 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q63679 from www.uniprot.org...
The NucPred score for your sequence is 0.67 (see score help below)
1 MYKSLLDKAGLGSITSVRFLGDQQSVFVSKDLLKPIQDVNSLRLSLTDNQ 50
51 TVSKEFQALIVKHLDESHLLQGDKNLVGSEVRIYSLDPSTQWFSATVVHG 100
101 NPSSKTLQVNCEEIPALKIVDPALIHVEVVHDNFVTCGNSTRIGAVKRKS 150
151 SENNGSSVSKQAKSCSEVSPSMCPVQSVPTTVCKEILLGCTAATPSSNRQ 200
201 QNTPQAANSPPNIGAKLPQGCHKQSLPEEISSCLNTKSEVLRTKPDVCKA 250
251 GLLSSKSSQVGAGDLKILSEPKGSCIQPKTNTDQESRLESTPQPVTGLTK 300
301 ECLVTKTSSKAELDNATAPELQKRLEHTASTPDGLSDKPEVEAGVTRLNS 350
351 CSEKKVGPSDLGSQSQNLKETSVKVDHDSCCTRSSNKTQTPPARKSVLTD 400
401 PDKLKKLQQSGEAFVQDDSCVNIVAQLPKCRECRLDSLRKDKDQQKDSPV 450
451 FCRFFHFRRLQFNKHGVLRVEGFLTPNKYDSEAIGLWLPLTKNVVGTDLD 500
501 TAKYILANIGDHFCQMVISEKEAMSTIEPHRQVAWKRAVKGVREMCDVCD 550
551 TTIFNLHWVCPRCGFGVCVDCYRLKRKNCQQGAAYKTFSWIRCVKSQIHE 600
601 PENLMPTQIIPGKALYDVGDIVHSVRAKWGIKANCPCSNRQFKLFSKPAL 650
651 KEDLKQASLSGEKPSLGTMVQQSSPVLEPAAVCGEAPSKPASNVKPICPA 700
701 NTSPLNWLADLTSGNVNKENKEKQLTMPILKNEIKCLPPLPPLNKSSTVL 750
751 HTFNSTILTPVSNNNSGFLRNLLNSSTGKTENGLKNTPKILDDIFASLVQ 800
801 NKTSSDLSKRPQGLTIKPSILGFDTPHYWLCDNRLLCLQDPNNKSNWNVF 850
851 RECWKQGQPVMVSGVHHKLNTELWKPESFRKEFGEQEVDLVNCRTNEIIT 900
901 GATVGDFWDGFEDVPNRLKNEKEKEPMVLKLKDWPPGEDFRDMMPSRFDD 950
951 LMANIPLPEYTRRDGKLNLASRLPNYFVRPDLGPKMYNAYGLITPEDRKY 1000
1001 GTTNLHLDVSDAANVMVYVGIPKGQCEQEEEVLRTIQDGDSDELTIKRFI 1050
1051 EGKEKPGALWHIYAAKDTEKIREFLKKVSEEQGQENPADHDPIHDQSWYL 1100
1101 DRSLRKRLYQEYGVQGWAIVQFLGDVVFIPAGAPHQVHNLYSCIKVAEDF 1150
1151 VSPEHVKHCFWLTQEFRHLSQTHTNHEDKLQVKNVIYHAVKDAVAMLKAV 1200
1201 NPVWANVNSSAHWR 1214
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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