 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q3UVR3 from www.uniprot.org...
The NucPred score for your sequence is 0.74 (see score help below)
1 MSGGGEQPDILSVGILVKERWKVLRKIGGGGFGEIYDALDMLTRENVALK 50
51 VESAQQPKQVLKMEVAVLKKLQGKDHVCRFIGCGRNDRFNYVVMQLQGRN 100
101 LADLRRSQSRGTFTISTTLRLGKQILESIESIHSVGFLHRDIKPSNFAMG 150
151 RFPSTCRKCFMLDFGLARQFTNSCGDVRPPRAVAGFRGTVRYASINAHRN 200
201 REMGRHDDLWSLFYMLVEFVVGQLPWRKIKDKEQVGSIKERYDHRLMLKH 250
251 LPPEFSTFLDHISSLDYFTKPDYQLLTSVFDNSIKTFGVIESDPFDWEKS 300
301 GTDGSLTTTTTSATPQLHTRLTPAAIGIANATPIPGDLLRENTDEVFPDE 350
351 QLSDGENGIPVGVSPDKLPGSLGHPRPQEKDVWEEMDINKNKIKLGICKA 400
401 ATEEENSHGQVNGILNAPSLGSPIRVRSEITQPDRDVPLVRKLRSIHSFE 450
451 LEKRLTLEPKPDTDKFLETCMEKMQKDSSAGKEPVPPALPHKPCVPVVTH 500
501 TDHIWHYDDEYLPDASKPASANTPEQADGGGSNGFIAVNLSSCKQEVDSK 550
551 EWVIVDKEQDLQDFRTNEVLGHKTTGSPSDEEPEVLQVLEGSPQDEKIQV 600
601 GPWTDNHHLKKESSGVVLALSAECPATAASELYTDRLDLQAGAASQFITV 650
651 TPTSPMEAQAEGPLTAITIPRPSVASTQSTSGSFHYGPQPEKKDLQPLEP 700
701 TVELYSPRENFSGLVVTEGELASGGSRVDLGLQIDHTGHDMLPNMRDGDT 750
751 SQDLGPKDPPDHNRLAVKEFEHLPGETEERSLLLGSENEDERLSKGQHCI 800
801 EVSSPGELVTAERAQLAATEPLHVSETQNCSVLPNQDKTHEIMKLLAVGT 850
851 SEISPQAIDPHAEGQIGQMAAMQKNKLFKDDGIQSESLPRQQGDLSAFLH 900
901 QEGKREKVVPRNGELYHCVSENEHGPPTRKDMLRSSFVTRHSRIPVLAQE 950
951 IDSTFESSSAISAKEKLLQKKAYQPEIVKLLVEKRQFKSFLGDLSSASDK 1000
1001 LIEEKLAAVPVPFSEEEVFAPFSRLAADSHLSRSVEDSFLSPIISQARKS 1050
1051 KIPRPVSWVSTDQINGSASPQFLPRPPPGKPPVRPGVEARLRRYKVLGSS 1100
1101 NSDSDLFSRLAQILQNGSQKSRSTTQCKSPGSPHNPKTPPKSPVVPRRSP 1150
1151 SASPRSSSLPRTSSSSPSRAGRPHHDQRSSSPHLGRSKSPPSHSGSSSSR 1200
1201 RSCQQEHCKPSKNGPKGSGSLHHHSTSSKTPPGKSKPASKLSR 1243
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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