 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8CGN4 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MLSATPLYGNVHSWMNSERVRMCGTSEDRKIPVNDGDASKARLELREETP 50
51 LSHSVVDTSGAHRIDGLAALSMDRTGLIREGLRVPGNIVYSGLCGLGSEK 100
101 GREATPSSLSGLGFSSERNPEMQFKPNTPETVEASAVSGKPPNGFSAIYK 150
151 TPPGIQKSAVATAESLGLDRPASDKQSPLNINGASYLRLPWVNPYMEGAT 200
201 PAIYPFLDSPNKYSLNMYKALLPQQSYGLAQPLYSPVCTSGERFLYLPPP 250
251 HYVNPHIPSSLASPMRLSTPSASAAIPPLVHCSDKSLPWKMGVNPGNPVD 300
301 SHSYPHIQNSKQPRVTSAKAVNSGLPGDTALLLPPSPRPSARVHLPTQPA 350
351 AETYSEFHKHYPRISTSPSVTLTKPYMTANSEFSTSRLSNGKYPKALDGG 400
401 DCAQSMPGHTRKTTVQDRKDGGSPPLLEKQTVTKDVTDKPLDLSSKVVDA 450
451 DASKGDHMKKMAPTVLVHSRAASGLVLSGSEIPKETLSPPGNGCSIYRSE 500
501 IISTAPSSWVVPGPSPNEENNGKSLSLKNKALDWAIPQQRSSSCPRMGGT 550
551 DAVVTNVSGSVSSSGRPASASPAPNANANADGTKTSRSSVDTTPSVIQHV 600
601 GQPSSTPAKHGGSTSSKGAKANPEPSFKASENGLPPTSIFLSPNEAFRSP 650
651 AIPYPRSYLPYAAPEGIALSPLSLHGKGPVYPHPVLLPNGSLFPGHLAPK 700
701 PGLPYGLHTSRPEFVTYQDALGLGMVHPMLIPHTPIEITKEEKPERRSRS 750
751 HERARYEDPTLRSRFSEMLEASSTKLHPEVPTDKNLKPNSSWNQGKTGVK 800
801 SDKLVYVDLLREEADTKTDAGAPKAGLVAENVGQDTEATKPSADPVIQQR 850
851 REFISLREELGRITDFHESFTFKQASSQPVFSLGKDSGAAGTNKENLGVQ 900
901 VATPFLETALGSEGPAVTFGKTQEDPKPFCVGGAPPNMDVTPAYTKEGTD 950
951 EAESNDGKVLKPKPSKLAKRIANSAGYVGDRFKCVTTELYADSSQLSREQ 1000
1001 RALQMEGLQEDSILCLPAAYCERAMMRFSELEMKEREGSHPATKDSEVCK 1050
1051 FSPADWERLKGNQEKKPKSVTLEEAIADQNDSERCEYSTGNKHDLFEAPE 1100
1101 DKDLPVEKYFLERPPVSEPPSDQGVVDTPHSPTLRLDRKRKLSGDSTHTE 1150
1151 TAVEELAEDPLKAKRRRISKDDWPEREMTNSSSNHLEDPHCNELTNLKVC 1200
1201 IELTGLHPKKQRHLLHLRERWEQQVSAAESKPGRQSRKEVAQAVQPEVTS 1250
1251 QGTNITEEKPGRKKAEAKGNRGWSEESLKSCDNEQGLPVLSGSPPMKSLS 1300
1301 STNASGKKQTQPSCTPASRLPAKQQKIKESQKTDVLCTGEDEDCQAASPL 1350
1351 QKYTDNIEKPSGKRLCKTKHLIPQESRRSLQITGDYYVENTDTKMTVRRF 1400
1401 RKRPEPSSDYDLSPPAKQEPKPFDRLQQLLPATQATQLPRSNSPQETTQS 1450
1451 RPMPPEARRLIVNKNAGETLLQRAARLGYEEVVLYCLENKVCDVNHRDNA 1500
1501 GYCALHEACARGWLNIVRHLLEYGADVNCSAQDGTRPLHDAVENDHLEIV 1550
1551 RLLLSYGADPTLATYSGRTIMKMTHSELMEKFLTDYLNDLQGRSEDDTSG 1600
1601 AWEFYGSSVCEPDDESGYDVLANPPGPEDPDEEEDTYSDLFEFEFAESSL 1650
1651 LPCYNIQVSVAQGPRNWLLLSDVLKKLKMSSRIFRSNFPNLEIVTIAEAE 1700
1701 FYRQVSTSLLFSCPKDLEAFNPESKELLDLVEFTNELQTLLGSSVEWLHP 1750
1751 SDTGHENYW 1759
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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