 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q99102 from www.uniprot.org...
The NucPred score for your sequence is 0.46 (see score help below)
1 MKGARWRRVPWVSLSCLCLCLLPHVVPGTTEDTLITGSKTAAPVTSTGST 50
51 TATLEGQSTAASSRTSNQDISASSQNHQTKSTETTSKAQTDTLTQMMTST 100
101 LFSSPSVHNVMETAPPDEMTTSFPSSVTNTLMMTSKTITMTTSTDSTLGN 150
151 TEETSTAGTESSTPVTSAVSITAGQEGQSRTTSWRTSIQDTSASSQNHWT 200
201 RSTQTTRESQTSTLTHRTTSTPSFSPSVHNVTGTVSQKTSPSGETATSSL 250
251 CSVTNTSMMTSEKITVTTSTGSTLGNPGETSSVPVTGSLMPVTSAALVTF 300
301 DPEGQSPATFSRTSTQDTTAFSKNHQTQSVETTRVSQINTLNTLTPVTTS 350
351 TVLSSPSGFNPSGTVSQETFPSGETTTSSPSSVSNTFLVTSKVFRMPTSR 400
401 DSTLGNTEETSLSVSGTISAITSKVSTIWWSDTLSTALSPSSLPPKISTA 450
451 FHTQQSEGAETTGRPHERSSFSPGVSQEIFTLHETTTWPSSFSSKGHTTW 500
501 SQTELPSTSTGAATRLVTGNPSTGTAGTIPRVPSKVSAIGEPGEPTTYSS 550
551 HSTTLPKTTGAGAQTQWTQETGTTGEALLSSPSYSVTQMIKTATSPSSSP 600
601 MLDRHTSQQITTAPSTNHSTIHSTSTSPQESPAVSQRGHTQAPQTTQESQ 650
651 TTRSVSPMTDTKTVTTPGSSFTASGHSPSEIVPQDAPTISAATTFAPAPT 700
701 GDGHTTQAPTTALQAAPSSHDATLGPSGGTSLSKTGALTLANSVVSTPGG 750
751 PEGQWTSASASTSPDTAAAMTHTHQAESTEASGQTQTSEPASSGSRTTSA 800
801 GTATPSSSGASGTTPSGSEGISTSGETTRFSSNPSRDSHTTQSTTELLSA 850
851 SASHGAIPVSTGMASSIVPGTFHPTLSEASTAGRPTGQSSPTSPSASPQE 900
901 TAAISRMAQTQRTRTSRGSDTISLASQATDTFSTVPPTPPSITSTGLTSP 950
951 QTETHTLSPSGSGKTFTTALISNATPLPVTYASSASTGHTTPLHVTDASS 1000
1001 VSTGHATPLPVTSPSSVSTGHTTPLPVTDTSSESTGHVTPLPVTSFSSAS 1050
1051 TGDSTPLPVTDTSSASTGHVTPLPVTSLSSASTGDTTPLPVTDTSSASTG 1100
1101 HATSLPVTDTSSVSTGHTTPLPVTDTSSASTGHATSLPVTDTSSVSTGHT 1150
1151 TPLHVTDASSASTGQATPLPVTSLSSVSTGDTTPLPVTSPSSASTGHATP 1200
1201 LLVTDTSSASTGHATPLPVTDASSVSTDHATSLPVTIPSAASTGHTTPLP 1250
1251 VTDTSSASTGQATSLLVTDTSSVSTGDTTPLPVTSTSSASTGHVTPLHVT 1300
1301 SPSSASTGHATPLPVTSLSSASTGDTMPLPVTSPSSASTGDTTPLPVTDA 1350
1351 SSVSTGHTTPLHVTDASSASTGQATPLPVTSLSSVSTGDTTPLPVTSPSS 1400
1401 ASTGHATPLLVTDTSSASTGHATPLPVTDASSVSTDHATSLPVTIPSAAS 1450
1451 TGHTTPLPVTDTSSASTGQATSLLVTDTSSVSTGDTTPLPVTSTSSASTG 1500
1501 HVTPLHVTSPSSASTGHATPLPVTSLSSASTGDTMPLPVTSPSSASTGDT 1550
1551 TPLPVTDASSVSTGHTTPLPVTSPSSASTGHTTPLPVTDTSSASKGDTTP 1600
1601 LPVTSPSSASTGHTTPLPVTDTSSASTGDTTPLPVTNASSLSTGHATPLH 1650
1651 VTSPSSASTGHATPLPVTSTSSASTGHATPLPVTGLSSATTDDTTRLPVT 1700
1701 DVSSASTGQATPLPVTSLSSVSTGDTTPLPVTSPSSASTGHASPLLVTDA 1750
1751 SSASTGQATPLPVTDTSSVSTAHATPLPVTGLSSASTDDTTRLPVTDVSS 1800
