 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P11046 from www.uniprot.org...
The NucPred score for your sequence is 0.68 (see score help below)
1 MLELRLIVVIVLALLSWQWDPVDSQRPPQHGRRDRPKYPPNKFIKTHPCE 50
51 RSSCYPATGNLLIGRENRLTASSTCGLHSPERFCILSHLQDKKCFLCDTR 100
101 EETKHDPYKNHRIGQIIYKTKPGTNIPTWWQSENGKENATIQLDLEAEFH 150
151 FTHLIITFTTFRPAAMYIERSFDFGQTWHIYRYFAYDCKESFPGVPTVLE 200
201 NITDVMCTSRYSNVEPSRNGEVIFRVLPPNINVTDPYAEHVQNQLKMTNL 250
251 RIQMTKLHKLGDNLLDSRLENEEKYYYGISNMVVRGSCSCYGHASQCLPL 300
301 DPAFSQADNEDGMVHGRCECTHNTKGMNCEECEDFFNDLPWKPAFGKKTN 350
351 ACKKCECNDHAVSCHFDEAVFTASGFVSGGVCDNCLHNTRGQHCEECMPY 400
401 FYRDPEQDITSERVCQPCDCDPQGSSDDGICDSLNELEEGAVAGACHCKA 450
451 FVTGRRCNQCKDGYWNLQSDNPEGCEPCTCNPLGTLNNSGCVMRTGECKC 500
501 KKYVTGKDCNQCMPETYGLSESPEGCSLCNCDAGGSYDNYCDVISGQCRC 550
551 RPHMTGRSCSQPKQNYFIPLLPEVHEAEVVDECISYGANGNCSLVAETPD 600
601 GSFTGIGFTRVPENSELVFTVGDIPRSMPYDAVIRYQSTSRGDWENAFIT 650
651 LVRPDQVDPEGGCGELAAATSSETRIPFSLPDRSRQVVALNEVCLEAGKV 700
701 YKFRIYFERKRHDVDSPTATILVDSLTLIPRIDVTPIFQGSVLADIRKKD 750
751 YEKYNCKSSLYDMNYKSDPKCQNLDNILSVFVHDGASMCNCNPTGSLSKV 800
801 CESNGGYCQCKPNVVGRQCDQCAPGTYGFGPEGCKACDCNSIGSKDKYCD 850
851 LITGQCQCVPNTYGRECNQCQPGYWNFPECRVCQCNGHAATCDPIQGTCI 900
901 DCQDSTTGYSCDSCLDGYYGNPLFGSEIGCRPCRCPETVASGLAHADGCS 950
951 LDTRNNNMLCHCQEGYSGSRCEICADNFFGNPDNGGTCSKCECSNNVDLY 1000
1001 DTGNCDRQTGACLKCLYQTTGDHCELCKDGFFGDALQQNCQQCECDFLGT 1050
1051 NNTIAHCDRFTGQCPCLPNVQGVRCDQCAENHWKIASGEGCESCNCDPIG 1100
1101 ALHEQCNSYTGQCQCKPGFGGRACNQCQAHYWGNPNEKCQPCECDQFGAA 1150
1151 DFQCDRETGNCVCHEGIGGYKCNECARGYIGQFPHCSPCGECFNNWDLIL 1200
1201 SALEDATTATILRAKEIKQVGATGAYTSEFSELDKKLQHIRNLLQNTSVS 1250
1251 LVDIEKLDYETQSLRDQLQASHGRLSETEQNLDDIYNSLSLSGVELESLQ 1300
1301 NHSRLVQQLSKELKENGIQLQESNIEGALNLTRHAYERVSNLSTLKDEAN 1350
1351 ELASNTDRNCKRVENLSNKIQAEADDLANNNKLIEDYRAELTSLTSQIPE 1400
1401 LNNQVCGKPGDPCDSLCGGAGCGHCGGFLSCEHGAKTHSEEALKVAKDAE 1450
1451 TAITSKKDQADQTIRALTQAKLNASEAYEKAKRGFEQSERYLNQTNANIK 1500
1501 LAENLFIALNNFQENKTASPSESKELAQKTLDLDLKLEPEEIETLGDQIN 1550
1551 RAVSSLKNVEAIIYRTKPDLDRVNNLQSIANATKEKADKILDSANSVVES 1600
1601 LAAADESQGKAKDAIQQANSNIELAGQDLEKIDEETYSAEAPANNTAQQV 1650
1651 EKLAKKVQKLQNNIMKNDRDAKEITKEAGSVKLEAMRARGEANNLQSATS 1700
1701 ATNQTLTDRASRSENARERAKQLLQRASKLTVDTNAKLKDLNDLQTVYLN 1750
1751 KNQQLLRLQAEIGPLNKELNEHLIHIKERGSHYRQCYT 1788
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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