 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9DBV3 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MPPPRTREGRGHRDRDHHRAPREEEAPEKWDWNCPETRCLLEDVFFRDED 50
51 YIRRGSEECQKFWAFFERLQRFQHLKTSQKKKKDPGMPKHGIAALADLPL 100
101 TYDPRYRINLSILSPDTRGRHGPGRGLPPERVSEFRRALLHYLDFQQKQA 150
151 FGRLAKLQRERAALPIAQYGNRILQTLKEHQVVVVAGDTGCGKSTQVPQY 200
201 LLAAGFSHVACTQPRRIACISLAKRVGFESLSQYGSQVGYQIRFESTRSA 250
251 ATKIVFLTVGLLLRQIQREPSLPQYQVLIVDEVHERHLHNDFLLGVLQRL 300
301 LPQRPDLKVILMSATINISLFSSYFSHAPVVQVPGRLFPITVVYQPQEAD 350
351 QTASKSEKLDPRPFLRVLEAIDNKYPPEERGDLLVFLSGMAEITTVLDAA 400
401 QAYASLTQRWVVLPLHSALSVSDQDKVFDVAPAGVRKCILSTNIAETSVT 450
451 IDGIRFVVDSGKVKEMSYDPQAKLQRLQEFWISQASAEQRKGRAGRTGPG 500
501 VCYRLYAESDYDAFAPYPVPEIRRVALDALVLQMKSMSVGDPRTFPFIEP 550
551 PPPASVETAILYLQEQGALDSSEALTPIGSLLAQLPVDVVIGKMLILGSM 600
601 FSLAEPVLTIAAALSVQSPFTRSAQSNLDCATARRPLESDQGDPFTLFNV 650
651 FNAWVQVKSERSGNSRKWCRRRGVEEHRLYEMANLRRQFKELLEDHGLLS 700
701 GAQVVAPGDSYSRLQQRRERRALHQLKRQHEEGGGRRRKVLRLQEDGCSS 750
751 DEEDRKGSTSQRADSVDIQDVKFKLRHNLEQLQAAASSAQDLTRDQLALL 800
801 KLVLGRGLYPQLAVPDAFNSGRKDSDQIFHTQAKQGTVLHPTCVFANSPE 850
851 VLHTQGQEASGQEGSQDGRDQMSCKHQLLAFVSLLETNKPYLVNCVRIPA 900
901 LQSLLLFSRSIDTNGDCSRLVADGWLELQLADSESAVRLLATSLRLRAHW 950
951 ESALDRQLARQAQRRKLEQEEDVGSPAVSPQEVAALSRELLQFMAAKVPY 1000
1001 RLRRLTGLEAQNLYVGPQTITTAPSLPGLFGNSTLSPHPTKGGYAVSDYL 1050
1051 TYNCLTSDTDLYSDCLRSFWTCPHCGLHMPFTPLERIAHENTCPEAPGDD 1100
1101 PGSEEAAPAPPQKTSALQRPYHCQVCGQDFLFTPTEVLRHRRQHV 1145
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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