 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9QY81 from www.uniprot.org...
The NucPred score for your sequence is 0.16 (see score help below)
1 MARASLVQPALWALLLLQVVGPAAAAKLNIPKVLLPFTRATRVNFTLEAS 50
51 EGCYRWSSTRPEVASIEPLGSSEQQCSQKAVVQARLTQPARLTSIIFAED 100
101 ITTGQVLRCDAIVDLIHGIQIVSTTRELYLEDSPLELKIQALDSEGNTFS 150
151 TLAGLVFDWTIVKDTEANGFSDSHNALRILTFLESTYIPPSYISEMEKAA 200
201 KQGDTILVSGMKTGSSKLKARIQEAVYKNVRPAEVRLLILENILLNPAYD 250
251 VYLLVGTSIHYKVQKIRQGKITELSMPSDQYELQLQNSIPDPQGDPARPV 300
301 AILTQDTSRVTAMQMGQSNLVLGHRSIRMQGASRLPNSTIYVVEAGYLGF 350
351 TVYPGDRWVLETGHLYAITIEVFDRSSNKVYPSDNIRIEAVLPAEFFEVL 400
401 SSSQNGSYHHIRAIQSGQTAISATLTSVVDQDGGVHVLQVPVWNQQEVDI 450
451 HIPITLYPSILTFPWQPKTGAYQYTIKAHGGSGNFSWSSSSSMVATVTVK 500
501 GVMTTSGDTGLSVIRAHDVQNPLHFGEMKVYVIEPSSMEFAPCQVEARVG 550
551 HTLELPLTISGFMPGGGSEVVTLSDCSHFDLVVEVENQGVFQPLPGRLPP 600
601 GPEHCSGVKVKADAQGSTTLLVSYTHGHVHLDAKITLAAYLPLKAVDPSS 650
651 VAVVTLGSSKEMLFEGGPRPWVLEPSKFFRNVTSEDTGSISLSLLGPPAS 700
701 RNYQQHRVLMTCQALGEQVIALSVGNRPSLSNPFPAVEPTVVKSICAPPS 750
751 RLTLMPVYALPQLDLSCPLLQQNKQVVPVSSHRNPLLDLGAYDQQGRRFD 800
801 NFSSLSIQWESSRPLLASIELDQPMQLVSQDDGNGQKKLHGLQTVSVHEA 850
851 SGTTAISATATGYQQSHLSEARVKQPHDPLVPVSASIELILVEDVRVSPE 900
901 EMTIYNHPGVQVELYITEGSGYFFLNTSTQDIIKVAYQDTRGVALVHPLL 950
951 PGSSTVMVHDLCLAFPAPAKAIIHVSDIQELYVRVVDKVEIGKAVKAYVR 1000
1001 VLDFYKKPFLAKYFTFMDLKLQAASQIITLVTLDEALDNYTATFLVHGVA 1050
1051 IGQTSLSASVTDKSGQRVSSTPQQIEVFPPFRLIPRKVTLIIGAMMQITS 1100
1101 EGGPQPQSNILFSINNESVAAVSSSGLVRGLMVGNGSVLGVVQAVDAETG 1150
1151 KVIIVSQDLVEVEVLQLQAVRIRAPITRMRTGTQMPVFVTGITSNQSPFS 1200
1201 FGNAVPGLTFHWSVTKRDVLDLRGRHHEVSIRLPPQYNFAMNVYGRVKGR 1250
1251 TGLRVVVKALDPTAGQLHGLGKELSDEIQIQVFEKLRLLNPEIEAEQILM 1300
1301 SPNSFIKLQTNRDGAAILSYRVLDGPEKAPIVHTDEKGFLVSGSGIGVST 1350
1351 LEVIAQEPFGTNQTILVAVKVSPVSYLRISMSPVLHTQHKEALTALPLGM 1400
1401 TVTFIVHFHDSSGDIFHAHNSVLNFATNRDDFVQIGKGATNNTCIIRTVS 1450
1451 VGLTLLHVWDVEHLGLSDFVPLPVLQAITPELSGAVVVGDILCLASVLTS 1500
1501 LGGVSGTWSSSASHVLYVDPKTGVAIARDAGSVTVYYEIAGQLKTFKEIV 1550
1551 VGTPQKIVARRLHSAQTSIQEATASKVTVSVGDRSSNLLGECSPAQREAI 1600
1601 EALHPESLISCQLQFKQDVFDFPACDVFTVEPGFDAALGQYLCSVTMRRL 1650
1651 TDKQLKHLNMKKTSLAVTASIPSSYTSVEKVGAEVPFSPGLYANQAEILL 1700
1701 SNHYTSSEVKVFGAVESLENLEVKSGSPAVLAFVKEKSFGLPSFITYTVG 1750
1751 VLDPTAGSQGPLSTALTFSSPATNQAITIPVTVAFVLDRRGPGPYGASLL 1800
1801 SHFLDSYQVMFFTFFALLAGTAVTIIAYHTVCAPRELASPLALTPRASPQ 1850
1851 HSPHYLASSPAAFNTLPSGRKASPPSGLWSPAYASH 1886
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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