 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q7KZ85 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MSDFVESEAEESEEEYNDEGEVVPRVTKKFVEEEDDDEEEEEENLDDQDE 50
51 QGNLKGFINDDDDEDEGEEDEGSDSGDSEDDVGHKKRKRTSFDDRLEDDD 100
101 FDLIEENLGVKVKRGQKYRRVKKMSDDEDDDEEEYGKEEHEKEAIAEEIF 150
151 QDGEGEEGQEAMEAPMAPPEEEEEDDEESDIDDFIVDDDGQPLKKPKWRK 200
201 KLPGYTDAALQEAQEIFGVDFDYDEFEKYNEYDEELEEEYEYEDDEAEGE 250
251 IRVRPKKTTKKRVSRRSIFEMYEPSELESSHLTDQDNEIRATDLPERFQL 300
301 RSIPVKGAEDDELEEEADWIYRNAFATPTISLQESCDYLDRGQPASSFSR 350
351 KGPSTIQKIKEALGFMRNQHFEVPFIAFYRKEYVEPELHINDLWRVWQWD 400
401 EKWTQLRIRKENLTRLFEKMQAYQYEQISADPDKPLADGIRALDTTDMER 450
451 LKDVQSMDELKDVYNHFLLYYGRDIPKMQNAAKASRKKLKRVREEGDEEG 500
501 EGDEAEDEEQRGPELKQASRRDMYTICQSAGLDGLAKKFGLTPEQFGENL 550
551 RDSYQRHETEQFPAEPLELAKDYVCSQFPTPEAVLEGARYMVALQIAREP 600
601 LVRQVLRQTFQERAKLNITPTKKGRKDVDEAHYAYSFKYLKNKPVKELRD 650
651 DQFLKICLAEDEGLLTTDISIDLKGVEGYGNDQTYFEEIKQFYYRDEFSH 700
701 QVQEWNRQRTMAIERALQQFLYVQMAKELKNKLLAEAKEYVIKACSRKLY 750
751 NWLRVAPYRPDQQVEEDDDFMDENQGKGIRVLGIAFSSARDHPVFCALVN 800
801 GEGEVTDFLRLPHFTKRRTAWREEEREKKAQDIETLKKFLLNKKPHVVTV 850
851 AGENRDAQMLIEDVKRIVHELDQGQQLSSIGVELVDNELAILYMNSKKSE 900
901 AEFRDYPPVLRQAVSLARRIQDPLIEFAQVCSSDEDILCLKFHPLQEHVV 950
951 KEELLNALYCEFINRVNEVGVDVNRAIAHPYSQALIQYVCGLGPRKGTHL 1000
1001 LKILKQNNTRLESRTQLVTMCHMGPKVFMNCAGFLKIDTASLGDSTDSYI 1050
1051 EVLDGSRVHPETYEWARKMAVDALEYDESAEDANPAGALEEILENPERLK 1100
1101 DLDLDAFAEELERQGYGDKHITLYDIRAELSCRYKDLRTAYRSPNTEEIF 1150
1151 NMLTKETPETFYIGKLIICNVTGIAHRRPQGESYDQAIRNDETGLWQCPF 1200
1201 CQQDNFPELSEVWNHFDSGSCPGQAIGVKTRLDNGVTGFIPTKFLSDKVV 1250
1251 KRPEERVKVGMTVHCRIMKIDIEKFSADLTCRTSDLMDRNNEWKLPKDTY 1300
1301 YDFDAEAADHKQEEDMKRKQQRTTYIKRVIAHPSFHNINFKQAEKMMETM 1350
1351 DQGDVIIRPSSKGENHLTVTWKVSDGIYQHVDVREEGKENAFSLGATLWI 1400
1401 NSEEFEDLDEIVARYVQPMASFARDLLNHKYYQDCSGGDRKKLEELLIKT 1450
1451 KKEKPTFIPYFICACKELPGKFLLGYQPRGKPRIEYVTVTPEGFRYRGQI 1500
1501 FPTVNGLFRWFKDHYQDPVPGITPSSSSRTRTPASINATPANINLADLTR 1550
1551 AVNALPQNMTSQMFSAIAAVTGQGQNPNATPAQWASSQYGYGGSGGGSSA 1600
1601 YHVFPTPAQQPVATPLMTPSYSYTTPSQPITTPQYHQLQASTTPQSAQAQ 1650
1651 PQPSSSSRQRQQQPKSNSHAAIDWGKMAEQWLQEKEAERRKQKQRLTPRP 1700
1701 SPSPMIESTPMSIAGDATPLLDEMDR 1726
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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