| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q64318 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MADGPRCKRRKQANPRRNNVTNYNTVVEANSDSDDEDKLHIVEEESITDA 50
51 ADCEGGMPDDELPADQTVLPGGSDRGGGAKNCWQDNVKDNECDSDAENEQ 100
101 NHDPNVEEFLQQQDTAVIYPEAPEEDQRQGTPEASSHDENGTPDAFSQLL 150
151 TCPYCDRGYKRFTSLKEHIKYRHEKNEDNFSCSLCSYTFAYRTQLERHMT 200
201 SHKSGREQRHVTQSGGNRKFKCTECGKAFKYKHHLKEHLRIHSGEKPYEC 250
251 PNCKKRFSHSGSYSSHISSKKCISLMPVNGRPRSGLKTSQCSSPSLSTSP 300
301 GSPTRPQIRQKIENKPLQEPLSVNQIKTEPVDYEFKPIVVASGINCSTPL 350
351 QNGVFSSGGQLQATSSPQGVVQAVVLPTVGLVSPISINLSDIQNVLKVAV 400
401 DGNVIRQVLETNQASLASKEQEAVSASPIQQGGHSVISAISLPLVDQDGT 450
451 TKIIINYSLEQPSQLQVVPQNLKKEIPAPTNSCKSEKLPEDLTVKSETDK 500
501 SFEGARDDSTCLLCEDCPGDLNALPELKHYDPECPAQPPPPAPATEKPES 550
551 SASSAGNGDLSPSQPPLKNLLSLLKAYYALNAQPSTEELSKIADSVNLPL 600
601 DGVKKWFEKMQAGQIPGQSPDPPSPGTGSVNIPTKTDEQPQPADGNEPQE 650
651 DSTRGQSPVKIRSSPVLPVGSAMNGSRSCTSSPSPLNLCSARNPQGYSCV 700
701 AEGAQEEPQVEPLDLSLPKQQGELLERSTVSSVYQNSVYSVQEEPLNLSC 750
751 AKKEPQKDSCVTDSEPVVNVVPPSANPINIAIPTVTAQLPTIVAIADQNS 800
801 VPCLRALAANKQTILIPQVAYTYSATVSPAVQEPPVKVIQPNGNQDERQD 850
851 TSSEGVSTVEDQNDSDSTPPKKKTRKTENGMYACDLCDKIFQKSSSLLRH 900
901 KYEHTGKRPHECGICRKAFKHKHHLIEHMRLHSGEKPYQCDKCGKRFSHS 950
951 GSYSQHMNHRYSYCKRGAEDRDAMEQEDAGPEVLPEVLATEHVGARASPS 1000
1001 QADSDERESLTREEDEDSEKEEEEEDKEMEELQEGKECENPQGEEEEEEE 1050
1051 EEEEEEEEEEEEVEADEAEHEAAAKTDGTVEVGAAQQAGSLEQKASESEM 1100
1101 ESESESEQLSEEKTNEA 1117
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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