 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q60767 from www.uniprot.org...
The NucPred score for your sequence is 0.54 (see score help below)
1 MRTGRVTPGLAAGLLLLLLRSFGLVEPSESSGNDPFTIVHENTGKCIQPL 50
51 SDWVVAQDCSGTNNMLWKWVSQHRLFHLESQKCLGLDITKATDNLRMFSC 100
101 DSTVMLWWKCEHHSLYTAAQYRLALKDGYAVANTNTSDVWKKGGSEENLC 150
151 AQPYHEIYTRDGNSYGRPCEFPFLIGETWYHDCIHDEDHSGPWCATTLSY 200
201 EYDQKWGICLLPESGCEGNWEKNEQIGSCYQFNNQEILSWKEAYVSCQNQ 250
251 GADLLSIHSAAELAYITGKEDIARLVWLGLNQLYSARGWEWSDFRPLKFL 300
301 NWDPGTPVAPVIGGSSCARMDTESGLWQSVSCESQQPYVCKKPLNNTLEL 350
351 PDVWTYTDTHCHVGWLPNNGFCYLLANESSSWDAAHLKCKAFGADLISMH 400
401 SLADVEVVVTKLHNGDVKKEIWTGLKNTNSPALFQWSDGTEVTLTYWNEN 450
451 EPSVPFNKTPNCVSYLGKLGQWKVQSCEKKLRYVCKKKGEITKDAESDKL 500
501 CPPDEGWKRHGETCYKIYEKEAPFGTNCNLTITSRFEQEFLNYMMKNYDK 550
551 SLRKYFWTGLRDPDSRGEYSWAVAQGVKQAVTFSNWNFLEPASPGGCVAM 600
601 STGKTLGKWEVKNCRSFRALSICKKVSEPQEPEEAAPKPDDPCPEGWHTF 650
651 PSSLSCYKVFHIERIVRKRNWEEAERFCQALGAHLPSFSRREEIKDFVHL 700
701 LKDQFSGQRWLWIGLNKRSPDLQGSWQWSDRTPVSAVMMEPEFQQDFDIR 750
751 DCAAIKVLDVPWRRVWHLYEDKDYAYWKPFACDAKLEWVCQIPKGSTPQM 800
801 PDWYNPERTGIHGPPVIIEGSEYWFVADPHLNYEEAVLYCASNHSFLATI 850
851 TSFTGLKAIKNKLANISGEEQKWWVKTSENPIDRYFLGSRRRLWHHFPMT 900
901 FGDECLHMSAKTWLVDLSKRADCNAKLPFICERYNVSSLEKYSPDPAAKV 950
951 QCTEKWIPFQNKCFLKVNSGPVTFSQASGICHSYGGTLPSVLSRGEQDFI 1000
1001 ISLLPEMEASLWIGLRWTAYERINRWTDNRELTYSNFHPLLVGRRLSIPT 1050
1051 NFFDDESHFHCALILNLKKSPLTGTWNFTSCSERHSLSLCQKYSETEDGQ 1100
1101 PWENTSKTVKYLNNLYKIISKPLTWHGALKECMKEKMRLVSITDPYQQAF 1150
1151 LAVQATLRNSSFWIGLSSQDDELNFGWSDGKRLQFSNWAGSNEQLDDCVI 1200
1201 LDTDGFWKTADCDDNQPGAICYYPGNETEEEVRALDTAKCPSPVQSTPWI 1250
1251 PFQNSCYNFMITNNRHKTVTPEEVQSTCEKLHSKAHSLSIRNEEENTFVV 1300
1301 EQLLYFNYIASWVMLGITYENNSLMWFDKTALSYTHWRTGRPTVKNGKFL 1350
1351 AGLSTDGFWDIQSFNVIEETLHFYQHSISACKIEMVDYEDKHNGTLPQFI 1400
1401 PYKDGVYSVIQKKVTWYEALNACSQSGGELASVHNPNGKLFLEDIVNRDG 1450
1451 FPLWVGLSSHDGSESSFEWSDGRAFDYVPWQSLQSPGDCVVLYPKGIWRR 1500
1501 EKCLSVKDGAICYKPTKDKKLIFHVKSSKCPVAKRDGPQWVQYGGHCYAS 1550
1551 DQVLHSFSEAKQVCQELDHSATVVTIADENENKFVSRLMRENYNITMRVW 1600
1601 LGLSQHSLDQSWSWLDGLDVTFVKWENKTKDGDGKCSILIASNETWRKVH 1650
1651 CSRGYARAVCKIPLSPDYTGIAILFAVLCLLGLISLAIWFLLQRSHIRWT 1700
1701 GFSSVRYEHGTNEDEVMLPSFHD 1723
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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