1801 ASTGQAIPLPVTSPSSASTGDTTPLPVTDASSASTGDTTSLPVTIPSSAS 1850
1851 SGHTTSLPVTDASSVSTGHATSLLVTDASSVSTGDTTPLPVTDTNSASTG 1900
1901 DTTPLHVTDASSVSTGHATSLPVTSLSSASTGDTTPLPVTSPSSASSGHT 1950
1951 TPLPVTDASSVPTGHATSLPVTDASSVSTGHATPLPVTDASSVSTGHATP 2000
2001 LPVTDTSSVSTGQATPLPVTSLSSASTGDTTPLPVTDTSSASTGQDTPLP 2050
2051 VTSLSSVSTGDTTPLPVTNPSSASTGHATPLLVTDASSISTGHATSLLVT 2100
2101 DASSVSTGHATALHDTDASSLSTGDTTPLPVTSPSSTSTGDTTPLPVTET 2150
2151 SSVSTGHATSLPVTDTSSASTGHATSLPVTDTSSASTGHATPLPVTDTSS 2200
2201 ASTGQATPLPVTSPSSASTGHAIPLLVTDTSSASTGQATPLPVTSLSSAS 2250
2251 TGDTTPLPVTDASSVSTGHATSLPVTSLSSVSTGDTTPLPVTSPSSASTG 2300
2301 HATPLHVTDASSASTGHATPLPVTSLSSASTGDTTPLPVTSPSSASTGHA 2350
2351 TPLHVTDASSVSTGDTTPLPVTSSSSASSGHTTPLPVTDASSASTGDTTP 2400
2401 LPVTDTSSASTGHATHLPVTGLSSASTGDTTRLPVTNVSSASTGHATPLP 2450
2451 VTSTSSASTGDTTPLPGTDTSSVSTGHTTPLLVTDASSVSTGDTTRLPVT 2500
2501 SPSSASTGHTTPLPVTDTPSASTGDTTPLPVTNASSLSTRHATSLHVTSP 2550
2551 SSASTGHATSLPVTDTSAASTGHATPLPVTSTSSASTGDTTPLPVTDTYS 2600
2601 ASTGQATPLPVTSLSSVSTGDTTPLPVTSPSSASTGHATPLLVTDASSAS 2650
2651 TGQATPLPVTSLSSVSTGDTTPLPVTSPSSASTGHATSLPVTDTSSASTG 2700
2701 DTTSLPVTDTSSAYTGDTTSLPVTDTSSSSTGDTTPLLVTETSSVSTGDT 2750
2751 TPLPVTDTSSASTGHATPLPVTNTSSVSTGHATPLHVTSPSSASTGHTTP 2800
2801 LPVTDASSVSTGHATSLPVTDASSVFTGHATSLPVTIPSSASSGHTTPLP 2850
2851 VTDASSVSTGHATSLPVTDASSVSTGHATPLPVTDASSVSTGHATPLPLT 2900
2901 SLSSVSTGDTTPLPVTDTSSASTGQATPLPVTSLSSVSTGDTTPLPVTDT 2950
2951 SSASTGHATSLPVTDTSSASTGHATPLPDTDTSSASTGHATLLPVTDTSS 3000
3001 ASIGHATSLPVTDTSSISTGHATPLHVTSPSSASTGHATPLPVTDTSSAS 3050
3051 TGHANPLHVTSPSSASTGHATPLPVTDTSSASTGHATPLPVTSLSSVSTG 3100
3101 DTTPLPVTSPSSASTGHTTPLPVTDTSSASTGQATALPVTSTSSASTGDT 3150
3151 TPLPVTDTSSASTGQATPLPVTSLSSVSTGDTTPLPVTSPSSASTGHATP 3200
3201 LLVTDASSASTGQATPLPVTSLSSVSTGDTTPLPVTSPSSASTGHATSLP 3250
3251 VTDTSSASTGDTTSLPVTDTSSAYTGDTTSLPVTDTSSSSTGDTTPLLVT 3300
3301 ETSSVSTGHATPLLVTDASSASTGHATPLHVTSPSSASTGDTTPVPVTDT 3350
3351 SSVSTGHATPLPVTGLSSASTGDTTRLPVTDISSASTGQATPLPVTNTSS 3400
3401 VSTGDTMPLPVTSPSSASTGHATPLPVTSTSSASTGHATPVPVTSTSSAS 3450
3451 TGHTTPLPVTDTSSASTGDTTPLPVTSPSSASTGHTTPLHVTIPSSASTG 3500
3501 DTSTLPVTGASSASTGHATPLPVTDTSSVSTGHATPLPVTSLSSVSTGDT 3550
3551 TPLPVTDASSASTGQATPLPVTSLSSVSTGDTTPLLVTDASSVSTGHATP 3600
3601 LPVTDTSSASTGDTTRLPVTDTSSASTGQATPLPVTSLSSVSTGDTTPLL 3650
