| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q01389 from www.uniprot.org...
The NucPred score for your sequence is 0.95 (see score help below)
1 MPFLRKIAGTAHTHSRSDSNSSVKFGHQPTSSVASTKSSSKSPRATSRKS 50
51 IYDDIRSQFPNLTPNSTSSQFYESTPVIEQSFNWTTDDHISAGTLENPTS 100
101 FTNSSYKNDNGPSSLSDSRKSSGGNSVNSLSFDKLILSWDPTDPDEWTMH 150
151 RVTSWFKFHDFPESWILFFKKHQLFGHRFIKLLAYDNFAVYEKYLPQTKT 200
201 ASYTRFQQLLKKTMTKNVTNSHIRQKSASKLKSSRSSSESIKSKLKNSKS 250
251 QEDISNSRSTSESALSPTKSGPSKTDEKNFLHSTSTHQKTKSASSLYRRS 300
301 FISLRGSSSSNASSAKSPSNIKLSIPARPHSIIESNSTLTKSASPPASPS 350
351 YPSIFRRHHKSSSSESSLLNSLFGSGIGEEAPTKPNPQGHSLSSENLAKG 400
401 KSKHYETNVSSPLKQSSLPTSDDKGNLWNKFKRKSQIGVPSPNTVAYVTS 450
451 QETPSLKSNSSTATLTVQTADVNIPSPSSSPPPIPKTANRSLEVISTEDT 500
501 PKISSTTASFKETYPDCINPDKTVPVPVNNQKYSVKNFLLDQKFYPLKKT 550
551 GLNDSENKYILVTKDNVSFVPLNLKSVAKLSSFKESALTKLGINHKNVTF 600
601 HMTDFDCDIGAAIPDDTLEFLKKSLFLNTSGKIYIKDQMKLQQKPKPAPL 650
651 TSENNVPLKSVKSKSSMRSGTSSLIASTDDVSIVTSSSDITSFDEHASGS 700
701 GRRYPQTPSYYYDRVSNTNPTEELNYWNIKEVLSHEENAPKMVFKTSPKL 750
751 ELNLPDKGSKLNIPTPITENESKSSFQVLRKDEGTEIDFNHRRESPYTKP 800
801 ELAPKREAPKPPANTSPQRTLSTSKQNKPIRLVRASTKISRSKRSKPLPP 850
851 QLLSSPIEASSSSPDSLTSSYTPASTHVLIPQPYKGANDVMRRLKTDQDS 900
901 TSTSPSLKMKQKVNRSNSTVSTSNSIFYSPSPLLKRGNSKRVVSSTSAAD 950
951 IFEENDITFADAPPMFDSDDSDDDSSSSDDIIWSKKKTAPETNNENKKDE 1000
1001 KSDNSSTHSDEIFYDSQTQDKMERKMTFRPSPEVVYQNLEKFFPRANLDK 1050
1051 PITEGIASPTSPKSLDSLLSPKNVASSRTEPSTPSRPVPPDSSYEFIQDG 1100
1101 LNGKNKPLNQAKTPKRTKTIRTIAHEASLARKNSVKLKRQNTKMWGTRMV 1150
1151 EVTENHMVSINKAKNSKGEYKEFAWMKGEMIGKGSFGAVYLCLNVTTGEM 1200
1201 MAVKQVEVPKYSSQNEAILSTVEALRSEVSTLKDLDHLNIVQYLGFENKN 1250
1251 NIYSLFLEYVAGGSVGSLIRMYGRFDEPLIKHLTTQVLKGLAYLHSKGIL 1300
1301 HRDMKADNLLLDQDGICKISDFGISRKSKDIYSNSDMTMRGTVFWMAPEM 1350
1351 VDTKQGYSAKVDIWSLGCIVLEMFAGKRPWSNLEVVAAMFKIGKSKSAPP 1400
1401 IPEDTLPLISQIGRNFLDACFEINPEKRPTANELLSHPFSEVNETFNFKS 1450
1451 TRLAKFIKSNDKLNSSKLRITSQENKTE 1478
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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