 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9R1D7 from www.uniprot.org...
The NucPred score for your sequence is 0.73 (see score help below)
1 MVDKNIYIIQGEINIVVGAIKRNARWSTHIPLDEERDPLLHSFSHLKEVL 50
51 NSVTELSEIEPNVFLRPFLEVIRSEDTTGPITGLALTSVNKFLSYALIDP 100
101 THEGTAEGMENMADAVTHARFVGTDPASDEVVLMKILQVLRTLLLTPVGT 150
151 HLTNESVCEIMQSCFRICFEMRLSELLRKSAEHTLVDMVQLLFTRLPQFK 200
201 EEPKSYVGTNMKKLKMRAGGMSDSSKWKKQKRSPRPPRHMTRVTPGSELP 250
251 APNGATLSCNLTSGMPFIDVPSSISSASSEAASAVVSPCTDSGLELSSQT 300
301 TSKEDLTDLEQAGSPRESTTTESGSNEIGVSDQLDPQEGSHVEKAQSASV 350
351 ESIPEVLEECTSPPDHSASVHDMDYVNPRGVRFTQSSQKEGTALVPYGLP 400
401 CIRELFRFLISLTNPHDRHNSEGMIHMGLHLLTVALESAPVAQCQTLLGL 450
451 IKDEMCRHLFQLLSVERLNLYAASLRVCFLLFESMREHLKFQLEMYMKKL 500
501 MEIITVENPKMPYEMKEMALEAIVQLWRIPSFVTELYINYDCDYYCANLF 550
551 EDLTKLLSKNAFPVSGQLYTTHLLSLDALLTVIDSTEAHCQAKVLNTLTQ 600
601 QEKKETSRPSYEAVDSTQEANSTERATIDGKATGMASDALGLHLQSGGWL 650
651 SAEHGKPRCNDVEEAGDSGADKKFTRKPPRFSCLLPDPRELIEIKNKKKL 700
701 LITGTEQFNQKPKKGIQFLQEKGLLTIPMDNTEVAQWLRENPRLDKKMIG 750
751 EFVSDRKNIDLLESFVSTFSFQGLRLDEALRLYLEAFRLPGEAPVIHRLL 800
801 EAFTEHWRSCNGSPFANSDACFALAYAVIMLNTDQHNHNVRKQNVPMTLE 850
851 EFRKNLKGVNGGKDFEQDILEDMYHAIKNEEIVMPEEQTGLVRENYVWSV 900
901 LLHRGATPEGIFLRVPPGSYDLDLFTMTWGPTIAALSYVFDKSIEETIIQ 950
951 KAISGFRKCAMISAHYGLSDVFDNLIISLCKFTALSSESIENLPTVFGSN 1000
1001 PKAHIAAKTVFHLAHRHGDILREGWKNIMEAVLQLFRAQLLPQAMVEVED 1050
1051 FVDPNGKISLQREEMPSNRGESSVLSFVSWLTLSGPEQSSVRGPSTENQE 1100
1101 AKRVALDCIKQCDPEKMITESKFLQLESLQELMKALVSVTADEETYDEED 1150
1151 AAFCLEMLLRIVLENRDRVGCVWQTVRDHLYHLCVQAQDFCFLVERAVVG 1200
1201 LLRLAIRLLRREEISGQVLLSLRILLLMKPSVLSRVSHQVAYGLHELLKT 1250
1251 NAANIHSGDDWATLFTLLECIGSGVKPPDALQATARADAPDAGAQSDSEL 1300
1301 PSYHQNDVSLDRGYTSDSEVYTDHGRPGKIHRSATDADMVNSGWLVVGKD 1350
1351 DIDNSKAGAGLSRPSPSPLVNQYSLTVGLDLGPHDTKSLLKCVESLSFIV 1400
1401 RDAAHITPDNFELCVKTLRIFVEASLNGGCKSQDKRGKSHKYDSKGNRFK 1450
1451 KKPKEGSVLRRPRTSSQHGTRGGHSDEEEDEGVPASYHTVSLQVSQDLLD 1500
1501 LMHTLHTRAASIYSSWAEEQRHLESGGRKIEADSRTLWAHCWCPLLQGIA 1550
1551 CLCCDARRQVRMQALTYLQRALLVHDLQKLDALEWESCFNKVLFPLLTKL 1600
1601 LENISPADVGGMEETRMRASTLLSKVFLQHLSPLLSLSTFAALWLTILDF 1650
1651 MDKYMHAGSSDLLSEAIPESLKNMLLVMDTAEIFHSADARGGSPSALWEI 1700
1701 TWERIDCFLPHLRDELFKQTVIQDPMPTEPHSQNALASTHLTPAAGDPGH 1750
1751 LPSPEIPSEVGACDSEKPEGTRATSSSSPGSPVASSPSRLSPSPEGPPPL 1800
1801 AQPPLILQPLTSPLQVGVPPMALPIILNPALIEATSPVPLLSTPRPTDPI 1850
1851 PTSEVN 1856
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.) |
Go back to the NucPred Home Page.