 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8VIM6 from www.uniprot.org...
The NucPred score for your sequence is 0.46 (see score help below)
1 MALSLQPQLLLLLSLLPQEVTSAPTGPQSLDAGLSLLKSFVATLDQAPQR 50
51 SLSQSRFSAFLANISSSFQLGRMGEGPVGEPPPLQPPALRLHDFLVTLRG 100
101 SPDWEPMLGLLGDVLALLGQEQTPRDFLVHQAGVLGGLVEALLGALVPGG 150
151 PPAPTRPPCTRDGPSDCVLAADWLPSLMLLLEGTRWQALVQLQPSVDPTN 200
201 ATGLDGREPAPHFLQGLLGLLTPAGELGSEEALWGGLLRTVGAPLYAAFQ 250
251 EGLLRVTHSLQDEVFSIMGQPEPDASGQCQGGNLQQLLLWGMRNNLSWDA 300
301 RALGFLSGSPPPPPALLHCLSRGVPLPRASQPAAHISPRQRRAISVEALC 350
351 ENHSGPEPPYSISNFSIYLLCQHIKPATPRPPPTTPRPPPTTPQPPPTTT 400
401 QPIPDTTQPPPVTPRPPPTTPQPPPSTAVICQTAVWYAVSWAPGARGWLQ 450
451 ACHDQFPDQFLDMICGNLSFSALSGPSRPLVKQLCAGLLPPPTSCPPGLI 500
501 PVPLTPEIFWGCFLENETLWAERLCVEDSLQAVPPRNQAWVQHVCRGPTL 550
551 DATDFPPCRVGPCGERCPDGGSFLLMVCANDTLYEALVPFWAWLAGQCRI 600
601 SRGGNDTCFLEGMLGPLLPSLPPLGPSPLCLAPGPFLLGMLSQLPRCQSS 650
651 VPALAHPTRLHYLLRLLTFLLGPGTGGAETQGMLGQALLLSSLPDNCSFW 700
701 DAFRPEGRRSVLRTVGEYLQREEPTPPGLDSSLSLGSGMSKMELLSCFSP 750
751 VLWDLLQREKSVWALRTLVKAYLRMPPEDLQQLVLSAEMEAAQGFLTLML 800
801 RSWAKLKVQPSEEQAMGRLTALLLQRYPRLTSQLFIDMSPLIPFLAVPDL 850
851 MRFPPSLLANDSVLAAIRDHSSGMKPEQKEALAKRLLAPELFGEVPDWPQ 900
901 ELLWAALPLLPHLPLESFLQLSPHQIQALEDSWPVADLGPGHARHVLRSL 950
951 VNQSMEDGEEQVLRLGSLACFLSPEELQSLVPLSDPMGPVEQGLLECAAN 1000
1001 GTLSPEGRVAYELLGVLRSSGGTVLSPRELRVWAPLFPQLGLRFLQELSE 1050
1051 TQLRAMLPALQGASVTPAQAVLLFGRLLPKHDLSLEELCSLHPLLPGLSP 1100
1101 QTLQAIPKRVLVGACSCLGPELSRLSACQIAALLQTFRVKDGVKNMGAAG 1150
1151 AGSAVCIPGQPTTWPDCLLPLLPLKLLQLDAAALLANRRLYRQLPWSEQQ 1200
1201 AQFLWKKMQVPTNLSLRNLQALGNLAGGMTCEFLQQISSMVDFLDVVHML 1250
1251 YQLPTGVRESLRACIWTELQRRMTMPEPELTTLGPELSELDTKLLLDLPI 1300
1301 QLMDRLSNDSIMLVVEMVQGAPEQLLALTPLHQTALAERALKNLAPKETP 1350
1351 ISKEVLETLGPLVGFLGIESTRRIPLPILLSHLSQLQGFCLGETFATELG 1400
1401 WLLLQEPVLGKPELWSQDEIEQAGRLVFTLSAEAISSIPREALGPETLER 1450
1451 LLGKHQSWEQSRVGHLCGESQLAHKKAALVAGIVHPAAEGLQEPVPNCAD 1500
1501 IRGTFPAAWSATQISEMELSDFEDCLSLFAGDPGLGPEELRAAMGKAKQL 1550
1551 WGPPRGFRPEQILQLGRLLIGLGERELQELTLVDWGVLSSLGQIDGWSSM 1600
1601 QLRAVVSSFLRQSGRHVSHLDFIYLTALGYTVCGLRPEELQHISSWEFSQ 1650
1651 AALFLGSLHLPCSEEQLEVLAYLLVLPGGFGPVSNWGPEIFTEIGTIAAG 1700
1701 IPDLALSALLRGQIQGLTPLAISVIPAPKFAVVFNPIQLSSLTRGQAVAV 1750
1751 TPEQLAYLSPEQRRAVAWAQHEGKEIPEQLGRNSAWGLYDWFQASWALAL 1800
1801 PVSIFGHLL 1809
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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