3651 VTDASSVSTGHATPLPVTDTSSASTGDTTRLPVTDTSSASTGQATPLPVT 3700
3701 IPSSSSSGHTTPLPVTSTSSVSTGHVTPLHVTSPSSASTGHVTPLPVTST 3750
3751 SSASTGHATPLLVTDASSVSTGHATPLPVTDASSASTGDTTPLPVTDTSS 3800
3801 ASTGQATPLPVTSLSSVSTGDTTPLPVTDASSASTGHATPLPVTIPSSVS 3850
3851 TGDTMPLPVTSPSSASTGHATPLPVTGLSSASTGDTTPLPVTDTSSASTR 3900
3901 HATPLPVTDTSSASTDDTTRLPVTDVSSASTGHATPLPVTSTSSASTGDT 3950
3951 TPLPVTDTSSVSTGHATSLPVTSRSSASTGHATPLPVTDTSSVSTGHATP 4000
4001 LPVTSTSSVSTGHATPLPVTSPSSASTGHATPVPVTSTSSASTGDTTPLP 4050
4051 VTNASSLSTGHATPLHVTSPSSASRGDTSTLPVTDASSASTGHATPLPLT 4100
4101 SLSSVSTGDTTPLPVTDTSSASTGQATPLPVTSLSSVSTGDTTPLPVTIP 4150
4151 SSASSGHTTSLPVTDASSVSTGHGTPLPVTSTSSASTGDTTPLPVTDTSS 4200
4201 ASTGHATPLPVTDTSSASTGHATPLPVTSLSSVSTGHATPLAVSSATSAS 4250
4251 TVSSDSPLKMETPGMTTPSLKTDGGRRTATSPPPTTSQTIISTIPSTAMH 4300
4301 TRSTAAPIPILPERGVSLFPYGAGAGDLEFVRRTVDFTSPLFKPATGFPL 4350
4351 GSSLRDSLYFTDNGQIIFPESDYQIFSYPNPLPTGFTGRDPVALVAPFWD 4400
4401 DADFSTGRGTTFYQEYETFYGEHSLLVQQAESWIRKMTNNGGYKARWALK 4450
4451 VTWVNAHAYPAQWTLGSNTYQAILSTDGSRSYALFLYQSGGMQWDVAQRS 4500
4501 GNPVLMGFSSGDGYFENSPLMSQPVWERYRPDRFLNSNSGLQGLQFYRLH 4550
4551 REERPNYRLECLQWLKSQPRWPSWGWNQVSCPCSWQQGRRDLRFQPVSIG 4600
4601 RWGLGSRQLCSFTSWRGGVCCSYGPWGEFREGWHVQRPWQLAQELEPQSW 4650
4651 CCRWNDKPYLCALYQQRRPHVGCATYRPPQPAWMFGDPHITTLDGVSYTF 4700
4701 NGLGDFLLVGAQDGNSSFLLQGRTAQTGSAQATNFIAFAAQYRSSSLGPV 4750
4751 TVQWLLEPHDAIRVLLDNQTVTFQPDHEDGGGQETFNATGVLLSRNGSEV 4800
4801 SASFDGWATVSVIALSNILHASASLPPEYQNRTEGLLGVWNNNPEDDFRM 4850
4851 PNGSTIPPGSPEEMLFHFGMTWQINGTGLLGKRNDQLPSNFTPVFYSQLQ 4900
4901 KNSSWAEHLISNCDGDSSCIYDTLALRNASIGLHTREVSKNYEQANATLN 4950
4951 QYPPSINGGRVIEAYKGQTTLIQYTSNAEDANFTLRDSCTDLELFENGTL 5000
5001 LWTPKSLEPFTLEILARSAKIGLASALQPRTVVCHCNAESQCLYNQTSRV 5050
5051 GNSSLEVAGCKCDGGTFGRYCEGSEDACEEPCFPSVHCVPGKGCEACPPN 5100
5101 LTGDGRHCAALGSSFLCQNQSCPVNYCYNQGHCYISQTLGCQPMCTCPPA 5150
5151 FTDSRCFLAGNNFSPTVNLELPLRVIQLLLSEEENASMAEVNASVAYRLG 5200
5201 TLDMRAFLRNSQVERIDSAAPASGSPIQHWMVISEFQYRPRGPVIDFLNN 5250
5251 QLLAAVVEAFLYHVPRRSEEPRNDVVFQPISGEDVRDVTALNVSTLKAYF 5300
5301 RCDGYKGYDLVYSPQSGFTCVSPCSRGYCDHGGQCQHLPSGPRCSCVSFS 5350
5351 IYTAWGEHCEHLSMKLDAFFGIFFGALGGLLLLGVGTFVVLRFWGCSGAR 5400
5401 FSYFLNSAEALP 5412
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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