 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8NI35 from www.uniprot.org...
The NucPred score for your sequence is 0.48 (see score help below)
1 MPENPATDKLQVLQVLDRLKMKLQEKGDTSQNEKLSMFYETLKSPLFNQI 50
51 LTLQQSIKQLKGQLNHIPSDCSANFDFSRKGLLVFTDGSITNGNVHRPSN 100
101 NSTVSGLFPWTPKLGNEDFNSVIQQMAQGRQIEYIDIERPSTGGLGFSVV 150
151 ALRSQNLGKVDIFVKDVQPGSVADRDQRLKENDQILAINHTPLDQNISHQ 200
201 QAIALLQQTTGSLRLIVAREPVHTKSSTSSSLNDTTLPETVCWGHVEEVE 250
251 LINDGSGLGFGIVGGKTSGVVVRTIVPGGLADRDGRLQTGDHILKIGGTN 300
301 VQGMTSEQVAQVLRNCGNSVRMLVARDPAGDISVTPPAPAALPVALPTVA 350
351 SKGPGSDSSLFETYNVELVRKDGQSLGIRIVGYVGTSHTGEASGIYVKSI 400
401 IPGSAAYHNGHIQVNDKIVAVDGVNIQGFANHDVVEVLRNAGQVVHLTLV 450
451 RRKTSSSTSPLEPPSDRGTVVEPLKPPALFLTGAVETETNVDGEDEEIKE 500
501 RIDTLKNDNIQALEKLEKVPDSPENELKSRWENLLGPDYEVMVATLDTQI 550
551 ADDAELQKYSKLLPIHTLRLGVEVDSFDGHHYISSIVSGGPVDTLGLLQP 600
601 EDELLEVNGMQLYGKSRREAVSFLKEVPPPFTLVCCRRLFDDEASVDEPR 650
651 RTETSLPETEVDHNMDVNTEEDDDGELALWSPEVKIVELVKDCKGLGFSI 700
701 LDYQDPLDPTRSVIVIRSLVADGVAERSGGLLPGDRLVSVNEYCLDNTSL 750
751 AEAVEILKAVPPGLVHLGICKPLVEDNEEESCYILHSSSNEDKTEFSGTI 800
801 HDINSSLILEAPKGFRDEPYFKEELVDEPFLDLGKSFHSQQKEIEQSKEA 850
851 WEMHEFLTPRLQEMDEEREILVDEEYELYQDPSPSMELYPLSHIQEATPV 900
901 PSVNELHFGTQWLHDNEPSESQEARTGRTVYSQEAQPYGYCPENVMKENF 950
951 VMESLPSVPSTEGNSQQGRFDDLENLNSLAKTSLDLGMIPNDVQGPSLLI 1000
1001 DLPVVAQRREQEDLPLYQHQATRVISKASAYTGMLSSRYATDTCELPERE 1050
1051 EGEGEETPNFSHWGPPRIVEIFREPNVSLGISIVGGQTVIKRLKNGEELK 1100
1101 GIFIKQVLEDSPAGKTNALKTGDKILEVSGVDLQNASHSEAVEAIKNAGN 1150
1151 PVVFIVQSLSSTPRVIPNVHNKANKITGNQNQDTQEKKEKRQGTAPPPMK 1200
1201 LPPPYKALTDDSDENEEEDAFTDQKIRQRYADLPGELHIIELEKDKNGLG 1250
1251 LSLAGNKDRSRMSIFVVGINPEGPAAADGRMRIGDELLEINNQILYGRSH 1300
1301 QNASAIIKTAPSKVKLVFIRNEDAVNQMAVTPFPVPSSSPSSIEDQSGTE 1350
1351 PISSEEDGSVEVGIKQLPESESFKLAVSQMKQQKYPTKVSFSSQEIPLAP 1400
1401 ASSYHSTDADFTGYGGFQAPLSVDPATCPIVPGQEMIIEISKGRSGLGLS 1450
1451 IVGGKDTPLNAIVIHEVYEEGAAARDGRLWAGDQILEVNGVDLRNSSHEE 1500
1501 AITALRQTPQKVRLVVYRDEAHYRDEENLEIFPVDLQKKAGRGLGLSIVG 1550
1551 KRNGSGVFISDIVKGGAADLDGRLIQGDQILSVNGEDMRNASQETVATIL 1600
1601 KCAQGLVQLEIGRLRAGSWTSARTTSQNSQGSQQSAHSSCHPSFAPVITG 1650
1651 LQNLVGTKRVSDPSQKNSGTDMEPRTVEINRELSDALGISIAGGRGSPLG 1700
1701 DIPVFIAMIQASGVAARTQKLKVGDRIVSINGQPLDGLSHADVVNLLKNA 1750
1751 YGRIILQVVADTNISAIAAQLENMSTGYHLGSPTAEHHPEDTEEQLQMTA 1800
1801 D 1801
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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