 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9M3J5 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MIFQSFLLGNLVSLCMKIINSVVVVGLYYGFLTTFSIGPSYLFLLRAQVM 50
51 EEGEEGTEKKVSGTTGFIMGQLMMFISIYYTPLHLALGRPHTITVLALPY 100
101 LLFHFFWNNHKHFFDYGSTSRNSMRNLSIQCVFLNNLIFQLFNYFILPSS 150
151 MLARLVNIYMFRCNNKMLFVTSSFVGWLIGHILFMKWVGLVLVWIQQNNS 200
201 IRSNKYLVSELRNSMARIFSILFFITCVYYLGRMPSPIFTNKLKQMLETN 250
251 EIEEETNLEIEKTSETKETKQEEEGFTEEDPSPSLFSEEKEDPDKIDETE 300
301 KIRVNGKDKTKDEFHLKEACYKNSPTSYSGNQDISKLEILKKEKKILFWF 350
351 QKPLIFLLFDYKRWNRPMRYIKNNRFENAVRNEMSQYFFYTCQNDGKQRI 400
401 SFTYPPSLSIFWEMIQRKISLATTEKFLYDDELYNYWIYTNEQKKNSLSN 450
451 EFANRITVLDKGLFYIDVLDKKTRLCKSKNEYLQKDHDPLLNGSYRGIIK 500
501 KTLLPFINNDETTVKKLIDEIFINKIHSVLGNCNNYQEFEYKKDPFKKNP 550
551 ISSKIRHFVTLMSQFDGESTFNQKGISLLSEHKQICSEDPEIFFKFLVDT 600
601 IIADSFTQTIPKESIGIKEISKKVPHWSYQLIDESEQEEMENEKQVSWPH 650
651 QIRSRSGKEVVFFTDKQENTDNPTPNTADISEQADEVVLTRYPQESDFRR 700
701 DIIKGSMRSQRRKIVIWELFQANIHSPLFLDRTNKSSFFSITFSRLIKRI 750
751 FKNYMGKNPELDISNYKEEELKKKEKAKEHKKDKEKKQEQIRLDIAETWD 800
801 TIPGAQIIRSLILLTQSILRKYILLPLLITGKNIGRILLFQLPEWSDDFK 850
851 EWTSEMHIKCTYNGVQLSEKEFPKNWLTDGMQIKILSPFCLKPWHKSMIR 900
901 PYHQDKKKKEQNQIDAFCFLTVVGLETDIPFGPPRKRPSFFQPIFKQLDK 950
951 KIEKLIKGNFQVRKRLKEKILFFLKLQNETNNWIIEIFPFFKKIIRKMST 1000
1001 VNTIGVFGLKEASSEIKSEKDSRIKNHMIHESSVQIRFLNQTNSSVTEKK 1050
1051 MKDLANRTRIIKNKIEKISNDKLKMSPKKTRYGTKNLGQILKRRNARLIR 1100
1101 NSNYILKFFRERIYGDIFLYIINIPKINTQLFLESTKNGIDKSIYNNESI 1150
1151 TKTNKNRIQFISTINKKFLPFLSTSKNNSKIISDFSFLSQAYVFYKLSQA 1200
1201 KILNLYKLRLVLQYRGISLFLKNEIKDFFGTQGITNSELKTKKLPNSGMN 1250
1251 QWKNWLKLKNNYQYNLSQLKWSRLVPQKWRNRVTEHCEVENTNLYQNEEL 1300
1301 INSKKHLLLLPDQKYNFQKNYRYDVLSYKFFNYKNKNDSYRYSYGLPFQV 1350
1351 NKNQEFSYTYNYNINNNKFIDMWWNIPISNFSYLEKTKIMDIDKNIDRKY 1400
1401 LDFKILDFSLRNKIDIEDWIDISTSINENTKTEPRNYQIVEKINKKSLVY 1450
1451 STIYQEIKQSDQKNKLFDWMGMNEKILSRPISNLEFWFFSEFFSFYNAYK 1500
1501 MKPWVIPINLLFSNSNVSEKFSKNKSINRKKKTNPFIPSNEKKSFELENR 1550
1551 NQDEKELVSKEDLGSYVQENYEKDIEEDYISFIDIKKPIKQKQPKSVIEA 1600
1601 EFDLFLKRYLLFQLKWADSLNEKLMDNIQVYCLVLRLINPIEILISSIER 1650
1651 KELSMDIMLDRKDFNCPNWKQKRVLIIEPIRLSIRGDGQFLLYQTIGISL 1700
1701 VHKSKHQNNQKRYSENVDKKFLGERNKNNFDLLAPENLLSPRRRRELRIL 1750
1751 LCLNSRNNNGVNTNPMENRVKNCNQFFDEKKDLDRDKNTLRNLKFFLWPN 1800
1801 YRLEDLACMNRFWFDTNNGSRFSILRIHMYPQF 1833
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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