 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8MQW8 from www.uniprot.org...
The NucPred score for your sequence is 0.92 (see score help below)
1 MVNAVMDAIALLSSLASDLDIMLNDLRSAPSHAATATATATTTATVATAT 50
51 ATTTANRQQQHHNHHNQQQMQSRQLHAHHWQSINNNKNNNISNKNNNNNN 100
101 NNNNNINNNNNNNNHSAHPPCLIDIKLKSSRSAATKITHTTTANQLQQQQ 150
151 RRRVAPKPLPRPPRRTRPTGQKEVGPSEEDGDTDASDLANMTSPLSASAA 200
201 ATRINGLSPEVKKVQRLPLWNARNGNGSTTTHCHPTGVSVQRRLPIQSHQ 250
251 QRILNQRFHHQRMHHGTSEPIPSGVATPSSLDSASVDGGKSHTGNNNNIN 300
301 NNHNGQQSQKSQQQAGLAAKLNVLAQSNLNNNNTTNQPGSMTPASNRTGL 350
351 DSNQNQKQNLNADSRRSSSVDPDADADDVVDAAHGGAFEDDMQALLPKCS 400
401 RRSRDELSQSRTSLVSSSEGGILAEGETSSEDDEEEPVEAEDEGEESSRD 450
451 SSDNSPPCDLGLMERLLVTHPMWFLPGIQRSGAVHLLQGKEEGTFIVRGS 500
501 SQPNTMAVSVRLPQDTGPYIEHYLIQSHDNVLSLESSRFTFGSIPSLIAH 550
551 YAQCCDELPVQLMLPRVLREANNRKKLSSLALLGQEFWSYVSSPALLGPL 600
601 TPSVAPSKDQQLLDAKSPLSLTETSGLGTATFFSDTVSKPPPTGAPPLPG 650
651 GGLFSPTGSGQLLGFFSQAGTPSDTTNSSLSSFTTSGGQHMQLLSPNSVD 700
701 SVILTMSPVDNPGHYLPGSTGAPMAPLCPSVVDQQLSTFKVAQTAPEVDQ 750
751 VRPQRPKPPNTLNLKPPAPPLRWSKPHSPDQNGSANGNFTVTTTVTFSME 800
801 NGGGGGSGPTVGNGNGKFVEVTTPAASNPFNALLNGQASTFQTFAKRLSP 850
851 EGECKDTLSSQGSSSNDSRWPPPARKLLTSPMTPLTPSGGSSSSGGKSRK 900
901 SRAGKESQHYKESDILESPPMQYCASALSDKISDYEDVWSHDPSDRASLL 950
951 TSFRPALDTVGGVMNRRPDLLAETPSTPTPTQQSHLTPCEEETTATPNES 1000
1001 SSQSLLQFSGDVPARSRAGLLLPNLSGQVPPVAMTKSMTAAEDDGGDTTP 1050
1051 TAEGQANGASRSKQGSPFYAEPADALRQAGLTSAATAILRRQHRSQMLHA 1100
1101 SQRHSEPLKAGFGGSGNGAMLQPSDLEKLAGSLDELKPKPKVSQQQQQSQ 1150
1151 QQQQPTKRARNRIDHWQLDSSWEFMAKQDTGSHAGGDYDTAAIDWQEKEN 1200
1201 SLGRDSRADGQGKKRTLTIHQIIANRLPDLNLPELVRCSTPPQTAALQPH 1250
1251 VLGQDKAGVGCDGSQKSFQSQIGCRLSSYDNVFCQNSFGGIDSAQSDDGT 1300
1301 IFSEPWDSSQWDTFLPHDDATINSDTIHLSKCRPALSEDDTIVEELQSTK 1350
1351 DGSNGSCNQDTLKANRNGAGHHKLNNGNGNGKANNRPKVATILRNPSMRD 1400
1401 REVLCHPRNKMSIQSSGPGDSLRAYTLQLAQDPSSTFARNIENFICCTKE 1450
1451 SREAAPQVVMRNMRQFMSGMKNYLVKHGEGKFHAELETARARLKSDEFLN 1500
1501 LDAMLETVMHQLVVLPLREHLYGIFVDHYQRSEDIQLLAQNVRYACEREA 1550
1551 ADFGIRPTVTPPSQAALRLIANLLWRLQEAELPLDKLELFLCVISTVFDA 1600
1601 TGCPRGQQLGADDFLPVLVYVVAKCGFVGAEIEAEFMWGLLQPTLLNGEP 1650
1651 GYYLTALCSAVQVLKTFMASEGESGSGSLDWRSSCLPACSSVLRVIIPDE 1700
1701 CNGSLQTRTLPVRPHTTTREVCRIIAHKARITNPQDYALFKLVDGEETLL 1750
1751 TDAECPQDARLAAKGKHCMLAYKRIDAKIAWPTAQLAGH 1789
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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