 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q80TY5 from www.uniprot.org...
The NucPred score for your sequence is 0.71 (see score help below)
1 MLESYVTPILMSYVNRYIKNLKPSDLQLSLWGGDVVLSKLELKLDVLEQE 50
51 LKLPFTFLSGHIHELRIHVPWTKLGSEPVVITINTMECILKLKDGIQDDH 100
101 ESCGSNSTNRSTAENTKSSIKPRRIQQAAPADPDLPPGYVQSLIRRVVNN 150
151 VNIVINNLILKYVEDDIVLSVNITSAECYTVGELWDRAFMDISATDLVLR 200
201 KAINFSDCTVCLDKRNASGKIEFYQDPLLYKCSFRTRLHFTYDNLNSKMP 250
251 SVIKIHTLVESLKLSITDQQLPMFIRIMQLGIALYYGEIGNFKDGETEDP 300
301 PCLSKDTLANLTGTEEESRIDMQYPAPYKGQELYSQDYEEPQGWVSWAWS 350
351 FVPAIVSYDDGEEDDLGTDPASIMHQQKAQTLKDPIVSVGFYCTKATVTF 400
401 KLTEMQAENSYYSPQKVKSKEVLCWEQEGTTIEALMMGEPFFDCQIGFVG 450
451 CRAMCLKGILGVKDFEEHMNRSETEACFFICGENLSTKGLTYLTNSLFDY 500
501 RSPENNGTRAEFILDAAHHKETHTDIAGIQRFGAFYMDYLYTVEHSSGKG 550
551 PTSQQDFPSGKNEDLGIVQEKSTKSLVIGPLDCRLDSSAVHRVLKMIVCA 600
601 LEHEYEPYSRLKPESKDEKETVLDPEEVSSLEEYIPTRHTSVTLLKCTCT 650
651 VFMAEFNLLDCLLPVIMGGKNSSNVTNATNFQSLRPLPSIQILVDKINLE 700
701 HSVPMYAEQLVHVVSSLNQPSDNLLHYCYVHCYLKVFGFQAGLTCLDHSG 750
751 SYCLPAPIIPSFSTALYGKLLKLPALWTKRSQTVVTEGIFELPNLTIQAT 800
801 RAQTLLLQAIYQSWSHIGNVSSSTVNEALMNEVFPMTGVKSKNPLPTLEG 850
851 SIQNVELKYCSTSLVKCASGTLGSIKICAKAPGDSGKEKLIPLLQGPSDT 900
901 RDLHSSKWLNESRKPESLLAPDLIAFTIQVPQYMDYCHHSGAVFLCSVQG 950
951 LAVNIDPILYTWVIYQPQKRANRHAQQQPVVAVPLVTSVNRRKEDELSIG 1000
1001 SAPLGKQQSYQASEYASSPIKTKTVTESRPVSVPVKAVLRVHEECRSPED 1050
1051 KMKEFIAILWNAVKSLTLQLDVQSCCVFIPNDNLPSPSTIVSGDIPGTVR 1100
1101 SWYHGQTSIPGTLVLCLPQIKIISAGHKYMEPLQEIPFVIPRPILEEGDA 1150
1151 FPWTISLHHFSIYTLLGKQVTLSLVEPMGCTSTLAVTSQKLLPVGPDGRH 1200
1201 SFVVCLHVDLESLEIKCSNPQVQLIYELADTMSKVWSKIQKRGNLSPSSV 1250
1251 YPETVAGPIPGSPVWSSVGTAPPDTSTCSPSADIGTTTEGDSVQAGDDSP 1300
1301 FSDSVTLEQTTSNIGGSSGRVSLWMQWVLPKATVKLFAPDLEKKGTEVCM 1350
1351 VSELEDLSASIDVQDVYTKVKCKVESFSIDHYQSRPGEGWQSGHFEGVFL 1400
1401 QCKEKPVTTTKLLDGAHQQHGFLSLTYTKAVTKNVRHKLTSRNERRSFYK 1450
1451 LSEGLMDGSPHFLHEILLSAQAFDIVVCFPLLNAIASVFHTKLPKTQREK 1500
1501 RKSSGQPMRTHTLTSRNLPLIYINTSVIRIFVPQTEETQSTVAVNQAAKE 1550
1551 DTMVLKVGSIAMAPQADNPLGRSVLRKDIYQKALNLGILRDPGSEIEDRQ 1600
1601 YQIDLQSINIGTAQWDQLKPEKGSGSGGVPTESERNSQNPALEWNMASSI 1650
1651 QRHQERRAILTPILTDFSVRITGAPAIIFTKIISQENLHMEEILVCGHSL 1700
1701 EVNITTNLDFFLSVAQVQLLHQLIVANMTGLEPSTKATEISKQEQKKVDT 1750
1751 FDGGTAETSSRYSGAQDSGIGSDSVKIRIVQIEQYSGASQHRIARPSHQS 1800
1801 SIVKNLNFIPFDIFITASRISLMTYSSVALPKFKLPEQKEDGKTGRTFLN 1850
1851 LAEVDSDVAKPNQACVSMVTAEDPLSSSTSFSSGKKVRVLSLESLHASTR 1900
1901 SSARQALGVTVVRQPGRRGTGDLELDLFLHLIVSQPSLLLSCHHRKQRVE 1950
1951 VSIFDAMLKGVPSDYTCTDPGKTLPEASDYNIVWLQTVPGETDSKSGIPP 2000
