 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9W420 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MAEFLDSEAEESEEEEELDVNERKRLKKLKAAVSDSSEEEEDDEERLREE 50
51 LKDLIDDNPIEEDDGSGYDSDGVGSGKKRKKHEDDDLDDRLEDDDYDLIE 100
101 ENLGVKVERRKRFKRLRRIHDNESDGEEQHVDEGLVREQIAEQLFDENDE 150
151 SIGHRSERSHREADDYDDVDTESDADDFIVDDNGRPIAEKKKKRRPIFTD 200
201 ASLQEGQDIFGVDFDYDDFSKYEEDDYEDDSEGDEYDEDLGVGDDTRVKK 250
251 KKALKKKVVKKTIFDIYEPSELKRGHFTDMDNEIRKTDIPERMQLREVPV 300
301 TPVPEGSDELDLEAEWIYKYAFCKHTVSEQEKPESREKMRKPPTTVNKIK 350
351 QTLEFIRNQQLEVPFIAFYRKEYVKPELNIDDLWKVYYYDGIWCQLNERK 400
401 RKLKVLFEKMRQFQLDTLCADTDQPVPDDVRLILDSDFERLADVQSMEEL 450
451 KDVHMYFLLNYSHELPRMQAEQRRKAIQERREAKARRQAAAAENGDDAAE 500
501 AIVVPEPEDDDDPELIDYQLKQASNSSPYAVFRKAGICGFAKHFGLTPEQ 550
551 YAENLRDNYQRNEITQESIGPTELAKQYLSPRFMTTDEVIHAAKYVVARQ 600
601 LAQEPLLRKTMREVYFDRARINIRPTKNGMVLIDENSPVYSMKYVAKKPV 650
651 SDLFGDQFIKLMMAEEEKLLEITFLEEFEGNACANGTPGDYVEESKALYQ 700
701 LDQFAKHVQEWNKLRAECVQLALQKWVIPDLIKELRSTLHEEAQQFVLRS 750
751 CTGKLYKWLKVAPYKPQLPPDFGYEEWSTLRGIRVLGLAYDPDHSVAAFC 800
801 AVTTVEGDISDYLRLPNILKRKNSYNLEEKAQKLADLRKLSDFIKMKKPH 850
851 IVVIGAESRDAQNIQADIKEILHELETSEQFPPIEVEIIDNELAKIYANS 900
901 KKGESDFKEYPPLLKQAASLARKMQDPLVEYSQLCDADDEILCLRYHPLQ 950
951 ERVPREQLLEQLSLQFINRTSEVGLDINLMVQNSRTINLLQYICGLGPRK 1000
1001 GQALLKLLKQSNQRLENRTQLVTVCHLGPRVFINCSGFIKIDTSSLGDST 1050
1051 EAYVEVLDGSRVHPETYEWARKMAIDAMEYDDEETNPAGALEEILESPER 1100
1101 LKDLDLDAFAVELERQGFGSKSITLYDIRNELSCLYKDYRTPYTKPSAEE 1150
1151 LFDMLTKETPDSFYVGKCVTAMVTGFTYRRPQGDQLDSANPVRLDSNESW 1200
1201 QCPFCHKDDFPELSEVWNHFDANACPGQPSGVRVRLENGLPGFIHIKNLS 1250
1251 DRQVRNPEERVRVSQMIHVRIIKIDIDRFSVECSSRTADLKDVNNEWRPR 1300
1301 RDNYYDYVTEEQDNRKVSDAKARALKRKIYARRVIAHPSFFNKSYAEVVA 1350
1351 MLAEADQGEVALRPSSKSKDHLTATWKVADDIFQHIDVREEGKENDFSLG 1400
1401 RSLWIGTEEFEDLDEIIARHIMPMALAARELIQYKYYKPNMVTGDENERD 1450
1451 VMEKLLREEKANDPKKIHYFFTASRAMPGKFLLSYLPKTKVRHEYVTVMP 1500
1501 EGYRFRGQIFDTVNSLLRWFKEHWLDPTATPASASASNLTPLHLMRPPPT 1550
1551 ISSSSQTSLGPQAPYSVTGSVTGGTPRSGISSAVGGGGSSAYSITQSITG 1600
1601 YGTSGSSAPGAGVSSSHYGSSSTPSFGAINTPYTPSGQTPFMTPYTPHAS 1650
1651 QTPRYGHNVPSPSSQSSSSQRHHYGSSSGTGSTPRYHDMGGGGGGGVGGG 1700
1701 GGSNAYSMQPHHQQRAKENLDWQLANDAWARRRPQQHQSHQSYHAQQQHH 1750
1751 HSQQQPHMGMSMNMGITMSLGRGTGGGGGGGYGSTPVNDYSTGGGHNRGM 1800
1801 SSKASVRSTPRTNASPHSMNLGDATPLYDEN 1831
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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