 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O60072 from www.uniprot.org...
The NucPred score for your sequence is 0.62 (see score help below)
1 MEVELNYVVNHLEKLGPASFCDTPYSFSLSDSNAELGALSLKVDEILKTN 50
51 YNLINPEDVTDSDNNEFALKDLTWLQNCCNEISQSSSTELDASVLFEAVI 100
101 MSLKATEDQCAIQEDLLNLVGLDHIDLISDIVANSSNLIEEYMNQNDTSI 150
151 AAQLSDGYTSEAGSSATHGQGLLDSLKSRPRRFSRSRDNRGPLFTGQQVF 200
201 EVEKYPHVYGDKRLGNTISVIGKKFALPAGSEREDYQKYEEIIVPHAQRA 250
251 PQMQGEKLLEISSMDILCRKTFLSYQTLNRIQSLVYPIAYKTNENMLICA 300
301 PTGAGKTDVALLAMLQTISNYVESMNLMDESEPLDVHRDDFKIVYIAPMK 350
351 ALAAEVVEKMGKRLAWLGLKTRELTGDMQLTKTEIAETQILVTTPEKWDV 400
401 VTRKSVGDTQLAEKVRLVIIDEVHMLHDERGAVIESLVARTQRLVETSQQ 450
451 MIRIVGLSATLPNYLDVADFLGVNRYKGLFYFSSAFRPCPIEQHFIGAKG 500
501 SPKIVNSNIDEACFDKVLKLIQEGHQVMIFVHSRKETINSAKKLREQFFH 550
551 EGEADLLDNSQHEKYSLAQRDVSKSKNKELKELFKYSMGIHNAGMLRSDR 600
601 HLTERLFSMGILKILCCTATLAWGVNLPAYAVLIKGTQLYDPQKGSFVDL 650
651 GVLDVLQIFGRAGRPQFESSAVAYIITTHDKLSHYISVVTQQSPIESRFT 700
701 DRLVDNLNAEVSLGTVTNIDEAVSWLGYTYLYIRMRRNPLVYGIAYDELV 750
751 EDPLLGSKRRELVSVAAGRLADNQMIVYNKKNGYLIPKDLGRIASNYYIN 800
801 YQTVSTLNNLLKSKMSEADIIALLSQCSEFSQIKSRENEHRELESLMENS 850
851 SPCQLRDSISNTSGKVNVILQSYISRAHVEDFTLTSDTNYVAQNAGRITR 900
901 ALFEIAMSRTWASAFTILSLNKSIDRRQWSFEHPLLQFDLPHDLAVKVEN 950
951 QCGSLSLEELSDMSTGELGDLIHNRKMGPTVKKFISKLPLLNINVDLLPL 1000
1001 TKNVLRLVLNITPNFNWDMRYHGNSQMFWIFVEDSNGLEILHHEQLLLNK 1050
1051 RNVSTSHLLSFTIPVSNPLPSQLYIIAVSDKWLGAETVTPVSLSNVVFHD 1100
1101 DSNPITELLDLQPLPITALHDPVLEGICAKRFSFFNAVQTQFFHTIYHTD 1150
1151 TNIFVGAPTGSGKTMAAELATWRALHNYPKSKVVYIAPMKALVKERVKDW 1200
1201 GHRLVEPMGISMIELTGDTNPDVKAVTNANIIITTPEKWDGITRSWKSRK 1250
1251 YVQDVSLIILDEIHLLGSDRGPVLEMIVSRMNYVASQTNKKVRVLGLSTA 1300
1301 VANANDLANWLNIRDGLFNFRHSVRPVPLEIYIDGFPGRAYCPRMMSMNK 1350
1351 PAFQAIKTHSPTQPVLIFVSSRRQTRLTAKDLIAFCGLEDNPRRFLYMDE 1400
1401 EELEMIVSEVEDKSLKLALPFGIALHHAGLTENDRKISEELFVNNKVQIL 1450
1451 IATSTLAWGVNTPAHLVIVKGTEYYDAKIGGYKDMDLTDVLQMLGRAGRP 1500
1501 QFDNSGVARIFVQDIKKSFYKHFLHSGFPVESYLHKVLDNHLNAEIATGT 1550
1551 IDCIQGAMDFLTCTYFYRRVHQNPVYYGADGDDQKSIDTYLSKLVVTAFN 1600
1601 ELEKSACIYRVNEETYAPTTLGRIVSYYYLFHTTIRNFVQKITENAEFDL 1650
1651 ALQLLAEASEFDDLAIRHNEDLINIEINKSLKYSAACLNLPMVDAHVKAF 1700
1701 ILTQAHMARLKLPVDDYVTDTSTVLDQVIRIIQSYIDVSAELGYSHVCLQ 1750
1751 YISLMQCLKQACYPSEIYRASLPGLNASSEKEARDYLNKFAGNKTDELYQ 1800
1801 MLCNDPNVFDIESLVNSLISYPKMNIEVSQSSSDKLLLYLRRLNQPLNPD 1850
1851 FYIFAPLFPKPQSEGFFVLIIDSETQELFAIRRASFAGRRNDDSIRLSLR 1900
1901 ISMDIPPTCRNRNVKVMVVCDGYPLIYEHKIVLMI 1935
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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