 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q05793 from www.uniprot.org...
The NucPred score for your sequence is 0.50 (see score help below)
1 MGQRAVGSLLLGLLLHARLLAVTHGLRAYDGLSLPEDTETVTASRYGWTY 50
51 SYLSDDEDLLADDASGDGLGSGDVGSGDFQMVYFRALVNFTRSIEYSPQL 100
101 EDASAKEFREVSEAVVEKLEPEYRKIPGDQIVSVVFIKELDGWVFVELDV 150
151 GSEGNADGSQIQEVLHTVVSSGSIGPYVTSPWGFKFRRLGTVPQFPRVCT 200
201 ETEFACHSYNECVALEYRCDRRPDCRDMSDELNCEEPVPELSSSTPAVGK 250
251 VSPLPLWPEAATTPPPPVTHGPQFLLPSVPGPSACGPQEASCHSGHCIPR 300
301 DYLCDGQEDCRDGSDELGCASPPPCEPNEFACENGHCALKLWRCDGDFDC 350
351 EDRTDEANCSVKQPGEVCGPTHFQCVSTNRCIPASFHCDEESDCPDRSDE 400
401 FGCMPPQVVTPPQQSIQASRGQTVTFTCVATGVPTPIINWRLNWGHIPAH 450
451 PRVTMTSEGGRGTLIIRDVKEADQGAYTCEAMNSRGMVFGIPDGVLELVP 500
501 QRGPCPDGHFYLEDSASCLPCFCFGVTNVCQSSLRFRDQIRLSFDQPNDF 550
551 KGVNVTMPSQPGVPPLSSTQLQIDPALQEFQLVDLSRRFLVHDAFWALPK 600
601 QFLGNKVDSYGGFLRYKVRYELARGMLEPVQKPDVILVGAGYRLHSRGHT 650
651 PTHPGTLNQRQVQLSEEHWVHESGRPVQRAEMLQALASLEAVLLQTVYNT 700
701 KMASVGLSDIVMDTTVTHTTIHGRAHSVEECRCPIGYSGLSCESCDAHFT 750
751 RVPGGPYLGTCSGCNCNGHASSCDPVYGHCLNCQHNTEGPQCDKCKPGFF 800
801 GDATKATATACRPCPCPYIDASRRFSDTCFLDTDGQATCDACAPGYTGRR 850
851 CESCAPGYEGNPIQPGGKCRPTTQEIVRCDERGSLGTSGETCRCKNNVVG 900
901 RLCNECSDGSFHLSKQNPDGCLKCFCMGVSRQCSSSSWSRAQVLGASEQP 950
951 SQFSLSNAAGTHTTSEGVSSPAPGELSFSSFHNLLSEPYFWSLPASFRGD 1000
1001 KVTSYGGELRFTVMQRPRPSSAPLHRQPLVVLQGNNIVLEHHASRDPSPG 1050
1051 QPSNFIVPFQEQAWQRPDGQPATREHLLMALAGIDALLIQASYTQQPAES 1100
1101 RLSGISMDVAVPENTGQDSAREVEQCTCPPGYRGPSCQDCDTGYTRVPSG 1150
1151 LYLGTCERCNCHGHSETCEPETGACQSCQHHTEGASCEQCQPGYYGDAQR 1200
1201 GTPQDCQPCPCYGAPAAGQAAHTCFLDTDGHPTCDSCSPGHSGRHCERCA 1250
1251 PGYYGNPSQGQPCHRDGQVPEVLGCGCDPHGSISSQCDAAGQCQCKAQVE 1300
1301 GRSCSHCRPHHFHLSASNPEGCLPCFCMGVTQQCASSSYSRQLISTHFAP 1350
1351 GDFQGFALVNPQRNSQLTGGFTVEPVHDGARLSFSNFAHLGQESFYWQLP 1400
1401 EIYQGDKVAAYGGKLRYTLSYTAGPQGSPLLDPDIQITGNNIMLVASQPA 1450
1451 LQGPERRSYEIIFREEFWRRPDGQPATREHLLMALADLDELLVRATFSSV 1500
1501 PRAASISAVSLEGAQPGPSSGPRALEVEECRCPPGYVGLSCQDCAPGYTR 1550
1551 TGSGLYLGQCELCECNGHSDLCHPETGACSRCQHNTAGEFCELCATGYYG 1600
1601 DATAGTPEDCQPCACPLTNPENMFSRTCESLGAGGYRCTACEPGYTGQYC 1650
1651 EQCAPGYEGDPNVQGGRCQPLTKESLEVQIHPSRSVVPQGGPHSLRCQVS 1700
1701 GSPPHYFYWSREDGRPLPSSAQQRHQGSELHFPSVQPSDAGVYICTCRNL 1750
1751 IHTSNSRAELLVAEAPSKPIMVTVEEQRSQSVRPGADVTFICTAKSKSPA 1800
1801 YTLVWTRLHNGKLPSRAMDFNGILTIRNVQPSDAGTYVCTGSNMFAMDQG 1850
