 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O97831 from www.uniprot.org...
The NucPred score for your sequence is 0.21 (see score help below)
1 MARLAAVLWSLCVTAILVTSATQGLSRAGLPFGLMRRELACEGYPIELRC 50
51 PGSDVIMVENANYGRTDDKICDADPFQMENVQCYLPDAFKIMSQRCNNRT 100
101 QCVVVAGSDAFPDPCPGTYKYLEVQYDCVPYKVKQKVFVCPGTLQKVLEP 150
151 TSTHESEHQSGAWCKDPLQAGDRIYVMPWIPYRTDTLTEYASWEDYVAAR 200
201 HTTTYRLPNRVDGTGFVVYDGAVFYNKERTRNIVKYDLRTRIKSGETVIN 250
251 TANYHDTSPYRWGGKTDIDLAVDENGLWVIYATEGNNGRLVVSQLNPYTL 300
301 RFEGTWETGYDKRSASNAFMVCGVLYVLRSVYVDDDSEAAGNRVDYAFNT 350
351 NANREEPVSLAFPNPYQFVSSVDYNPRDNQLYVWNNYFVVRYSLEFGPPD 400
401 PSAGPATSPPLSTTTTARPTPLTSTASPAATTPLRRAPLTTHPVGAINQL 450
451 GPDLPPATAPAPSTRRPPAPNLHVSPELFCEPREVRRVQWPATQQGMLVE 500
501 RPCPKGTRGIASFQCLPALGLWNPRGPDLSNCTSPWVNQVAQKIKSGENA 550
551 ANIASELARHTRGSIYAGDVSSSVKLMEQLLDILDAQLQALRPIERESAG 600
601 KNYNKMHKRERTCKDYIKAVVETVDNLLRPEALESWKDMNATEQAHTATM 650
651 LLDVLEEGAFLLADNVREPARFLAAKQNVVLEVTVLNTEGQVQELVFPQE 700
701 YPSENSIQLSANTIKQNSRNGVVKVVFILYNNLGLFLSTENATVKLAGEA 750
751 GSGGPGGASLVVNSQVIAASINKESSRVFLMDPVIFTVAHLEAKNHFNAN 800
801 CSFWNYSERSMLGYWSTQGCRLVESNKTHTTCACSHLTNFAVLMAHREIY 850
851 QGRINELLLSVITWVGIVISLVCLAICISTFCFLRGLQTDRNTIHKNLCI 900
901 NLFLAELLFLVGIDKTQYEIACPIFAGLLHYFFLAAFSWLCLEGVHLYLL 950
951 LVEVFESEYSRTKYYYLGGYCFPALVVGIAAAIDYRSYGTEKACWLRVDN 1000
1001 YFIWSFIGPVSFVIVVNLVFLMVTLHKMVRSSSVLKPDSSRLDNIKSWAL 1050
1051 GAIALLFLLGLTWAFGLLFINKESVVMAYLFTTFNAFQGVFIFVFHCALQ 1100
1101 KKVHKEYSKCLRHSYCCIRSPPGGAHGSLKTSAMRSNARYYTGTQSRIRR 1150
1151 MWNDTVRKQTESSFMAGDINSTPTLNRGTMGNHLLTNPVLQPRGGTSPYN 1200
1201 TLIAESVGFNPSSPPVFNSPGSYREPKHPLGGREACGMDTLPLNGNFNNS 1250
1251 YSLRSGDFPPGDGAPEPPRGRNLADAAAFEKMIISELVHNNLRGGSSGAK 1300
1301 GPPPPEPPVPPVPGGSGEEEAGGPGADRAEIELLYKALEEPLLLPRAQSV 1350
1351 LYQSDLDESESCTAEDGATSRPLSSPPGRDSLYASGANLRDSPSYPDSSP 1400
1401 EGPSEALPPPPPAPPGPPEIYYTSRPPALVARNPLQGYYQVRRPSHEGYL 1450
1451 AAPGLEGPGPDGDGQMQLVTSL 1472
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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