 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q00706 from www.uniprot.org...
The NucPred score for your sequence is 0.37 (see score help below)
1 MTPSPFLDAVDAGLSRLYACFGGQGPSNWAGLDELVHLSHAYADCAPIQD 50
51 LLDSSARRLESLAAIPHRSSFFAGRGFQLQAWLNDAAASAPLPEDLALSP 100
101 YSFPINTLLSLLHYAITAYSLQLDPGQLRQKLQGAIGHSQGVFVAAAIAI 150
151 SHTDHGWPSFYRAADLALQLSFWVGLESHHASPRSILCANEVIDCLENGE 200
201 GAPSHLLSVTGLDINHLERLVRKLNDQGGDSLYISLINGHNKFVLAGAPH 250
251 ALRGVCIALRSVKASPELDQSRVPFPLRRSVVDVQFLPVSAPYHSSLLSS 300
301 VELRVTDAIGGLRLRGNDLAIPVYCQANGSLRNLQDYGTHDILLTLIQSV 350
351 TVERVNWPALCWAMNDATHVLSFGPGAVGSLVQDVLEGTGMNVVNLSGQS 400
401 MASNLSLLNLSAFALPLGKDWGRKYRPRLRKAAEGSAHASIETKMTRLLG 450
451 TPHVMVAGMTPTTCSPELVAAIIQADYHVEFACGGYYNRATLETALRQLS 500
501 RSIPPHRSITCNVIYASPKALSWQIQVLRRLIMEEGLPIDGITVGAGIPS 550
551 PEVVKEWIDMLAISHIWFKPGSVDAIDRVLTIARQYPTLPVGIQWTGGRA 600
601 GGHHSCEDFHLPILDCYARIRNCENVILVAGSGFGGAEDTWPYMNGSWSC 650
651 KLGYAPMPFDGILLGSRMMVAREAKTSFAVKQLIVEAPGVKDDGNDNGAW 700
701 AKCEHDAVGGVISVTSEMGQPIHVLATRAMRLWKEFDDRFFSIRDPKRLK 750
751 AALKQHRVEIINRLNNDFARPWFAQTDSSKPTEIEELSYRQVLRRLCQLT 800
801 YVQHQARWIDSSYLSLVHDFLRLAQGRLGSGSEAELRFLSCNTPIELEAS 850
851 FDAAYGVQGDQILYPEDVSLLINLFRRQGQKPVPFIPRLDADFQTWFKKD 900
901 SLWQSEDVDAVVDQDAQRVCIIQGPVAVRHSRVCDEPVKDILDGITEAHL 950
951 KMMLKEAASDNGYTWANQRDEKGNRLPGIETSQEGSLCRYYLVGPTLPST 1000
1001 EAIVEHLVGECAWGYAALSQKKVVFGQNRAPNPIRDAFKPDIGDVIEAKY 1050
1051 MDGCLREITLYHSLRRQGDPRAIRAALGLIHLDGNKVSVTLLTRSKGKRP 1100
1101 ALEFKMELLGGTMGPLILKMHRTDYLDSVRRLYTDLWIGRDLPSPTSVGL 1150
1151 NSEFTGDRVTITAEDVNTFLAIVGQAGPARCRAWGTRGPVVPIDYAVVIA 1200
1201 WTALTKPILLEALDADPLRLLHQSASTRFVPGIRPLHVGDTVTTSSRITE 1250
1251 RTITTIGQRVEISAELLREGKPVVRLQTTFIIQRRPEESVSQQQFRCVEE 1300
1301 PDMVIRVDSHTKLRVLMSRKWFLLDGPCSDLIGKILIFQLHSQTVFDAAG 1350
1351 APASLQVSGSVSLAPSDTSVVCVSSVGTRIGRVYMEEEGFGANPVMDFLN 1400
1401 RHGAPRVQRQPLPRAGWTGDDAASISFTAPAQSEGYAMVSGDTNPIHVCP 1450
1451 LFSRFAGLGQPVVHGLHLSATVRRILEWIIGDNERTRFCSWAPSFDGLVR 1500
1501 ANDRLRMEIQHFAMADGCMVVHVRVLKESTGEQVMHAEAVLEQAQTTYVF 1550
1551 TGQGTQERGMGMALYDTNAAARAVWDRAERHFRSQYGISLLHIVRENPTS 1600
1601 LTVNFGSRRGRQIRDIYLSMSDSDPSMLPGLTRDSRSYTFNYPSGLLMST 1650
1651 QFAQPALAVMEIAEYAHLQAQGVVQTQAIFAGHSLGEYSSLGACTTIMPF 1700
1701 ESLLSLILYRGLKMQNTLPRNANGRTDYGMVAADPSRIRSDFTEDRLIEL 1750
1751 VRLVSQATGVLLEVVNYNVHSRQYVCAGHVRSLWVLSHACDDLSRSTSPN 1800
1801 SPQTMSECIAHHIPSSCSVTNETELSRGRATIPLAGVDIPFHSQMLRGHI 1850
1851 DGYRQYLRHHLRVSDIKPEELVGRWIPNVTGKPFALDAPYIRLVQGVTQS 1900
1901 RPLLELLRRVEENR 1914
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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