 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6CP76 from www.uniprot.org...
The NucPred score for your sequence is 0.75 (see score help below)
1 MSFSFEVSVIVTGLSSLKLKTRNDSLDNLNLLLKTSPTEVPVKAFSPILD 50
51 AIITIIESEKTRYEKTRLENGKDARIELYENRLGSAAYTLRLFVERNCER 100
101 FKPKHIKLLSMTLFELMTRPRSRSLITSVADHLTYSLVALCGSPVFQCNF 150
151 ELHQWISLSHDISDAVTYHLDVSYNDKIIANLLQTLLELFQIDTIGIEDI 200
201 ATPVVRMTIKYLTLITKENTNTRTILTLVNSAILRLHLIRFQDVINLSYY 250
251 TIKHLLRIKLTNENNIGEIARFNLMISEVLYNKTPIIVGEDKDQSYVNKE 300
301 KLLPALQDYLIHSLKQYDHTKFTLDCVTFIDGPASSKFNWYSFSDICQNE 350
351 KNCLEDIWLYALSLTMMLKANYQFLEYKESSLAGGSLLFKRRKVKDTFAH 400
401 MLKDSLTYDDFLCNCIDSDSIKIKTTGLHIGLLYLSIFDCSNIELSHLKE 450
451 ELFRCSQDVRFMLLCLSCFIPMCSQSKNSFSPEEEIRLFKMCVPLLKTSN 500
501 GCKTACSLLYKLIEFQLEPIKDKSVLQQMSDLYLLSDVNGPALVCNESFK 550
551 FWMHLHYYAKTFQTVKSPITYVFSWLYARWDQLFTLVVSETHFYVFASWL 600
601 CGCTHTTFPTFEYSRPSLFHDTWMGLSEERASITGFSLTIRTIELRKQKF 650
651 APVFCEEAERVRFMYKLFDLIDESAISATFIDRAIQVLRTIESLVGQRNY 700
701 TDYLSRFKEIFLLSSSVIDFGQNAQIFSVMEGMISLKDSLLRHIIMDILP 750
751 TEKVLSTFMQRLAEHTQQTSHQDEFLSHHAKPEAGSIPISEMIEIGFEFA 800
801 LQVHSVSKAFDPLSSFILYSKKLSLPMLNRTLPNLITYLENNENEIPTAS 850
851 LERLTQFLGSSLLAPSFDTSSTSMKLLTRYLEGISKYWVMEDRSQVLTAD 900
901 CNDIFDWIVTQYDESSFSGVEALYELARFMTLLLEKYNLSNSSISGGKQR 950
951 VFKILSGCITRLPKYLTNRVVSLLGTYVKRVGVTNQRILFKELLQRFNPP 1000
1001 QESVETAAFFSLTCTKLSLINEFYLLNSILHLLDNTNFSHLLLYVEKSLD 1050
1051 TISTFYGLCSKQDLFHQCRYFIIDQWFTKSAKSKIYEPSIWKVELFEFEF 1100
1101 DEFCIRYQMELTSFFFAKSSTYYYIIDHLKKLLNLKQEALLTKYIAPTIA 1150
1151 LSYVDSGVKDLIFDIAADLLGRKFPNVLTINLDDVIYYFIKLSDLSNLAT 1200
1201 SLTFWCKIFNSSRFTNMLHYNSSNCMQLNDNVAIAFPIVYKVLKKNVFTD 1250
1251 IDDGRSFEYVIQRLVMDLQNCVLIDQKIRVLRQIKLLVLFFEHKLTLFKD 1300
1301 IDFFLLELSKFLFNADIFSEVYGFILDLLEFSANNKMDVARSLTELMRFC 1350
1351 FTVTDSNVKKTLFPKVNPVLFNFCVSDGKQLYATCYALLTLETNSFGWND 1400
1401 IAQVFKFQEVDRTSVSLLSDLFDNFDYDGSFDANLISPTTIQNLISIPRD 1450
1451 NARVSDKFRRWLGNILGEIVYTRPYDHIIPHHCSTLDLESGISGLLQILW 1500
1501 VQYQKADDISLRFLLDHIQSIILQDESVLAEISSDSYSSLVNLKNLTDIS 1550
1551 WEKFENCHGMLNIKLGETFLTLTFTDRSCHYQKWISAFICNILLVIVEKF 1600
1601 PSFRILALLCDNTAFLHSAIISQLIKILLVSFPKQRSSFLSDILNRADEI 1650
1651 FKTEDRTLKMEVITKVFSIIRGMALNGVQNALYVYDKIKLQPVIPIMLSL 1700
1701 GSEIWSLMIYEEFYGEYCTGKMLDYELLYQIYSKIDEKDLFYGLPLSSSL 1750
1751 ASSLTLISKTKFNSYTNFALSNGRFEEGLRNKDSSCLHEFASVTSSNGFT 1800
1801 GLATMLDSNFENPLLSANQYSWALKLNKWDLPIPEARDSFAKSAFSILKD 1850
1851 VKEIPDFFSFDDHILKVMDGGSLLKNSQLNLETMESLGLLVSLKKLGSAD 1900
1901 MNTLTTLNNLRVHDTLNADYLPENVFDILHWSRHFFIESKINNTSVIEHA 1950
1951 PGSNFTLQLAKILNLVHASTFCRDQGRFQDLINIVMTLEAAVDDITNNPA 2000
2001 IGPSDTITLFCKRISTVESARMLWANKESAMAINMLEDLLQTNLTAVNVE 2050
2051 NVSLADVQDILMPDAVVDSQLVEWSSFSRHRSPDVIFNDHILYYERDVLN 2100
2101 INEPNLRSSICYTYAEFCYKQSQKVDEGELLYLKQKIAKASNQLQEISSI 2150
2151 YKNPKLRDAERKEAKRHHNRLSLQNHHDKDRYNKISSSRIAFVSQALHFF 2200
2201 LTTLVHSNSRDAEVVDKFCSLWFSYSTDDIINSKLQKEIGTVPSFKFLPW 2250
2251 VSQMASKLADSVSPFQDTLQLTLKRMLYKLPYETLYPLISMSLQDSESKV 2300
2301 IDPVTKSRVEVVNKIIAALDMYDSGRYGSQFTRPVQAFCSMSVALACHKI 2350
2351 PPKMKFLQLDTLNIGKYWLETLPKVHLPLPTLPVKITCSQDGRREGRSYI 2400
2401 SSIDPKVLISSSGLSLPKIATFTVSDGTRHRVLLKGSNDDLRQDAIMEQV 2450
2451 FKQVNKILKANKTTRKQNLSVRTYEVIPLGPRAGLIEFVANSMSLHDILL 2500
2501 NLHCNDEISFDKARKTMKAAQNHSVEERVLTFSRITEKIKPQLRRFFFQS 2550
2551 FVHAHDWYESRNRYTKSVVTSSIVGYLLGLGDRHLNNILIDIKTGEPIHI 2600
2601 DLGVAFDQGKLLPIPELVPFRLTRDIVDGFGVAGIEGLFRNNCERVFKVL 2650
2651 QDEKERLLCVLNVLKWDPLYSWKMTPLKKQRLQAKFTGDYDEEEISVSDA 2700
2701 DFSELLEEDNNNDESIRALKGVESKLYGDGLSVEAIVQELLSSATDKQNL 2750
2751 ATIYMGWSPFY 2761
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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