 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q76E23 from www.uniprot.org...
The NucPred score for your sequence is 0.84 (see score help below)
1 MSYNQSRPDRSETQYRRTGRSTGNQQQQQQHRSSSAAGYGKGAGAPGSAP 50
51 APSTYPDNSSLSSNRSFKKPGNAQGGGQPRVNLPPVNHPNNHNNGPNAHS 100
101 RSQVTGEPGVGGPTNPTESFNRNTGPIPKAPTSQSTVMSSKINETPNTAK 150
151 VAASGDASQAFPLQFGSLGPDLMVPARTTSAPPNMDDQKRAQMQQSSLRT 200
201 ASNVPASVPKKDSSNKGADNQLMRKEGHNPSSEKADIQVPHIAPPSQTQK 250
251 SPITNIRMPSVQTPYQHTQVPHPVHFGGPNMHMQTPVTATSFQMPMPMAL 300
301 SMGNTPQIPPQVFYQGHPPHPMHHQGMMHQAQGHGFATPMGAQIHPQLGH 350
351 VGVGLSPQYPQQQGGKYGGARKTTPVKITHPDTHEELRLDRRGDPYSEGD 400
401 STALKPHSNPPPRSQPVSSFAPRPVNLVQPSYNSNTMIYPPVSVPLNNGP 450
451 MSSAQAPRYHYPVIDGSQRVQLINQPAHTAPQLIRPAAPAHLSSDSTSSV 500
501 KARNAQNVMSSALPVNAKVSVKPAGVSEKLGSPKDRSHGEVNISLSQKNV 550
551 EACSLSSSQQPKPSFVSGVPNSSAPPAKSPVETVPLAKSSVETVPPVKSS 600
601 VETAPVTTTEIRRAEMVSESISVEDQTCKVEPPHNLTENRGQTMPDSLVS 650
651 DPETATVAAKENLSLPATNGFRKQLLKVSTTSDAPTSDSVDTSIDKSTEG 700
701 SSHASSEISGSSPQEKDLKCDNRTASDKLDERSVISDAKHETLSGVLEKA 750
751 QNEVDGATDVCPVSEKLAVTDDTSSDLPHSTHVLSSTVPLGHSETHKSAV 800
801 ETNTRRNTSTKGKKKIKEILQKADAAGTTSDLYMAYKGPEEKKESSNVVH 850
851 DVSNQNLLPAIPQAVEAIVDTEPVKNEPEDWEDAADVSTPKLETADNSVN 900
901 AKRGSSDEVSDNCINTEKKYSRDFLLKFADLCTALPEGFDVSPDIANALI 950
951 VAYMGASHHEHDSYPTPGKVMDRQASGARLDRRPSNVAGDDRWTKNQGSL 1000
1001 PAGYGGNVGFRPGQGGNSGVLRNPRMQGPIISRPMQPVGPMGGMGRNTPD 1050
1051 LERWQRGSNFQQKGLFPSPHTPMQVMHKAERKYQVGTIADEEQAKQRQLK 1100
1101 SILNKLTPQNFEKLFEQVKSVNIDNAVTLSGVISQIFDKALMEPTFCEMY 1150
1151 ADFCFHLSGALPDFNENGEKITFKRLLLNKCQEEFERGEKEEEEASRVAE 1200
1201 EGQVEQTEEEREEKRLQVRRRMLGNIRLIGELYKKRMLTEKIMHACIQKL 1250
1251 LGYNQDPHEENIEALCKLMSTIGVMIDHNKAKFQMDGYFEKMKMLSCKQE 1300
1301 LSSRVRFMLINAIDLRKNKWQERMKVEGPKKIEEVHRDAAQERQTQANRL 1350
1351 SRGPSMNSSGRRGHMEFSSPRGGGGMLSPPAAQMGSYHGPPQGRGFSNQD 1400
1401 IRFDDRPSYEPRMVPMPQRSVCEEPITLGPQGGLGQGMSIRRPAVASNTY 1450
1451 QSDATQAGGGDSRRPAGGLNGFGSHRPASPVTHGRSSPQERGTAYVHREF 1500
1501 ASLSRASDLSPEVSSARQVLQGPSATVNSPRENALSEEQLENLSLSAIKE 1550
1551 YYSARDENEIGMCMKDMNSPAYHPTMISLWVTDSFERKDKERDLLAKLLV 1600
1601 NLVKSADNALNEVQLVKGFESVLKTLEDAVNDAPKAAEFLGRIFGKSVTE 1650
1651 KVVTLTEIGRLIQEGGEEPGSLIEFGLGGDVLGSVLEMIKTEAGEETLVE 1700
1701 IRRSSGLRIENFKPHAPNRSKILEKFT 1727
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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