 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q96RT7 from www.uniprot.org...
The NucPred score for your sequence is 0.83 (see score help below)
1 MASITQLFDDLCEALLPAAKTHLGQRSVNRKRAKRSLKKVAYNALFTNLF 50
51 QDETQQLQPDMSKLPARNKILMLSFDLRVGGLGPKADRLEELVEELEAAP 100
101 CCPLLEVGSVLDLLVQLAGSGPPQVLPRKRDYFLNNKHVGRNVPYSGYDC 150
151 DDLSVFEMDVQSLISREECLCHSMIQETLQVMEAAPGTGLPTVGLFSFGD 200
201 PCGDRFERDTRVSLFGALVHSRTYDMDVRLGLPPVPDNADLSGLAIKVPP 250
251 SVDQWEDEGFQSASNLTPDSQSEPSVTPDVDLWEAALTYEASKRRCWERV 300
301 GCPPGHREEPYLTEAGRDAFDKFCRLHQGELQLLAGGVLQAPQPVLVKEC 350
351 ELVKDVLNVLIGVVSATFSLCQPAQAFVVKRGVHVSGASPESISSLLSEV 400
401 AEYGTCYTRLSHFSLQPVLDSLYSKGLVFQAFTSGLRRYLQYYRACVLST 450
451 PPTLSLLTIGFLFKKLGRQLRYLAELCGVGAVLPGTCGGGPRAAFPTGVK 500
501 LLSYLYQEALHNCSNEHYPVLLSLLKTSCEPYTRFIHDWVYSGVFRDAYG 550
551 EFMIQVNHEYLSFRDKLYWTHGYVLISKEVEDCVPVFLKHIAHDIYVCGK 600
601 TINLLKLCCPRHYLCWSDVPVPRISVIFSLEELKEIEKDCAVYVGRMERV 650
651 ARHSSVSKEEKELRMEIAKQELIAHAREAASRVLSALSDRQMSERMALDA 700
701 RKREQFQRLKEQFVKDQERRQAARQEELDDDFSYARELRDRERRLKSLEE 750
751 ELERKARQALVDHYSKLSAEAARREQKALWRIQRHRLESARLRFLLEDEK 800
801 HIQEMLKAVSEAHQPQEPPDVLLSVHPQVTSPGPEHPEGGQGCDSGSAEQ 850
851 HSPAWDGWNRPGLLTPQPLKPLAVGAGGRGLQQAEGARPFSDSLSIGDFL 900
901 PVGPGAEPSVQTGMVPLLEVALQTINLDLPPSAPGEAPAAASTQPSRPQE 950
951 YDFSTVLRPAVATSPAPGPLQAAECSLGSSGLQLWEDSCGKMDACGSASR 1000
1001 ETLLPSHPPRRAALEEGSSQPTERLFGQVSGGGLPTGDYASEIAPTRPRW 1050
1051 NTHGHVSDASIRVGENVSDVAPTQPRWNTHGHVSNASISLGESVSDVAPT 1100
1101 RPRWNIHGHVSNASIRVGENVSDVAPTRPRWNTHGHVSNASIRVGENVSD 1150
1151 VAPTRPRWNTHGHVSDASISLGESVSDMAPARPRWNTHGHVSDASISLGE 1200
1201 SVSDMAPTRPRWNTHGHVSDTSIRVGENVSDVAPIRSRCNTHGHVSDASI 1250
1251 SLGEPVSDVVSTRPRWNTHVPIPPPHMVLGALSPEAEPNTPRPQQSPPGH 1300
1301 TSQSALSLGAQSTVLDCGPRLPVEVGPSLSSPSSGCGEGSISVGENVSDV 1350
1351 APTQPWWPNTPGDSVSEELGPGRSGDTEDLSPNWPLNSQEDTAAQSSPGR 1400
1401 GEEAEASAAEAQGGEQAYLAGLAGQYHLERYPDSYESMSEPPIAHLLRPV 1450
1451 LPRAFAFPVDPQVQSAADETAVQLSELLTLPVLMKRSITAPLAAHISLVN 1500
1501 KAAVDYFFVELHLEAHYEALRHFLLMEDGEFAQSLSDLLFEKLGAGQTPG 1550
1551 ELLNPLVLNSVLSKALQCSLHGDTPHASNLSLALKYLPEVFAPNAPDVLS 1600
1601 CLELRYKVDWPLNIVITEGCVSKYSGVFSFLLQLKLMMWALKDVCFHLKR 1650
1651 TALLSHMAGSVQFRQLQLFKHEMQHFVKVIQGYIANQILHVTWCEFRARL 1700
1701 ATVGDLEEIQRAHAEYLHKAVFRGLLTEKAAPVMNVIHSIFSLVLKFRSQ 1750
1751 LISQAWGPPGGPRGAEHPNFALMQQSYNTFKYYSHFLFKVVTKLVNRGYQ 1800
1801 PHLEDFLLRINFNNYYQDA 1819
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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