 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P11654 from www.uniprot.org...
The NucPred score for your sequence is 0.15 (see score help below)
1 MARASLIQPGLWALLLLQAVGPAVAAKLNIPKVLLPFTRATRVNFTLEAS 50
51 EGCYRWSSTRPEVASIEPLGSSEQQCSQKAVVQARLTQPARLTSIIFAED 100
101 ITTGQVLRCDAIVDLIHGIQIVSTTRELYLEDSPLELKIQALDSEGNTFS 150
151 TLAGLVFDWTIVKDTEANGFSDSHNALRILTFLESTYIPPSYISEMEKAA 200
201 KQGDTILVSGMKTGSSKLKARIQEAVYKNVRPAEVRLLILENILLNPAYD 250
251 VYLLVGTSIHYKVQKIRQGKITELSMPSDQYELQLQNSIPDPQGDPARPV 300
301 AVLTQDTSRVTAMQMGQSNLVLGHRSIRMQGASRLPNSTIYVVEAGYLGF 350
351 TVHPGDRWVLETGHLYAVTIEVFDRSSNKVYPSDNIRIEAVFPAEFFEVL 400
401 SSSQNGSYHHVRAIQSGQTTISASLTSVVDQDGGVHVLQVPVWNQQEVDI 450
451 HIPITLYPSILTFPWQPKTGAYQYTIKAHGGSGNFTWSSSSYMVATVTVK 500
501 GVMTTGGDTGLSVIRAHDVQNPLHFGEMKVYVIEPSSMEFAPCQVEARVG 550
551 HTLELPLTISGLMPGGSSEVVTLSDCSHFDLVVEVENQGVFQPLPGRLPP 600
601 GPEHCSGVKVRADAQGSTTLLVSYTHGHVHLGAKITLAAYLPLKAVDPSS 650
651 VAVVTLGSSKEMLFEGGPRPWVLEPSKFFRNVTSEDTGSISLSLLGPPAS 700
701 RNYQQHRVLVTCQALGEQVIALSVGNRPSLSNPFPAVEPTVVKSVCAPPS 750
751 RLTLMPVYALPQLDLSCPLLQQNKQVVPVSSHRNPLLDLGAYDQQGRRFD 800
801 NFSSLSIQWESFRPLLASIEVDQPMQLVSQDDGNGQKKLHGLQTVSVHEA 850
851 SGTTAISATATGYQQSHLSAAGVKQLRDPLVPVSASIELILVEDVRVSPE 900
901 EVTIYNHPGVQVELHITEGSGYFFLNTSTQDIINVAYQDTRGVAMVHPLF 950
951 PGSSTVMVHDLCLTFPAPAKATIHVSDIQELYVRVVDKVEIGKAVKAYVR 1000
1001 VLDFYKKPFLAKYFTFMDLKLRAASQIITLVTLDEALDNYTATFLVHGVA 1050
1051 IGQTSLSASVTDKSGQRVSSTAQQIEVFPPFRLIPRKVTLIIGAMIQITS 1100
1101 EGGPQPQSNILFSINNESVAAVSSAGLVRGLMVGNGSVLGVVQAVDAETG 1150
1151 KVIIVSQDHVEVEVLQLQAVRIRAPITRMRTGTQMPVYVTGITSNQSPFS 1200
1201 FGNAVPGLTFHWSVTKRDVLDLRGRHHEVSIRLSPQYNFAMNVHGRVKGR 1250
1251 TGLRVVVKALDPTAGQLHGLGKELSDEIQIQVFEKLRLLNPEVEAEQILM 1300
1301 SPNSFIKLQTNRDGAAILSYRVLDGPEKAPIVHIDEKGFLVSGSGIGVST 1350
1351 LEVIAQEPFGTNQTVLVAVKVSPISYLRISMSPVLHTQHKEVLTALPLGM 1400
1401 TVTFTVHFHDSSGDIFHAHNSDLNFATNRDDFVQIGKGATNNTCIIRTVS 1450
1451 VGLTLLHVWDVEHLGLSDFVPLPVLQAITPELSGAVVVGDILCLASVLIS 1500
1501 LGGVSGTWSSSAGNVLYVDPKTGVAIARDAGPVTVYYEIAGHLKTFKEIV 1550
1551 VVTPQKIVARRLHATQTSIQEATASKVTVSVGDRSSNLLGECSSAQREAI 1600
1601 EALHPESLISCQLQFKQDVFDFPARDIFSVEPGFDTALGQYLCSVTMHRL 1650
1651 TDKQLKHLNMKKTSLAVTASMPSSRTSVEKVGAEVPFSPGLYANQAEILL 1700
1701 SNHYPSSEVKIFGAVEILENLEVRSGSPAVLASVKEKSFGLPSFITYTVG 1750
1751 VLDPTAGSQGPLSTALTFSSPATNQAITIPVTVAFVLDRRGPGPYGASLL 1800
1801 SHFLDSYQVMFFTFFALLAGTAVTIIAYHTVCAPRELASPLALTPHASPQ 1850
1851 HSPHYLASSPTAFNTLPSDRKASPPSGLWSPAYASH 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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