 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q7Z5J4 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MQSFRERCGFHGKQQNYQQTSQETSRLENYRQPSQAGLSCDRQRLLAKDY 50
51 YNPQPYPSYEGGAGTPSGTAAAVAADKYHRGSKALPTQQGLQGRPAFPGY 100
101 GVQDSSPYPGRYAGEESLQAWGAPQPPPPQPQPLPAGVAKYDENLMKKTA 150
151 VPPSRQYAEQGAQVPFRTHSLHVQQPPPPQQPLAYPKLQRQKLQNDIASP 200
201 LPFPQGTHFPQHSQSFPTSSTYSSSVQGGGQGAHSYKSCTAPTAQPHDRP 250
251 LTASSSLAPGQRVQNLHAYQSGRLSYDQQQQQQQQQQQQQQALQSRHHAQ 300
301 ETLHYQNLAKYQHYGQQGQGYCQPDAAVRTPEQYYQTFSPSSSHSPARSV 350
351 GRSPSYSSTPSPLMPNLENFPYSQQPLSTGAFPAGITDHSHFMPLLNPSP 400
401 TDATSSVDTQAGNCKPLQKDKLPENLLSDLSLQSLTALTSQVENISNTVQ 450
451 QLLLSKAAVPQKKGVKNLVSRTPEQHKSQHCSPEGSGYSAEPAGTPLSEP 500
501 PSSTPQSTHAEPQEADYLSGSEDPLERSFLYCNQARGSPARVNSNSKAKP 550
551 ESVSTCSVTSPDDMSTKSDDSFQSLHGSLPLDSFSKFVAGERDCPRLLLS 600
601 ALAQEDLASEILGLQEAIGEKADKAWAEAPSLVKDSSKPPFSLENHSACL 650
651 DSVAKSAWPRPGEPEALPDSLQLDKGGNAKDFSPGLFEDPSVAFATPDPK 700
701 KTTGPLSFGTKPTLGVPAPDPTTAAFDCFPDTTAASSADSANPFAWPEEN 750
751 LGDACPRWGLHPGELTKGLEQGGKASDGISKGDTHEASACLGFQEEDPPG 800
801 EKVASLPGDFKQEEVGGVKEEAGGLLQCPEVAKADRWLEDSRHCCSTADF 850
851 GDLPLLPPTSRKEDLEAEEEYSSLCELLGSPEQRPGMQDPLSPKAPLICT 900
901 KEEVEEVLDSKAGWGSPCHLSGESVILLGPTVGTESKVQSWFESSLSHMK 950
951 PGEEGPDGERAPGDSTTSDASLAQKPNKPAVPEAPIAKKEPVPRGKSLRS 1000
1001 RRVHRGLPEAEDSPCRAPVLPKDLLLPESCTGPPQGQMEGAGAPGRGASE 1050
1051 GLPRMCTRSLTALSEPRTPGPPGLTTTPAPPDKLGGKQRAAFKSGKRVGK 1100
1101 PSPKAASSPSNPAALPVASDSSPMGSKTKETDSPSTPGKDQRSMILRSRT 1150
1151 KTQEIFHSKRRRPSEGRLPNCRATKKLLDNSHLPATFKVSSSPQKEGRVS 1200
1201 QRARVPKPGAGSKLSDRPLHALKRKSAFMAPVPTKKRNLVLRSRSSSSSN 1250
1251 ASGNGGDGKEERPEGSPTLFKRMSSPKKAKPTKGNGEPATKLPPPETPDA 1300
1301 CLKLASRAAFQGAMKTKVLPPRKGRGLKLEAIVQKITSPSLKKFACKAPG 1350
1351 ASPGNPLSPSLSDKDRGLKGAGGSPVGVEEGLVNVGTGQKLPTSGADPLC 1400
1401 RNPTNRSLKGKLMNSKKLSSTDCFKTEAFTSPEALQPGGTALAPKKRSRK 1450
1451 GRAGAHGLSKGPLEKRPYLGPALLLTPRDRASGTQGASEDNSGGGGKKPK 1500
1501 MEELGLASQPPEGRPCQPQTRAQKQPGHTNYSSYSKRKRLTRGRAKNTTS 1550
1551 SPCKGRAKRRRQQQVLPLDPAEPEIRLKYISSCKRLRSDSRTPAFSPFVR 1600
1601 VEKRDAFTTICTVVNSPGDAPKPHRKPSSSASSSSSSSSFSLDAAGASLA 1650
1651 TLPGGSILQPRPSLPLSSTMHLGPVVSKALSTSCLVCCLCQNPANFKDLG 1700
1701 DLCGPYYPEHCLPKKKPKLKEKVRPEGTCEEASLPLERTLKGPECAAAAT 1750
1751 AGKPPRPDGPADPAKQGPLRTSARGLSRRLQSCYCCDGREDGGEEAAPAD 1800
1801 KGRKHECSKEAPAEPGGEAQEHWVHEACAVWTGGVYLVAGKLFGLQEAMK 1850
1851 VAVDMMCSSCQEAGATIGCCHKGCLHTYHYPCASDAGCIFIEENFSLKCP 1900
1901 KHKRLP 1906
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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