 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9Y4D7 from www.uniprot.org...
The NucPred score for your sequence is 0.72 (see score help below)
1 MAPRAAGGAPLSARAAAASPPPFQTPPRCPVPLLLLLLLGAARAGALEIQ 50
51 RRFPSPTPTNNFALDGAAGTVYLAAVNRLYQLSGANLSLEAEAAVGPVPD 100
101 SPLCHAPQLPQASCEHPRRLTDNYNKILQLDPGQGLVVVCGSIYQGFCQL 150
151 RRRGNISAVAVRFPPAAPPAEPVTVFPSMLNVAANHPNASTVGLVLPPAA 200
201 GAGGSRLLVGATYTGYGSSFFPRNRSLEDHRFENTPEIAIRSLDTRGDLA 250
251 KLFTFDLNPSDDNILKIKQGAKEQHKLGFVSAFLHPSDPPPGAQSYAYLA 300
301 LNSEARAGDKESQARSLLARICLPHGAGGDAKKLTESYIQLGLQCAGGAG 350
351 RGDLYSRLVSVFPARERLFAVFERPQGSPAARAAPAALCAFRFADVRAAI 400
401 RAARTACFVEPAPDVVAVLDSVVQGTGPACERKLNIQLQPEQLDCGAAHL 450
451 QHPLSILQPLKATPVFRAPGLTSVAVASVNNYTAVFLGTVNGRLLKINLN 500
501 ESMQVVSRRVVTVAYGEPVHHVMQFDPADSGYLYLMTSHQMARVKVAACN 550
551 VHSTCGDCVGAADAYCGWCALETRCTLQQDCTNSSQQHFWTSASEGPSRC 600
601 PAMTVLPSEIDVRQEYPGMILQISGSLPSLSGMEMACDYGNNIRTVARVP 650
651 GPAFGHQIAYCNLLPRDQFPPFPPNQDHVTVEMSVRVNGRNIVKANFTIY 700
701 DCSRTAQVYPHTACTSCLSAQWPCFWCSQQHSCVSNQSRCEASPNPTSPQ 750
751 DCPRTLLSPLAPVPTGGSQNILVPLANTAFFQGAALECSFGLEEIFEAVW 800
801 VNESVVRCDQVVLHTTRKSQVFPLSLQLKGRPARFLDSPEPMTVMVYNCA 850
851 MGSPDCSQCLGREDLGHLCMWSDGCRLRGPLQPMAGTCPAPEIHAIEPLS 900
901 GPLDGGTLLTIRGRNLGRRLSDVAHGVWIGGVACEPLPDRYTVSEEIVCV 950
951 TGPAPGPLSGVVTVNASKEGKSRDRFSYVLPLVHSLEPTMGPKAGGTRIT 1000
1001 IHGNDLHVGSELQVLVNDTDPCTELMRTDTSIACTMPEGALPAPVPVCVR 1050
1051 FERRGCVHGNLTFWYMQNPVITAISPRRSPVSGGRTITVAGERFHMVQNV 1100
1101 SMAVHHIGREPTLCKVLNSTLITCPSPGALSNASAPVDFFINGRAYADEV 1150
1151 AVAEELLDPEEAQRGSRFRLDYLPNPQFSTAKREKWIKHHPGEPLTLVIH 1200
1201 KEQDSLGLQSHEYRVKIGQVSCDIQIVSDRIIHCSVNESLGAAVGQLPIT 1250
1251 IQVGNFNQTIATLQLGGSETAIIVSIVICSVLLLLSVVALFVFCTKSRRA 1300
1301 ERYWQKTLLQMEEMESQIREEIRKGFAELQTDMTDLTKELNRSQGIPFLE 1350
1351 YKHFVTRTFFPKCSSLYEERYVLPSQTLNSQGSSQAQETHPLLGEWKIPE 1400
1401 SCRPNMEEGISLFSSLLNNKHFLIVFVHALEQQKDFAVRDRCSLASLLTI 1450
1451 ALHGKLEYYTSIMKELLVDLIDASAAKNPKLMLRRTESVVEKMLTNWMSI 1500
1501 CMYSCLRETVGEPFFLLLCAIKQQINKGSIDAITGKARYTLSEEWLLREN 1550
1551 IEAKPRNLNVSFQGCGMDSLSVRAMDTDTLTQVKEKILEAFCKNVPYSQW 1600
1601 PRAEDVDLEWFASSTQSYILRDLDDTSVVEDGRKKLNTLAHYKIPEGASL 1650
1651 AMSLIDKKDNTLGRVKDLDTEKYFHLVLPTDELAEPKKSHRQSHRKKVLP 1700
1701 EIYLTRLLSTKGTLQKFLDDLFKAILSIREDKPPLAVKYFFDFLEEQAEK 1750
1751 RGISDPDTLHIWKTNSLPLRFWVNILKNPQFVFDIDKTDHIDACLSVIAQ 1800
1801 AFIDACSISDLQLGKDSPTNKLLYAKEIPEYRKIVQRYYKQIQDMTPLSE 1850
1851 QEMNAHLAEESRKYQNEFNTNVAMAEIYKYAKRYRPQIMAALEANPTARR 1900
1901 TQLQHKFEQVVALMEDNIYECYSEA 1925
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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