 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P98167 from www.uniprot.org...
The NucPred score for your sequence is 0.74 (see score help below)
1 MLLPALLFGAAWALANGRWCEQTETVLVEEEVTPHQEDLVPCASLQHYQR 50
51 RGWRLDLTWSGRAGLCAIYKPPETRPAAWNRTVRACCPGWGGTHCTLALA 100
101 EASPEGHCFATWLCNLGAGSVNASAGSLEECCAQPWGHSWRDGRSQTCHS 150
151 CSNHSRLGSTPSPAILQPLAGAVAQLWSQRQRPSATCATWSGFHYRTFDG 200
201 RHFHFLGRCTYLLAGAADATWAVHLQPMGHCPQPGHCQLARVMMGPEEVL 250
251 IRGENVTVNGRLVPEGASQLLPGLSLQWQGDWLVLSGGLGVVVRLDRSSS 300
301 VSISVDQELQGQTQGLCGVYNGQPEDDFLEPGRGLAALAATFGNSWRLPD 350
351 SELGCLDAVEAAQGCEDPLRGTETGTEAGQLRAEAQDVCHQLLEGPFREC 400
401 HTQVPPAEYHEACLFAYCAGAPAGSGRAERLEAVCATLASYAQDCAARRI 450
451 AVRWRKPGFCERLCPGGQLYSDCASACPPSCSAVGEGSEWSCGEECVSGC 500
501 ECPPGLFWDGALCVPAARCPCYRRRRRYEPGDTVRQLCNPCECRDGRWLC 550
551 AQAPCAAECAVGGDGHYVTFDGRSFSFRGRAGCRFILVQDFAKRQLLIVL 600
601 EHGDCDAGSCLHAISVSLGDTLVQLRDSGVVLVDGQDVALPWSAAGGLSV 650
651 SRASSSFLLLRWPGARILWGVSDPAAYITLDPHHAHQVQGLCGTFTRNQQ 700
701 DDFLTPAGDVETSITAFASKFQVAGGGTCSLEACTPLSPCSTHTERQVFA 750
751 EVACAILHGPTFQECHGLVDREAFHLRCLAAVCGCTPGRDCLCPVLAAYA 800
801 RRCAQEGALPSWRNQTFCPVLCPGGQEYQECAPACDRNCGEPEDCGELDN 850
851 CVAGCNCPLGLLWDPEGQCVPPNLCPCQLGAHRYAPGSATMKDCNHCVCQ 900
901 ERGLWNCTAHHCAPPRTFCPRELVYVPGACLLTCDSLDADRTCPPGSPGG 950
951 CVCPPGTVLLEERCVPPELCPCRHGGQWYLPNAAIQEDCNLCVCQGQQWH 1000
1001 CTGQRCDGRCRASGAPHYVTFDGLALTFPGACEYLLVREASGQFMVSAQN 1050
1051 LPCGASGLTCTKALTVRLQGTVVHMLRGRAVMVNGVSVTPPKVYSGPGLS 1100
1101 LHTAGLFLLLSTRLGLTLLWDGGTRVPVQLSPQLRGRVAGLCGDFDGDAS 1150
1151 NDLRSRQGVLEPTAELAAHSWRLGPLCPEPGDLPHPCAVNAHRAGWARAR 1200
1201 CGVVLQPLFARCHVEVPPQQHYEQCVYDACGCDSGGDCECLCSAIATYAD 1250
1251 ECARHGIHVRWRSQELCPLQCERGQVYEACGPTCPATCHDHRPEPGWPCR 1300
1301 AVACVEGCFCPEGTLLHGGVCLEPAACPCEWGGSFFPPGTVLQKDCGNNC 1350
1351 TCRESQWLCGDDGGRCVEPGPGCAEGETPCRESGHCVPHGWLCDNQDDCG 1400
1401 DGSDEEGCATRVCGEGQVSCCSGRCLPLVLLCDGQDDCGDGMDEQGCPCP 1450
1451 QDSLTCADGHCLPPARLCDGHPDCPDGADEESCLGQVDCAPGEVSCVDGT 1500
1501 CLGAIQLCDGVWDCLDGGDEGPGHCPLPSLPTPPAGTLPGPSAVSWKLHL 1550
1551 PPWPVSALRLPCGPLDFACGSGECAPRGWRCDGEEDCADGSDESGCDRPC 1600
1601 APHHAPCARGSHCVAAEQLCDGVPHCPDGSDEDPGACERLQAPGGPNRTG 1650
1651 LPCPEYSCPDGLCIGFQQVCDGQPDCELAGTAGPSPEEQGCGAWGPWSPW 1700
