 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6NTN5 from www.uniprot.org...
The NucPred score for your sequence is 0.87 (see score help below)
1 MARLADYFIVVGYDHEKTGSEGFGKIIQRFPMTDWSDTPFPQGIELFCQP 50
51 GGWQLSRERKQPTFFIVVLTDIDSDRHYCACLTFYEAEINLQGTKREHSE 100
101 TEEEDSGLIQPAQVFAPKSLVLVSRLDYPEIFRACLGLIYTVYIDSLNVS 150
151 LENLVSNLVTCIVPCAGGSQKLFSLGAGDRQLIQTPLHDSLPVTGTSVAL 200
201 LFQQLGIQNVLSLFCAVLTENKVLFHSSSFQRLGDACRALEALIYPLKYS 250
251 YPYIPILPAQLLEVLSSPTPFIIGVHSVFCSEIHDLLDVIIADLDGGTIK 300
301 IPECIHLSPIPEPLLHQTQAALSLVLHPDLEVADNAFAPLRTPVPHIKLL 350
351 DKEVRAVFLRLFAQIFQGYRSCLQLIRIHAEPIIHFHKAAFLGQRGLIEN 400
401 DFLTKVLSGMSFAGFVSERGPPYRPCDLFDELVSFEVERIKDDDQNDTHK 450
451 ILKHIRELAEQLFKNENPNPHMAFQKVPKPTEGSHLRVHILPFSKMNDLK 500
501 VQELIQEGLNKNQNSILSPRAEKKCVVPAGSPVVSIVDKASSVFNSARRL 550
551 EVVRNCIMYIFENKTLETEKTLPAALRALKGKAARQCLTEELALHVQQNR 600
601 SMLNHQQFDYIVRMMNCALQDCSGSEEYTIASQLLPLATAFCRKLSAAVS 650
651 QFAYTCVQDHGVWANQQFWETTFYNDVQNQVRSLYLTTKNGNQGASEPKE 700
701 NGVDSGNPERTVMDLAAEQLRLWPTLSKETQQELIQSEESTVFSQAIHFA 750
751 NLMVYLLVPLDTSKNKLLRTSATGDWESGSNSIVTNSIAGSVAESYDTES 800
801 GFEDSENDIANSVVRFITRFIDKVCTESGVTQDHIKSLHCMIPGIVAMHI 850
851 ETLEAVHRESRRLPPIKKPKIMRPALLPGEEFVCEALRVLLDPDGREEAT 900
901 GGMLGGPHILPAEGALFLTTYRIIFKGTPHDALVGEQTVIRSVPIASITR 950
951 EKKINVQNQLHQNMQEGLQIRSATFQLIKVAFDEEVSAEMVDLFKKQLMK 1000
1001 FRYPLSIFSAFAFAAGQTAPPIILPKQKEKNTSFRTISKTIVKGAKRAGK 1050
1051 MTIGRQYAAKKKTGTILEERGSRSGGNEDDDISVSDDNELPSGTLKPSEK 1100
1101 STMEQLVERACFRDYQRLALGTISNSSTRFKSEHFRVTALNRMHSLCRSY 1150
1151 PGLLVVPQSVQDSSLQKVARCYRHNRLPVVSWKNAKTNAVLLRGGGFHGK 1200
1201 TVVGLFKSQNTHTAAPASSLESSSSIEQEKYLQALLNAISVHYKMNGNST 1250
1251 LTVRPTLALSPGSDRKSSRMSSVVKHVVPSHVDGSLSHSFARGGVWASLR 1300
1301 SSNRLITTQTPLIDVGARLVGKDLQTTYTDHSALQSQLLKRQAALYIFGE 1350
1351 KSQLRGFKFDFALNCEFVPVEFGDIRQVKTSFKKLMRACVPSSNPTDSES 1400
1401 TFLKAMGESEWFLQIHRIIQLSVIISELMESGSSVMICLEDGWDITTQVV 1450
1451 SLVQILGDPFYRTLEGFRMLIEKEWLSFGHKFSQRSNLSPSSQGTGFVPI 1500
1501 FLQFLDCVHQIHNQYPTEFEFNRYYLKFLAYHHVSNRFKTFLLDSDYERL 1550
1551 EHGTLFEDKGDKHSRRGICIWEYIERIHKKKTVFFNYLFAPTELEALKPS 1600
1601 ANISTLRKWEYYMEETLASGPSYDWIITPSRFNASDETDSGEEAQQQGKR 1650
1651 KIVWPCYDDVQKVQPDAITHLMNEIERLEIKLNQTSERWQLLWERAKVKL 1700
1701 KENAKKENNNPASLVSANLQSYQKRSMVHLPDSGLGDEQNLNASPSNGVD 1750
1751 RRTATLYNHFTSKNEENRSYEGILYKRGALLKGWKPRWFVLDITKHQLRY 1800
1801 YDSGEDTSCKGYIDLADVETVVPAAPTIGAPKHANEKAFFDVKTSKRVYN 1850
1851 FCAQDAQSAQLWMDKIQNCISDA 1873
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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