1851 TATLHVQVSGTSTAPVASIHPPQLTVQPGQQAEFRCSATGNPTPMLEWIG 1900
1901 GPSGQLPAKAQIHNGILRLPAIEPSDQGQYLCRALSSAGQHVARAMLQVH 1950
1951 GGSGPRVQVSPERTQVHEGRTVRLYCRAAGVPSASITWRKEGGSLPFRHQ 2000
2001 AHGSRLRLHHMSVADSGEYVCRANNNIDAQETSIMISVSPSTNSPPAPAS 2050
2051 PAPIRIESSSSRVAEGQTLDLNCVVPGHAHAQVTWHKRGGSLPTHHQTHG 2100
2101 SRLRLYQVSSADSGEYVCSVLSSSGPLEASVLVSITPAAANVHIPGVVPP 2150
2151 IRIETSSSRVAEGQTLDLSCVVPGQAHAQVTWHKRGGSLPAGHQVHGHML 2200
2201 RLNRVSPADSGEYSCQVTGSSGTLEASVLVTIEASEPSPIPAPGLAQPVY 2250
2251 IESSSSHLTEGQTVDLKCVVPGQAHAQVTWHKRGSSLPARHQTHGSLLRL 2300
2301 YQLSPADSGEYVCQVAGSSHPEHEASFKLTVPSSQNSSFRLRSPVISIEP 2350
2351 PSSTVQQGQDASFKCLIHEGAMPIKVEWKIRDQELEDNVHISPNGSIITI 2400
2401 VAPGPATMEPTACVASNVYGMAQSVVNLSVHGPPTVSVLPEGPVHVKMGK 2450
2451 DITLECISSGEPRSSPRWTRLGIPVKLEPRMFGLMNSHAMLKIASVKPSD 2500
2501 AGTYVCQAQNALGTAQKQVELIVDTGTVAPGTPQVQVEESELTLEAGHTA 2550
2551 TLHCSATGNPPPTIHWSKLRAPLPWQHRIEGNTLVIPRVAQQDSGQYICN 2600
2601 ATNSAGHTEATVVLHVESPPYATIIPEHTSAQPGNLVQLQCLAHGTPPLT 2650
2651 YQWSLVGGVLPEKAVVRNQLLRLEPTVPEDSGRYRCQVSNRVGSAEAFAQ 2700
2701 VLVQGSSSNLPDTSIPGGSTPTVQVTPQLETRNIGASVEFHCAVPNERGT 2750
2751 HLRWLKEGGQLPPGHSVQDGVLRIQNLDQNCQGTYVCQAHGPWGQAQATA 2800
2801 QLIVQALPSVLINVRTSVHSVVVGHSVEFECLALGDPKPQVTWSKVGGHL 2850
2851 RPGIVQSGTIIRIAHVELADAGQYRCAATNAAGTTQSHVLLLVQALPQIS 2900
2901 TPPEIRVPAGSAAVFPCMASGYPTPAITWSKVDGDLPPDSRLENNMLMLP 2950
2951 SVRPEDAGTYVCTATNRQGKVKAFAYLQVPERVIPYFTQTPYSFLPLPTI 3000
3001 KDAYRKFEIKITFRPDSADGMLLYNGQKRSPTNLANRQPDFISFGLVGGR 3050
3051 PEFRFDAGSGMATIRHPTPLALGQFHTVTLLRSLTQGSLIVGNLAPVNGT 3100
3101 SQGKFQGLDLNEELYLGGYPDYGAIPKAGLSSGFVGCVRELRIQGEEIVF 3150
3151 HDVNLTTHGISHCPTCQDRPCQNGGQCQDSESSSYTCVCPAGFTAAAVNI 3200
3201 RKPCTATPSLWADATCVNRPDGRGYTCRCHLGRSGVRCEEGVTVTTPSMS 3250
3251 GAGSYLALPALTNTHHELRLDVEFKPLEPNGILLFSGGKSGPVEDFVSLA 3300
3301 MVGGHLEFRYELGSGLAVLRSHEPLALGRWHRVSAERLNKDGSLRVDGGR 3350
3351 PVLRSSPGKSQGLNLHTLLYLGGVEPSVQLSPATNMSAHFHGCVGEVSVN 3400
3401 GKRLDLTYSFLGSQGVGQCYDSSPCERQPCRNGATCMPAGEYEFQCLCQD 3450
3451 GFKGDLCEHEENPCQLHEPCLNGGTCRGARCLCLPGFSGPRCQQGAGYGV 3500
3501 VESDWHPEGSGGNDAPGQYGAYFYDNGFLGLPGNSFSRSLPEVPETIEFE 3550
3551 VRTSTADGLLLWQGVVREASRSKDFISLGLQDGHLVFSYQLGSGEARLVS 3600
3601 GDPINDGEWHRITALREGQRGSIQVDGEDLVTGRSPGPNVAVNTKDIIYI 3650
3651 GGAPDVATLTRGKFSSGITGCIKNLVLHTARPGAPPPQPLDLQHRAQAGA 3700
3701 NTRPCPS 3707
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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