 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q07963 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MEDSDLSITNIRDFLTELPKLAKCEYSETTSYLLWKTLNLRLKHSDNDIN 50
51 WRSLVSILNSEAWENEKYRDILNGRKWRTLEFENDHHSVGNMHIGTACTR 100
101 LCFPSETIYYCFTCSTNPLYEICELCFDKEKHVNHSYVAKVVMRPEGRIC 150
151 HCGDPFAFNDPSDAFKCKNELNNIPISNDNSNVTDDENVISLLNYVLDFL 200
201 IDVTVSYKEEAEAHSSERKASSLMHPNQNSITDDIMEKHECEPLVNDENF 250
251 VFFDNNWSNTRKEAHMEWAIQIEEEECNVHYMDLASTITRILNTPVEYAI 300
301 SITKALEDSHDVVTVLQSENFFEIDQIAKEFQKENIVVHVRKADDIFKRK 350
351 LTDDLTDWLYSLCFKAATSLQNKYALRISMLDVWYSHFSKMRVSPTNTNP 400
401 DFSKINLLGGFLISNEDSDESWFKPWSLENIEDERISKILTNYNERLIRA 450
451 HSPNTVSHFYNFYGSRFQYIIINSINILSKKSKFKMLKIMASLFSLRDES 500
501 RKFLAAQYIDVYLSVLYDAVASDAKECQVTLMSILGQYTFQDPSIANMTI 550
551 SSGFIERTIRFAFTLMAFNPEDLMSYLPISLYNGFKLPTETIRNRRTIIC 600
601 FKDLCTIMSANTVPEELLSNEAIFNAIIESFSEFSNVLPLKRETKEHVEV 650
651 ENFDFSAFYFFFSSILIMTDGYTRSISLVKDAAFRKQIVLKLLDVAQTRE 700
701 FESLTNSRKAISPDNASTNENDSNKATLSTVRETICNYVAETINFQVGVN 750
751 TQYFFNPMSYLFKFVIQWSQCGRYEPIPASLTNYINLFEVFQDKQKALYI 800
801 SESALSTLVLIGQINVGFWVRNGTPITHQARMYTKYSMREFTYISDIFNV 850
851 QFSMAMCNPDELMVTYLSRWGLKHWANGVPMYDYPDTETTVAVVNECILL 900
901 LIQLLTEVRSLVMKSSKEGFERTFKSEIIHALCFDTCSYAQIVNCIPEHI 950
951 TKHPSFDIYLEKYANYTSPVSLTDNGIFVLKEKYKDEIDPYYIGLSSSRR 1000
1001 YDVEKNIRLNMANLKKMKYEDTFVPAKKVKDLLKNTLFSGLYSISSVNTF 1050
1051 GLFLKNTLDHIIKYDYDNLLPRVVHLIHLCVVNNLNEFMGILWHEYAIVD 1100
1101 TEFCHYHSIGSILYYCLLKDNFSESHGKIREIFRYLMETAPHVNVNSYLR 1150
1151 EQTTSYTPGILWPTKEDKSHKDKEFERKKHLARLRKKKLMKKLAQQQMKF 1200
1201 MENNSVDTSDISTPRTTSPSLSPTRINAENSSNTINSCCDDDCVFCKMPK 1250
1251 DDDVFVYFSYQERNICDHGIDFTNPTDVNRINSLFSGKQTKDSAIQENPQ 1300
1301 DDDGTRLKFTSCEPVLRACGHGSHTKCLSGHMKSIRGIQNQTTKNIPLSY 1350
1351 GSGLIYCPVCNSLSNSFLPKTNDIDKRTSSQFFMCIEKRSEAEENLDPMS 1400
1401 SICIKAAMILGDLQGKKVTTIEDAYKVVNSVFINTISNTELRLRSHKKEG 1450
1451 KIVNMERISSQCILTLHLVCELKSFIYKKFVNSKTFSSEISRKIWNWNEF 1500
1501 LIKGNNVNLLLYMSQNFDNIDGGKTPQPPNLCIYEMFKRRFHQLLLLLAR 1550
1551 DMMRVNFYKDCRNKIKISSNGSEEPSTSFSYLFNTFKKYVDLFKPDDVRF 1600
1601 DFTSLEKIKDFICSLLLESLSIFCRRTFLLFNIQYDDDGDGDNNNNRSNN 1650
1651 FMDVKQREIELIFRYFKLPNLTHFLKDFFYNELTQNIERYNDGNDNLRIQ 1700
1701 QVIYDMVQNINTRAYPSPEHIQLIELPLNLSKFSLDNDEISNKCDKYEIA 1750
1751 VCLLCGQKCHIQKSIALQGYLQGECTDHMRNGCEITSAYGVFLMTGTNAI 1800
1801 YLSYGKRGTFYAAPYLSKYGETNEDYKFGTPVYLNRARYANLANEIVFGN 1850
1851 MIPHIVFRLTDGSADLGGWETM 1872
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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