 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9BTW9 from www.uniprot.org...
The NucPred score for your sequence is 0.31 (see score help below)
1 MALSDEPAAGGPEEEAEDETLAFGAALEAFGESAETRALLGRLREVHGGG 50
51 AEREVALERFRVIMDKYQEQPHLLDPHLEWMMNLLLDIVQDQTSPASLVH 100
101 LAFKFLYIITKVRGYKTFLRLFPHEVADVEPVLDLVTIQNPKDHEAWETR 150
151 YMLLLWLSVTCLIPFDFSRLDGNLLTQPGQARMSIMDRILQIAESYLIVS 200
201 DKARDAAAVLVSRFITRPDVKQSKMAEFLDWSLCNLARSSFQTMQGVITM 250
251 DGTLQALAQIFKHGKREDCLPYAATVLRCLDGCRLPESNQTLLRKLGVKL 300
301 VQRLGLTFLKPKVAAWRYQRGCRSLAANLQLLTQGQSEQKPLILTEDDDE 350
351 DDDVPEGVERVIEQLLVGLKDKDTVVRWSAAKGIGRMAGRLPRALADDVV 400
401 GSVLDCFSFQETDKAWHGGCLALAELGRRGLLLPSRLVDVVAVILKALTY 450
451 DEKRGACSVGTNVRDAACYVCWAFARAYEPQELKPFVTAISSALVIAAVF 500
501 DRDINCRRAASAAFQENVGRQGTFPHGIDILTTADYFAVGNRSNCFLVIS 550
551 VFIAGFPEYTQPMIDHLVTMKISHWDGVIRELAARALHNLAQQAPEFSAT 600
601 QVFPRLLSMTLSPDLHMRHGSILACAEVAYALYKLAAQENRPVTDHLDEQ 650
651 AVQGLKQIHQQLYDRQLYRGLGGQLMRQAVCVLIEKLSLSKMPFRGDTVI 700
701 DGWQWLINDTLRHLHLISSHSRQQMKDAAVSALAALCSEYYMKEPGEADP 750
751 AIQEELITQYLAELRNPEEMTRCGFSLALGALPGFLLKGRLQQVLTGLRA 800
801 VTHTSPEDVSFAESRRDGLKAIARICQTVGVKAGAPDEAVCGENVSQIYC 850
851 ALLGCMDDYTTDSRGDVGTWVRKAAMTSLMDLTLLLARSQPELIEAHTCE 900
901 RIMCCVAQQASEKIDRFRAHAASVFLTLLHFDSPPIPHVPHRGELEKLFP 950
951 RSDVASVNWSAPSQAFPRITQLLGLPTYRYHVLLGLVVSLGGLTESTIRH 1000
1001 STQSLFEYMKGIQSDPQALGSFSGTLLQIFEDNLLNERVSVPLLKTLDHV 1050
1051 LTHGCFDIFTTEEDHPFAVKLLALCKKEIKNSKDIQKLLSGIAVFCEMVQ 1100
1101 FPGDVRRQALLQLCLLLCHRFPLIRKTTASQVYETLLTYSDVVGADVLDE 1150
1151 VVTVLSDTAWDAELAVVREQRNRLCDLLGVPRPQLVPQPGAC 1192
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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