 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q86WG5 from www.uniprot.org...
The NucPred score for your sequence is 0.72 (see score help below)
1 MARLADYFIVVGYDHEKPGSGEGLGKIIQRFPQKDWDDTPFPQGIELFCQ 50
51 PGGWQLSRERKQPTFFVVVLTDIDSDRHYCSCLTFYEAEINLQGTKKEEI 100
101 EGEAKVSGLIQPAEVFAPKSLVLVSRLYYPEIFRACLGLIYTVYVDSLNV 150
151 SLESLIANLCACLVPAAGGSQKLFSLGAGDRQLIQTPLHDSLPITGTSVA 200
201 LLFQQLGIQNVLSLFCAVLTENKVLFHSASFQRLSDACRALESLMFPLKY 250
251 SYPYIPILPAQLLEVLSSPTPFIIGVHSVFKTDVHELLDVIIADLDGGTI 300
301 KIPECIHLSSLPEPLLHQTQSALSLILHPDLEVADHAFPPPRTALSHSKM 350
351 LDKEVRAVFLRLFAQLFQGYRSCLQLIRIHAEPVIHFHKTAFLGQRGLVE 400
401 NDFLTKVLSGMAFAGFVSERGPPYRSCDLFDELVAFEVERIKVEENNPVK 450
451 MIKHVRELAEQLFKNENPNPHMAFQKVPRPTEGSHLRVHILPFPEINEAR 500
501 VQELIQENVAKNQNAPPATRIEKKCVVPAGPPVVSIMDKVTTVFNSAQRL 550
551 EVVRNCISFIFENKILETEKTLPAALRALKGKAARQCLTDELGLHVQQNR 600
601 AILDHQQFDYIIRMMNCTLQDCSSLEEYNIAAALLPLTSAFYRKLAPGVS 650
651 QFAYTCVQDHPIWTNQQFWETTFYNAVQEQVRSLYLSAKEDNHAPHLKQK 700
701 DKLPDDHYQEKTAMDLAAEQLRLWPTLSKSTQQELVQHEESTVFSQAIHF 750
751 ANLMVNLLVPLDTSKNKLLRTSAPGDWESGSNSIVTNSIAGSVAESYDTE 800
801 SGFEDSENTDIANSVVRFITRFIDKVCTESGVTQDHIKSLHCMIPGIVAM 850
851 HIETLEAVHRESRRLPPIQKPKILRPALLPGEEIVCEGLRVLLDPDGREE 900
901 ATGGLLGGPQLLPAEGALFLTTYRILFRGTPHDQLVGEQTVVRSFPIASI 950
951 TKEKKITMQNQLQQNMQEGLQITSASFQLIKVAFDEEVSPEVVEIFKKQL 1000
1001 MKFRYPQSIFSTFAFAAGQTTPQIILPKQKEKNTSFRTFSKTIVKGAKRA 1050
1051 GKMTIGRQYLLKKKTGTIVEERVNRPGWNEDDDVSVSDESELPTSTTLKA 1100
1101 SEKSTMEQLVEKACFRDYQRLGLGTISGSSSRSRPEYFRITASNRMYSLC 1150
1151 RSYPGLLVVPQAVQDSSLPRVARCYRHNRLPVVCWKNSRSGTLLLRSGGF 1200
1201 HGKGVVGLFKSQNSPQAAPTSSLESSSSIEQEKYLQALLNAVSVHQKLRG 1250
1251 NSTLTVRPAFALSPGVWASLRSSTRLISSPTSFIDVGARLAGKDHSASFS 1300
1301 NSSYLQNQLLKRQAALYIFGEKSQLRNFKVEFALNCEFVPVEFHEIRQVK 1350
1351 ASFKKLMRACIPSTIPTDSEVTFLKALGDSEWFPQLHRIMQLAVVVSEVL 1400
1401 ENGSSVLVCLEEGWDITAQVTSLVQLLSDPFYRTLEGFQMLVEKEWLSFG 1450
1451 HKFSQRSSLTLNCQGSGFAPVFLQFLDCVHQVHNQYPTEFEFNLYYLKFL 1500
1501 AFHYVSNRFKTFLLDSDYERLEHGTLFDDKGEKHAKKGVCIWECIDRMHK 1550
1551 RSPIFFNYLYSPLEIEALKPNVNVSSLKKWDYYIEETLSTGPSYDWMMLT 1600
1601 PKHFPSEDSDLAGEAGPRSQRRTVWPCYDDVSCTQPDALTSLFSEIEKLE 1650
1651 HKLNQAPEKWQQLWERVTVDLKEEPRTDRSQRHLSRSPGIVSTNLPSYQK 1700
1701 RSLLHLPDSSMGEEQNSSISPSNGVERRAATLYSQYTSKNDENRSFEGTL 1750
1751 YKRGALLKGWKPRWFVLDVTKHQLRYYDSGEDTSCKGHIDLAEVEMVIPA 1800
1801 GPSMGAPKHTSDKAFFDLKTSKRVYNFCAQDGQSAQQWMDKIQSCISDA 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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