2001 SLVTLHIKDFLNGPADIYLDVSKPLKANLSFTKLDQINHFLKKIKKAHSS 2050
2051 AHSKETSTPSDSILNMDEPPVPKCYRGKLSKTKVHCDEAQKTSFQENIWR 2100
2101 AISCFQKVSVHTTQIVVSMETVPHPHKPCVLASLSNLNGSLTVKAAQKVP 2150
2151 GASLGSSFLLSIHDVLLKTSLKERSRILIGPFSATVNLEAKWCKHSGNPG 2200
2201 PQQSIPKISMDLRGGLLQVFWGQEHLNCLALLHELFNGYLQEGKSEMPVP 2250
2251 ESAPQMPSPVEKTQAFKTEQSSDDLRTGIFQYVQDAESLKLPGVYEVLFY 2300
2301 NETEESPGMMLWRYPEPRVLTLVRITPVPFNTTEDPDISTADLGDVLQVP 2350
2351 CGLEYWDELQKVFVAFQEFSLSESKVCELQLPDINLVHDQKKLVSSDLWR 2400
2401 IVLNNNQNTTDDQSSASESGSQSTCEPLVTPTALAACTRVDSCFTPWFVP 2450
2451 SLCMSFQFAHLEFRLCHHLDQLGTASPQYLQPFISDKNVPSELEYMIISF 2500
2501 REPNLHLRQWNSGPVCQEIKFSSQMDCKLLECRNVTMQTVVKPFGICGQM 2550
2551 ALSSDGVQKLLDSTVIVDSVLVNFGQHVVHSLNTAIQAWQQNKCPEVEEL 2600
2601 VFSHFVICNDTQETLRFGQVDTDENILLASLHSHQYSWRSHKSPQLLHIC 2650
2651 IEGWGNWRWSEPFTVDHAGTFIRTIQYKGRTASLIIKVRALSGVQKQIII 2700
2701 CGRQIICSYLSQSIELKVVQHYIGQDGQAVVREHFDCLTAKQKLPSYILE 2750
2751 NNELTELCVKAKGDEDWSRDVCLEPKASEYSTVIQVPTSNSSIIYVWCTV 2800
2801 LTLEPNSQVQQRMIVFSPLFIMRSHLPDPIIIHLEKRSLGLSETQIIPGR 2850
2851 GQENPLQNVEPDLVHHLTFQAREEYDPSDCAVPISTALIKQIATKIQPGG 2900
2901 TVNEMLDEFYGPEKSQEPTWPYSNKDSDRNEQLSQWDSPMRVKLSIWKPY 2950
2951 VRTLLIELLPWALLINQSKWDLWLFEGEKIVLQVPAGKIIIPPNFQEAFQ 3000
3001 IGIYWENTNTVHKTLAIKLVHNLTSPKWKDGGNGEVVTLDEEAFVDAEIR 3050
3051 LGAFPGHQKLCQFCISSMVQHGIQVIQIEDKTTVINNTPYQIVYKPHLAI 3100
3101 SNSYSGKEHCHVPDSATFSICPGGEHPAVRSSSLPCWDVTPAVGSSELDT 3150
3151 ATLQKQILLGFSPVPGADSAQCWSLPAIIGGEFPRQSVAVPFGTGRENGF 3200
3201 CTRAIALTYQEHLGVTYITLSEDPSPRVVFHNRCPVPMLMKENIRDIPKF 3250
3251 DVYCKKIPPESSVHHELYHQIISYPDCKTKDLLPSLFLRIDSMEEMTAEW 3300
3301 SDPVDINSQGTQVVFLTGFGYVYVDIAQQCGTVFIILAPEGKAGPIFTST 3350
3351 SRALERMVTFRMFITQLSLAVSDDLTHQAPSELLRLTLDNVFLHVSPVPA 3400
3401 LLPGEEPPSSFFQLYGVEVYCGDLQLDNQLYNKSNFHFAVLVCQGERTDP 3450
3451 AQYSRVQSLLVSSKALEEYKENCFIKLCLTVSEGKDILLDVSEFTFELKP 3500
3501 ARLYVEDTFVYYIKTLFDTYLPPSRMSGHHAQLFTGQQVLPVQVTQHAKA 3550
3551 LVNAVKLRKLLIQPVNLLISIHASLKLYIASDHTPLSFSVFERGPVFTTA 3600
3601 RQLVHALAMHYAAGALFRAGWVVGSLEILGSPASLVRSIGNGISDFFRLP 3650
3651 YEGLTRGPGAFVSGVSRGTTSFVKHISKGALTSITNLATSLARNMGRLSL 3700
3701 DEEHYNRQEEWRRQLPESLGEGLRQGLSRLGISLLGAIAGIVDQPMQNFQ 3750
3751 KTSETQASAGHKAKGVISGVGKGIMGVFTKPIGGAAELVSQTGYGILHGA 3800
3801 GLSQLPKQRCQPTHLYADQAPNSHVKYVWKMLQSLGRPEVHMALDVVLVR 3850
3851 GSGQEHEGCLLLTSEVLFVVSISEDTQQQAFPITEISCAQDTKQNNLLTV 3900
3901 QLKQPRVASDVEIDGARERLSEQQFKRLVDYIAKTSCHLAPSCSSMQTCS 3950
3951 VVAVEPPPATVKTYHYLVDPHFAQVFISKFTMVKNKALRKGFS 3993
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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