1701 ELCSRTCGPGVQGWSRRCSPPSLPVLWHCPGPERQTRACFAAACPEDGVW 1750
1751 TSWSRWSPCSEPCGGVTARHRECHPPQNGGRTCATLPGGPPSTRETRPCP 1800
1801 QDGCPNVTCSGELVFHACVPCPLTCDDISGQATCPPDRPCGGPGCWCPAG 1850
1851 QVLGAQGRCVWPRQCPCLVDGSRYWPGQRVKTDCQLCVCQDGRPRRCQPS 1900
1901 LDCAVNCGWSAWSPWAECLGPCGSRSVQWSFRSPNNPRPAGRGHQCRGLH 1950
1951 RKARRCQTEPCEGCEQDGRVHRVGERWRAGPCRVCQCLHDGSARCSPYCP 2000
2001 LGSCPQDWVLVEGVGESCCHCVPPGENQTVHPMATPVPAPTPSPQIGAPL 2050
2051 ITYLLPPPGDPCYSPLGLARLPEGSLPASSQQLEHPAWAAILRPAPGAPG 2100
2101 WSPVEHADTQGHTPPPYLQLDLLQPRNLTGIIVQGAGSSDWLQVSSDGLH 2150
2151 WHSYRDIQHGTQPAPQLFPKNWNGPSTVWMFARMVQARHVRVWPSDGHHQ 2200
2201 AAPSSDANLDGPLRVELLGCEPAPLCLGVGHRCVSGECAPRGAPCDGVED 2250
2251 CKDGSDEEGCVTPPAGAGRIESTAWSSAPSSAQPGQLPPQPSEGLAEAEA 2300
2301 DHWHPGRGSPVPPTGKGPASLGSEPHPSPGGSVQTVTPTSQPEAQALRPE 2350
2351 MAAVTVLPPHPMVTPEVPAGRSTTPGPFPHVQCSPGQVPCEVLGCVELEQ 2400
2401 LCDGREDCLDGSDERPCAWAAGTVPFTVPTTTLPGLPASRDLCSPSQLTC 2450
2451 GSGECLPVERRCDLQLDCQDGSDENGCVDCGLAPWSGWSSCSRSCGLGLA 2500
2501 FQRRELLRPPLPGGSCPPDRLRSQPCFVQACPVAGAWAEWEAWGPCSVSC 2550
2551 GGGHRSRRRSCMDPPPKNGGAPCPGPPQERAPCGLQPCAGGTDCGQGRVH 2600
2601 VSAELCRKGLVPPCPPSCLDPEANRSCSGLCLEGCRCPPGLLLQDAGCLP 2650
2651 LSECPCLVGEELQQPGVPFLLDNCSRCVCEKGALLCEPGGCPVPCGWSAW 2700
2701 SSWGPCDRSCGSGLRARFRSPSNPPAASGGAPCEGQRQELQACYSACGAE 2750
2751 VPGWTPWAPWSACSQSCLVPGGGPALRSRSRLCPGPGDTSCIGEATEEEP 2800
2801 CSPPVCLGLGVWGQWAAWSACSAPCNGGVQTRGRRCSASAPGDPGCQGPH 2850
2851 SQTRDCNTQPCTAQCPGDMVFRSAEQCRWEGGPCPGLCLARGPGVECTGV 2900
2901 CTAGCACPTGLFLHNSSCLPPSQCPCQLRGQLYAPGAVARLDSCSNCTCI 2950
2951 SGEMVCASEPCPVACGWSPWTPWSLCSRSCNVGVRRRFRAGTAPPAAFGG 3000
3001 AACQGPNMEAEFCSLRPCGGPAGEWGPWSPCSVPCGGGYRNRTRGSSGPS 3050
3051 PVDFSTCGLQPCAGPAPGVCPPGKRWLDCAQGPASCAELSAPRGADQPCH 3100
3101 PGCYCPSGMLLLNNACVPTQDCPCTHGGRLHPPGSAVLRPCENCSCVSGL 3150
3151 ITNCTSWPCKEGQPTWSPWTPWSECSASCGPARRHKHRFCTRPPGGAPSS 3200
3201 MAPPLLLSSVPPLCPGPEAEEEPCLLPECDRAGGWGPWGPWSSCSRSCGG 3250
3251 GLRSRSRACDQPPPQGLGDYCEGPRAQGAACQALPCPVTNCTAIEGAEYS 3300
3301 ACGPPCPRSCDDLVHCVWHCQPGCYCPPGQVLSADGTVHVQPGHCSCLDL 3350
3351 LTGERHRPGAQLAKPDGCNYCTCSEGQLTCTDLPCPVPGAWCPWSEWTAC 3400
3401 SQPCQGQTRTRSRACSCPAPQHGGAPCPGEAGEAGAQHQRETCASTPECP 3450
