 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
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The NucPred score for your sequence is 1.00 (see score help below)
1 MSAGGRDEERRKLADIIHHWNANRLDLFEISQPTEDLEFHGVMRFYFQDK 50
51 AAGNFATKCIRVSSTATTQDVIETLAEKFRPDMRMLSSPKYSLYEVHVSG 100
101 ERRLDIDEKPLVVQLNWNKDDREGRFVLKNENDAIPAKKAQSNGPEKQEK 150
151 EGVIQNFKRTLSKKEKKEKKKKEKEALRQASDKEERPSQGDDSENSRLAA 200
201 EVYKDMPETSFTRTISNPEVVMKRRRQQKLEKRMQEFRSSDGRPDSGGTL 250
251 RIYADSLKPNIPYKTILLSTTDTADFAVAESLEKYGLEKENPKDYCIARV 300
301 MLPPGAQHSDERGAKEIILDDDECPLQIFREWPSDKGILVFQLKRRPPDY 350
351 IPKKMKKHVEGKSLKGKDRADGSGYGSALPPEKLPYLVELSPGRRNHFAY 400
401 YSYHTYEDGSDSRDKPKLYRLQLSVTEVGTEKFDDNSIQLFGPGIQPHHC 450
451 DLTNMDGVVTVTPRSMDAETYVDGQRISETTMLQSGMRLQFGTSHVFKFV 500
501 DPIQDHVLSKRSVDGGLMVKGPRHKPGAVQETTFELGGDVHSGTALPASR 550
551 STTRLDSDRVSSASSTAERGMVKPMIRLDQEQEYRRRENRTQDATGPELI 600
601 LPASIEFRESSEDSFLSAIINYTNSSTVHFKLSPTYVLYMACRYVLSSQH 650
651 RPDISPTERTHKAIAVVNKMVSMMEGVIQKQKNIAGALAFWMANASELLN 700
701 FIKQDRDLSRITLDAQDVLAHLVQMAFKYLVHCLQSELNNYMPAFLDDPE 750
751 ENSLQRPKIDDVLHTLTGAMSLLRRCRVNAALTIQLFSQLFHFINMWLFN 800
801 RLVTDPDSGLCSHYWGAIIRQQLGHIEAWAEKQGLELAADCHLSRIVQAT 850
851 TLLTMDKYVPDDIPNINSTCFKLNSLQLQALLQNYHCAPDEPFIPTDLIE 900
901 NVVAVAENTADELARSDGRDVQLEEDPDLQLPFLLPEDGYSCDVVRNIPN 950
951 GLQEFLDPLCQRGFCRLVPHTRSPGTWTIYFEGADYESHLMRENAELAQP 1000
1001 LRKEPEIITVTLKKQNGMGLSIVAAKGAGQDKLGIYVKSVVKGGAADVDG 1050
1051 RLAAGDQLLSVDGRSLVGLSQERAAELMTRTSSVVTLEVAKQGAIYHGLA 1100
1101 TLLNQPSPMMQRISDRRGSGKPRPKSEGFELYNNSAQNGSPESPQMPWTE 1150
1151 YSEPKKLPGDDRLMKNRADHRSSPNVANQPPSPGGKGPYTSGTAAKITSV 1200
1201 STGNLCTEEQSPPPRPEAYPIPTQTYTREYFTFPASKSQDRMAPPQSQWP 1250
1251 NYEEKPHVHTESNHSSIAIQRVTRSQEELREEKVYQLERHRVEAGMDRKC 1300
1301 DSDMWINQSSSVESSTSSQEHLNHSSKSVTPASTLTKSGPGRWKTPAAVL 1350
1351 PTPVAVSQPIRTDLPPPPPPPPVHYTSEFDGIPMDLPLPPPPANQAGPQS 1400
1401 AQVAAAEWKKREEHQRWYEKEKARLEEERERKRREQERKLGQMRSQTLNP 1450
1451 ASFSPLATQAKPEKPSTLQRPQETVIRELQPQQQPRTIERKDLQYITISK 1500
1501 EELSSGDSLSPDPWKRDAREKLEKQQQMHIVDMLSKEIHELQNKVDRTAE 1550
1551 ESDRLRKLMLEWQFQKRLQESKQKDEDDDEEEDDDVDTMLIMQRLEAERR 1600
1601 ARMQDEERRRQQQLEEMRKREAEDRVRQEEDGRHQEEERVKRDAEEKRRQ 1650
1651 EEGYYSRLEAERRRQHEEAARRLLEPEEPGLSRPPLPRDYEPPSLSSAPC 1700
1701 APPPPPQRNASYLKTQVLSPDSLFTAKFVAYDEEEEDYGPAGPNSYSGSA 1750
1751 GTAVGAYDAPREAREKLTRSQDADLPGSSGAPENLTFKERQRLFSQGQDV 1800
1801 SDKVKASRKLTELENELNTK 1820
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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