDQTPGKGTLEDQIIQANPALEAFGNAKTVRNDNSSRFGKFIRIH 250
251 FGATGKLASADIETYLLEKSRVIFQLKAERDYHIFYQILSNKKPELLDML 300
301 LITNNPYDYAFIPQGETTVASIDDSEELMATDSAFDVLGFTSEEKNSIYK 350
351 LTGAIMHFGNMKFKQKQREEQADRDGTEEEDKSAYLMGLNSADLLKGMCH 400
401 PRVKVGNEYVTKGQNVQQVSYAIGALAKSVYEKMFNWMVTRINATLETKQ 450
451 PRQYFIGVLDIAGFEIFDFNSFEQLCINFTNEKLQQFFNHHMFVLEQEEY 500
501 KKEGIEWTFIDFGMDLQACIDLIEKPMRIMSILEEECMFPKATDMTFKAK 550
551 LYDNHLGKSNNFQKPRNVKGKQEAHFSLVHYAGTVDYNILGWLQKNKDPL 600
601 NETVVGLYQKSSLKLLSNLFANYAGADAPVDKGKGKAKKGSSFQTVSVLH 650
651 RENLNKLMTNLRSTHPHFVRCIIPNETKSPGVMDNPLVMHQLRCNGVLEG 700
701 IRICRKGFPNRILYGDFRQRYRILNPAAIPEGQFIDSRKGAEKLLSSLDI 750
751 DHNQYKFGHTKVFFKAGLLGLLEEMRDERLSRIITRIQAQSRGLLSRMEF 800
801 KKLLERRDSLLVIQWNIRAFMGVKNWPWMKLYFKIKPLLKSAETEKEMAT 850
851 MKEEFGRVKDALEKSEARRKELEEKMVSLLQEKNDLQLQVQAEQDNLADA 900
901 EERCDQLIKNKIQLEAKVKEMTERLEDEEEMNAELTAKKRKLEDECSELK 950
951 RDIDDLELTLAKVEKDKHATENKVKNLTEEMAGLDEIIAKLTKEKKALQE 1000
1001 AHQQALDDLQAEEDKVNTLTKSKVKLEQQVDDLEGSLEQEKKVRMDLERA 1050
1051 KRKLEGDLKLTQESIMDLENDKQQLDEKLKKKDFELNALNARIEDEQALG 1100
1101 SQLQKKLKELQARIEELEEELEAERTARAKVEKLRSDLSRELEEISERLE 1150
1151 EAGGATSVQIEMNKKREAEFQKMRRDLEEATLQHEATAAALRKKHADSVA 1200
1201 ELGEQIDNLQRVKQKLEKEKSEFKLELDDVTSNMEQIIKAKANLEKMCRT 1250
1251 LEDQMNEHRSKAEETQRSVNDLTSQRAKLQTENGELSRQLDEKEALISQL 1300
1301 TRGKLTYTQQLEDLKRQLEEEVKAKNTLAHALQSARHDCDLLREQYEEET 1350
1351 EAKAELQCVLSKANSEVAQWRTKYETDAIQRTEELEEAKKKLAQRLQDAE 1400
1401 EAVEAVNAKCSSLEKTKHRLQNEIEDLMVDVERSNAAAAALDKKQRNFDK 1450
1451 ILAEWKQKYEESQSELESSQKEARSLSTELFKLKNAYEESLEHLETFKRE 1500
1501 NKNLQEEISDLTEQLGSTGKSIHELEKIRKQLEAEKMELQSALEEAEASL 1550
1551 EHEEGNILRAQLEFNQIKAEIERKLAEKDEEMEQAKRNHLRVVDSLQTSL 1600
1601 DAETRSRNEALRVKKKMEGDLNEMEIQLSHANRMAAEAQKQVKSLQSLLK 1650
1651 DTQIQLDDAVRANDDLKENIAIVERRNNLLQAELEELRAVVEQTERSRKL 1700
1701 AEQELIETSERVQLLHSQNTSLINQKKKMDADLSQLQTEVEEAVQECRNA 1750
1751 EEKAKKAITDAAMMAEELKKEQDTSAHLERMKKNMEQTIKDLQHRLDEAE 1800
1801 QIALKGGKKQLQKLEARVRELENELEAEQKRNAESVKGMRKSERRIKELT 1850
1851 YQTEEDRKNLLRLQDLVDKLQLKVKAYKRQAEEAEEQANTNLSKFRKVQH 1900
1901 ELDEAEERADIAESQVNKLRAKSRDIGAKGLNEE 1934
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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