3451 VDGAWSPWGPWSPCEVCLGRSHRSRECSWPPTSEGGRPCPGGHRQSRPCQ 3500
3501 GNSTQCTDCAGGQDLLPCGQPCPRSCEDLSPGVECQPDSMGCQQPRCGCP 3550
3551 PGQLSQDGLCVTPSQCRCQYQPGAMGIPENQSRSAGSGLSSWESLEPGEV 3600
3601 VTGPCDNCTCVAGILQCQEVPACSGLGLWGSWGPWEDCSVSCGGGEQLRF 3650
3651 RRCPRPPCPGPARQSRTCRTQVCREAGCPAGRLYRECQPSEGCPFSCAHV 3700
3701 TGQVGCFSAGCEEGCHCPEGTFLHRSACVQECPCVLTALWLQGLGAAGAD 3750
3751 PGAHLSVLGENGQPLGPGDELGSGQSLRTGCHNCSCAHGKLSCSVEACSK 3800
3801 AAGGFSPWGPWGPCSRSCGGLGTRTRSRQCVRPMPAPGGQGCHGPHWDLE 3850
3851 YCPSPECPGAAGSTAEPATGLPGGWGLWSPWSPCSGTCTDPAHPAWRSRS 3900
3901 RLCLANCTGGAASQERPCNLPSCTELPLCPGPGCEAGNCSWTAWAPWEPC 3950
3951 SRSCGVGQQRRLRAYHPPGPGGHWCPDVLTAYQERRFCNLRACPVPGGWS 4000
4001 RWSPWSWCDRSCGGGRSLRSRSCSSPPPKNGGAPCVGERHHARLCNPTPC 4050
4051 EEGCPAGMEVVSCANRCPRRCSDLQEGIVCQEDQACQQGCRCPEGSLEQD 4100
4101 GGCVPLGHCECTDAQGHSWAPGSQHQEACNNCTCRAGQLSCTAQPCPPPA 4150
4151 HCAWSRWSAWSPCSRSCGPAGQQSRFRSSTSGSWAPECREEQSQSQPCPQ 4200
4201 SPCPPLCLQGTRPRSLGDSWLQDGCQQCSCTPEGIICEDAECAGLGAWTP 4250
4251 WSPWSDCPVSCGGGNQVRTRVCVASAPPRGGSPCLGPDVQSQRCGLWPCP 4300
4301 ALPDTCSWGPWGPCSRSCGPGLASRSASCPCLLAEAEPACNSTSPRLDTQ 4350
4351 ACYAGPCLEECVWSSWSSWTRCSCEVLVQQRYRHQRPAPGGAGAGPPCTR 4400
4401 LDGHFRPCLTGNCSEDSCAPPFEFQACGSPCTGLCATYLSPWLCQDLPPC 4450
4451 QPGCYCPEGLLEQAGGCVPPEQCNCQHVSGEGAGVTLAPGDRLQLGCKEC 4500
4501 ECQRGELQCTSQGCQGLLPLSGWSEWSPCGPCLPLGLLAPASRAALEERW 4550
4551 PQDTAGLSPTSAPTLASEQHRHRLCLDPETGRPWAGDPDLCTVPLSQQRL 4600
4601 CPDPGACQDLCQWGPWGAWSPCQVPCSGGFRLRWREAGIPPGGGCRGPWA 4650
4651 QTESCNMGPCPGESCEAQDTVPTPDCANQCPRSCVDLWDRVECLQGPCRP 4700
4701 GCRCPPGQLVQDGHCVPVSSCRCGLPSPNASWALAPAEVVRLDCRNCTCV 4750
4751 NGSLACSSHECPTLGPWSAWSNCSAPCGGGTTKRHRSCKEGPGVTPCQAQ 4800
4801 DMEQQQDCNLQPCPECPPGQVLSACAVSCPRLCSHLQPGTPCMQEPCQLG 4850
4851 CDCPRGQLLHNGTCVPPAECPCTQLSLPWGLTLTLEEQHRELPPGTLLTQ 4900
4901 NCTHCICQGGAFSCSLTDCQECPPGETWQQVAPGELGPCEQTCREPNATE 4950
4951 TQGNCSGRQAPGCVCQRGHFRSQEGPCVPVDLCECWHHGRPHPPGSEWQK 5000
5001 ACESCRCVSGESICTQHCPPLTCAQGETAVQEPGGCCPTCRQEAPEEQPV 5050
5051 SCRHLTELRNLTKGACYLEQVEVNYCSGHCPSSTNVLPEEPYLQSQCDCC 5100
5101 SYRLDPENPVRILNLRCPGGRTELVVLPVIHSCQCSACQGGDFSER 5146
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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