 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q864U1 from www.uniprot.org...
The NucPred score for your sequence is 0.97 (see score help below)
1 MDLSADHVEEVQNVLNAMQKILECPICLELIKEPVSTKCDHIFCKFCMLK 50
51 LLNQKKGPSQCPLCKNDITKRSLQESTRFSQLVEELLKIIHAFELDTGLQ 100
101 FANSYNFSRKEDNSPEHLKEEVSIIQSMGYRNRAKRLWQSEPENPTLQET 150
151 SLTVELSNLGIVRSLRTKQQTQSQNKSVYIELGSDSSEDTVNKASYFSVG 200
201 DHELLEITPQGAKAKTNLNPAEKAACEFSEKDITNTEHHQLSIKDLITTQ 250
251 KHATETHPEKYQGISVSDFHVEPCGTDTHASSLQHENSSLLLTENRLNVE 300
301 KAEFCNKSKQPVLVKSQQSRWAESKGTCKDRQIPSTEKKIVLNTDPLYRR 350
351 KELRKQKPACPDSPGDSQDVPWVTLNNSIQKVNDWFSRSDEILTSDDSCD 400
401 GGSESNNEVAGAVEIPNKVDGYSGSSEKINLMASDPHGTLIHERVHSKPV 450
451 ESNIEDKIFGKTYRRKSSLPNFSHIAEDLILGAFTVEPQITQEQPLTNKL 500
501 KCKRRGTSGLQPEDFIKKVDLTIVPKTPEKMTEGTDQTEQKCHGMNITSD 550
551 GHENKTKRDYVQKEQNANPAESLEKESVFRTEAEPISISISNMELELNIH 600
601 RSKAPKNRLKRKSSTRKIPELELVVSRNPSLPNHTELPIDSSSSNEEMKK 650
651 KHSSQMPVRQSQKLQLIGDKELTAGAKNNKTYEQINKRLASDAFPELKLT 700
701 NTPGYFTNCSSKPEEFVHPSLQREENLGTIQVSNSTKDPKDLILREGKAL 750
751 QIERSVESTNISLVPDTDYSTQDSISLLEAKTPEKAKTAPNPCVSLCTAT 800
801 KNLKELIHRDFKDTKNNTEGFQDLLGHDINYVIQETSREMEDSELDTQYL 850
851 QNTFKASKRQTFALFSNPGNPQKECATVFAHSGSLRDQSPRDPLKCRQKE 900
901 DSQGKSESKSQHVQAICTTVHFPVADQQDRTPGDDAKCSAKEVTRVCQSS 950
951 QLRGHKTELVFANKQGVSEKPNLIPSLSPIKSSVKTICKKSPSEKFEEPV 1000
1001 TSPEKTLGSESIIQSAVSTISQNNIQESTFKEVSSNSVNEVGSSTNEVGS 1050
1051 SVNEVGSSGENIQAEPGRNREPKLRALLGLGLTQPEVYKQSLPVSNCHHP 1100
1101 EIKRQGENEDMPQAVKADFSPCLISDNLEQPTGSRHASQVCSETPDNLLN 1150
1151 DDEIKENSHFAESDIKERSAVFSESVQKGEFRGSPGPFTHTHLAQGHQRG 1200
1201 AGKLESEETVSSEDEELPCFQQLLFGKVTSTLSPSTGCNTVATEGLSKET 1250
1251 EGNLESLKSGLNDCSGQVTSAKVSQEHHLNEEARCSGSLFSSQCSAMEDL 1300
1301 TTNTNTQDPFLMFERPSKQVYQSESEEVLSDKELVSDDEERETGLEEDSC 1350
1351 QEEQSVDSDLGEAVSDHVSETSLSEDGVGLSSQSDILTTQQRDTMQDNLL 1400
1401 KLQQEMAELEAVLERHGSQPSHSSASLTADSRGPEHLLNLEQDTSERAIL 1450
1451 TSEKSRDYSRSQNPESLSADKFPVSLDSSTNKNKEPGMERSSASKFQLSY 1500
1501 NRWYMHSSRSLQDRNCPSQKEPINVADMEEQQLAKREAQDLMGSFLPRQD 1550
1551 QEGTPYLKSGISLFSHEPESDPSEDRAAEPAHVHSMPPSASALKLSQFRV 1600
1601 EESTKNPAAAHIANTTRCNLREESMSKEKPEVISSTERSKKRLSMVASGL 1650
1651 TPKELMLVQKFARKHHVTLTNLITEETTHVIMKTDPEFVCERTLKYFLGI 1700
1701 AGGKWVVSYFWVTQSIKEGKMLDEHDFEVRGDVVNGRNHQGPKRARESRD 1750
1751 KKIFKGLEICCYGPFTNMPTDQLEWMVQLCGASVVKEPSSFTPDQGTHPV 1800
1801 VVVQPDAWTEDAGFHVIGQMCEAPVVTREWVLDSVALYQCQELDTYLVP 1849
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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