 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q90688 from www.uniprot.org...
The NucPred score for your sequence is 0.38 (see score help below)
1 MPEPAKKAVSAFTKKPKTTEVAAGSTAVFEAETEKTGIKVKWQRAGTEIT 50
51 DSEKYAIKAEGNKHSLTISNVGKDDEVTYAVIAGTSKVKFELKVKEPEKS 100
101 EPVAPAEASPAPAASELPAPPVESNQNPEVPPAETQPEEPVDPIGLFVTR 150
151 PQDGEVTVGGNITFTAKVAGESLLKKPSVKWFKGKWMDLASKVGKHLQLH 200
201 DNYDRNNKVYTFEMEIIEANMTFAGGYRCEVSTKDKFDSSNFNLIVNEAP 250
251 VSGEMDIRAAFRRTSLAGGGRRMTSAFLSTEGLEESGELNFSALLKKRDS 300
301 FLRTANRGDGKSDSQPDVDVWEILRKAPPSEYEKIAFQYGITDLRGMLKR 350
351 LKRIKKEEKKSTAFLKKLDPAYQVDKGQKIKLMVEVANPDADVKWLKNGQ 400
401 EIQVSGSKYIFEAIGNKRILTINHCSLADDAAYECVVAEEKSFTELFVKE 450
451 PPILITHPLEDQMVMVGERVEFECEVSEEGATVKWEKDGVELTREETFKY 500
501 RFKKDGKKQYLIINESTKEDSGHYTVKTNGGVSVAELIVQEKKLEVYQSI 550
551 ADLTVKARDQAVFKCEVSDENVKGIWLKNGKEVVPDERIKISHIGRIHKL 600
601 TIEDVTPGDEADYSFIPQGFAYNLSAKLQFLEVKIDFVPREEPPKIHLDC 650
651 LGQSPDTIVVVAGNKLRLDVPISGDPTPTVIWQKVNKKGELVHQSNEDSL 700
701 TPSENSSDLSTDSKLLFESEGRVRVEKHEDHCVFIIEGAEKEDEGVYRVI 750
751 VKNPVGEDKADITVKVIDVPDPPEAPKISNIGEDYCTVQWQPPTYDGGQP 800
801 VLGYILERKKKKSYRWMRLNFDLLKELTYEAKRMIEGVVYEMRIYAVNSI 850
851 GMSRPSPASQPFMPIAPPSEPTHFTVEDVSDTTVALKWRPPERIGAGGLD 900
901 GYIVEYCKDGSAEWTPALPGLTERTSALIKDLVTGDKLYFRVKAINLAGE 950
951 SGAAIIKEPVTVQEIMQRPKICVPRHLRQTLVKKVGETINIMIPFQGKPR 1000
1001 PKISWMKDGQTLDSKDVGIRNSSTDTILFIRKAELHHSGAYEVTLQIENM 1050
1051 TDTVAITIQIIDKPGPPQNIKLADVWGFNVALEWTPPQDDGNAQILGYTV 1100
1101 QKADKKTMEWYTVYDHYRRTNCVVSDLIMGNEYFFRVFSENLCGLSETAA 1150
1151 TTKNPAYIQKTGTTYKPPSYKEHDFSEPPKFTHPLVNRSVIAGYNTTLSC 1200
1201 AVRGIPKPKIFWYKNKVDLSGDAKYRMFSKQGVLTLEIRKPTPLDGGFYT 1250
1251 CKAVNERGEAEIECRLDVRVPQ 1272
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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