 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q86UW6 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MPRRRKNLGGNPFRKTANPKEVVVSSVASREEPTTTLPSMGETKVDQEEL 50
51 FTSISEIFSDLDPDVVYLMLSECDFKVENAMDCLLELSATDTKIEESSSQ 100
101 SFVASENQVGAAESKIMEKRPEEESEDSKMDSFLDMQLTEDLDSLIQNAF 150
151 EKLNSSPDDQVYSFLPSQDVNSFNDSSEFINPDSSNMTPIFSTQNMNLNG 200
201 ENLENSGSTLSLNPLPSHSVLNESKCFIKDNTLALESNYPEDSLLSSSLN 250
251 VASDSIAGCSSLNQKQKELLESECVEAQFSEAPVDLDASEPQACLNLPGL 300
301 DLPGTGGDQKSTRVSDVFLPSEGFNFKPHKHPELPTKGKDVSYCPVLAPL 350
351 PLLLPPPPPPPMWNPMIPAFDLFQGNHGFVAPVVTTAAHWRSVNYTFPPS 400
401 VISHTSPTKVWRNKDGTSAYQVQETPVSQVVRKKTSYVGLVLVLLRGLPG 450
451 SGKSFLARTLQEDNPSGVILSTDDYFYINGQYQFDVKYLGEAHEWNQNRA 500
501 KEAFEKKISPIIIDNTNLQAWEMKPYVALSQKHKYKVLFREPDTWWKFKP 550
551 KELARRNIHGVSKEKITRMLEHYQRFVSVPIIMSSSVPEKIERIELCAYS 600
601 CEDRSTSPRDDEDIISEKEENILSLSLKHLEFTEEKNLDVTKETMLPENV 650
651 AYLSNADLNKRRKEISDMNPSIQSALILETPHMYFSDSESKLQATDKSEN 700
701 EQIEMVAVKGYSKTDTDSSMERVSPSTCCSENNQEDCDLANSGPLQNEKS 750
751 SPGEIVEERATVTKKAFGKQKSKSTLEKFPRHELSNFVGDWPVDKTIGQR 800
801 TKRNRKTEKTSSVQSDKKYNYPQSHKLVNSVSVNTDCVQQRGSPHESVED 850
851 GRKSQCDDASEPLNSYKYDAYKNIDKNSFNIMGDWPSSDSLAQREHRSRM 900
901 PKTGLSEPNLEIGTNDKMNEISLSTAHEACWGTSSQKLKTLGSSNLGSSE 950
951 MLLSEMTCESQTCLSKKSHGQHTSLPLTFTNSAPTVSGVVEPQTLAECQE 1000
1001 QMPKRDPGKEVGMCTQTEPQDFALLWKIEKNKISISDSIKVLTGRLDGFK 1050
1051 PKVFNINTKSDVQEAIPYRVMYDKSTFVEESELTSADESENLNILCKLFG 1100
1101 SFSLEALKDLYERCNKDIIWATSLLLDSETKLCEDTEFENFQKSCDGSQI 1150
1151 GPFSLGLNLKEIISQRGTLENSNSPVPEFSHGIGISNADSQSTCDAERGN 1200
1201 SEQAEMRAVTPENHESMTSIFPSAAVGLKNNNDILPNSQEELLYSSKQSF 1250
1251 PGILKATTPKDMSETEKNLVVTETGDNIHSPSHFSDIFNFVSSTSNLELN 1300
1301 EEIYFTDSLEIKRNENFPKDYVKFSDEEEFMNEDEKEMKEILMAGSSLSA 1350
1351 GVSGEDKTEILNPTPAMAKSLTIDCLELALPPELAFQLNELFGPVGIDSG 1400
1401 SLTVEDCVVHIDLNLAKVIHEKWKESVMERQRQEEVSCGKFMQDPSLVGH 1450
1451 TGLDNPEQKSSQRTGKKLLKTLTASEMLPLLDHWNTQTKKVSLREIMSEE 1500
1501 IALQEKHNLKRETLMFEKDCATKLKEKQLFKIFPAINQNFLVDIFKDHNY 1550
1551 SLEHTVQFLNCVLEGDPVKTVVAQEFVHQNENVTSHTGQKSKEKKPKKLK 1600
1601 ETEETPSELSFQDFEYPDYDDYRAEAFLHQQKRMECYSKAKEAYRIGKKN 1650
1651 VATFYAQQGTLHEQKMKEANHLAAIEIFEKVNASLLPQNVLDLHGLHVDE 1700
1701 ALEHLMRVLEKKTEEFKQNGGKPYLSVITGRGNHSQGGVARIKPAVIKYL 1750
1751 ISHSFRFSEIKPGCLKVMLK 1770
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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