 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9JLU4 from www.uniprot.org...
The NucPred score for your sequence is 0.94 (see score help below)
1 MDGPGASAVVVRVGIPDLQQTKCLRLDPTAPVWAAKQRVLCALNHSLQDA 50
51 LNYGLFQPPSRGRAGKFLDEERLLQDYPPNLDTPLPYLEFRYKRRVYAQN 100
101 LIDDKQFAKLHTKANLKKFMDYVQLHSTDKVARLLDKGLDPNFHDPDSGE 150
151 CPLSLAAQLDNATDLLKVLRNGGAHLDFRTRDGLTAVHCATRQRNAGALT 200
201 TLLDLGASPDYKDSRGLTPLYHSALGGGDALCCELLLHDHAQLGTTDENG 250
251 WQEIHQACRFGHVQHLEHLLFYGANMGAQNASGNTALHICALYNQESCAR 300
301 VLLFRGANKDVRNYNSQTAFQVAIIAGNFELAEVIKTHKDSDVVPFRETP 350
351 SYAKRRRLAGPSGLASPRPLQRSASDINLKGDQPAASPGPTLRSLPHQLL 400
401 LQRLQEEKDRDRDGEQENDISGPSAGRGGHSKISPSGPGGSGPAPGPGPA 450
451 SPAPPAPPPRGPKRKLYSAVPGRKFIAVKAHSPQGEGEIPLHRGEAVKVL 500
501 SIGEGGFWEGTVKGRTGWFPADCVEEVQMRQYDTRHETREDRTKRLFRHY 550
551 TVGSYDSLTSHSDYVIDDKVAILQKRDHEGFGFVLRGAKAETPIEEFTPT 600
601 PAFPALQYLESVDVEGVAWKAGLRTGDFLIEVNGVNVVKVGHKQVVGLIR 650
651 QGGNRLVMKVVSVTRKPEEDSARRRAPPPPKRAPSTTLTLRSKSMTAELE 700
701 ELASIRRRKGEKLDEILAVAAEPTLRPDIADADSRAATVKQRPTSRRITP 750
751 AEISSLFERQGLPGPEKLPGSLRKGIPRTKSVGEDEKLASLLEGRFPRST 800
801 SMQDTVREGRGIPPPPQTAPPPPPAPYYFDSGPPPTFSPPPPPPGRAYDT 850
851 VRSSFKPGLEARLGAGAAGLYDSGTPLGPLPYPERQKRARSMIILQDSAP 900
901 EVGDVPRPAPAATPPERPKRRPRPSGPDSPYANLGAFSASLFAPSKPQRR 950
951 KSPLVKQLQVEDAQERAALAVGSPGPVGGSFAREPSPTHRGPRPGGLDYS 1000
1001 SGEGLGLTFGGPSPGPVKERRLEERRRSTVFLSVGAIEGSPPSADLPSLQ 1050
1051 PSRSIDERLLGTGATTGRDLLLPSPVSALKPLVGGPSLGPSGSTFIHPLT 1100
1101 GKPLDPSSPLALALAARERALASQTPSRSPTPVHSPDADRPGPLFVDVQT 1150
1151 RDSERGPLASPAFSPRSPAWIPVPARREAEKPTREERKSPEDKKSMILSV 1200
1201 LDTSLQRPAGLIVVHATSNGQEPNRLGAEEERPGTPELAPTPMQAAAVAE 1250
1251 PMPSPRAQPPGSIPADPGPGQGSSEEEPELVFAVNLPPAQLSSSDEETRE 1300
1301 ELARIGLVPPPEEFANGILLATPPPGPGPLPTTVPSPASGKPSSELPPAP 1350
1351 ESAADSGVEEADTRSSSDPHLETTSTISTVSSMSTLSSESGELTDTHTSF 1400
1401 ADGHTFLLEKPPVPPKPKLKSPLGKGPVTFRDPLLKQSSDSELMAQQHHA 1450
1451 TSTGLTSAAGPARPRYLFQRRSKLWGDPVESRGLPGPEDDKPTVISELSS 1500
1501 RLQQLNKDTRSLGEEPVGGLGSLLDPAKKSPIAAARCAVVPSAGWLFSSL 1550
1551 GELSTISAQRSPGGPGGGASYSVRPSGRYPVARRAPSPVKPASLERVEGL 1600
1601 GAGVGGAGRPFGLTPPTILKSSSLSIPHEPKEVRFVVRSVSARSRSPSPS 1650
1651 PLPSPSPGSGPSAGPRRPFQQKPLQLWSKFDVGDWLESIHLGEHRDRFED 1700
1701 HEIEGAHLPALTKEDFVELGVTRVGHRMNIERALRQLDGS 1740
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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