 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P41885 from www.uniprot.org...
The NucPred score for your sequence is 0.94 (see score help below)
1 MTKSTKLRHCKQKKKKPEKTPKGNPPILITEKSIEDAATTTSTTDALLGS 50
51 PEGSRSKSRKLKLCCCTAQAATLSPLDPTSYGGIASTSAHNGMVGGLSRD 100
101 SRAASRTSKRGSSKSLNRPQIDADEPSTSGTNPDRRPSTHFVLDLPVVST 150
151 RLRKLSEAFFNAQHGDKIDLMNDWEIGGTQNKWVCPSDRHLHLRAQLKSG 200
201 WSVRTATARSPTNSKAQTGSITAAEQEHIQKVLAKAEESKSKEQQRIGKM 250
251 VDRLEKMRRRATGNGVTHCLLCHTEFGLLASKSYAAMCVDCRKYVCQRNC 300
301 GVETTDVNQTTGKVETVFLCKICSEAREVLWKKSGAWFYKEMPEFQRPDD 350
351 RLPYYVPVTTNGTLPNASSAATPLSGTPGGAGPQPMTMPSTSSCQMTTPK 400
401 WASPGVCNSPGLQMNGGPTSPLPNGTRRNTGHGGIEFPSSSRPSICSVLQ 450
451 AIEPLDRSKSPRPRIQPRWVNEKVMSSMSVDDEEKAASSSDGESFVQSGV 500
501 PRRALNNKTPVGSTSATTSPAPPPTSTTPTSRREANMERFSRHTHAHANR 550
551 LYSTDDDDDSSPESRPSTRSTSPRHSLATPSSYAHDTCHDTSLPDADTRS 600
601 IDSGVVQSDHSNPQQSGLTCSSSSLTPLQQQASHDHHSGGGTPRRISNPD 650
651 RTTSRVAQSASGTSLVTPPPPISSRTSPDNCNSSPLNVMEHKSSSASTAS 700
701 SGGNRRVGSAEPVLNNHHAMHNNQNHNDINKKLISQTSRAESPLAASSSF 750
751 LSSPDDDTKQKNRRRDGVGRVNSLQLRTSLDDVAPPVAPISKMNGHIVSS 800
801 EPTSSTTSNQNHTSVPIPTVPVVPEEEEEKAITASTESASEPGSLGSITL 850
851 TLTYHSADKKLKMHLIRAKNLKAMDSNGFSDPYVKFHLLPGNTKATKLTS 900
901 KTIEKTLNPEWNEEMSYYGITEDDKEKKILRVTVLDRDRIGSDFLGETRI 950
951 ALKKLNDNEMKKFNLYLESALPVPQQTKEEENEDRGKINVGLQYNIQQGS 1000
1001 LFININRCVELVGMDSTGFSDPYCKVSLTPITSKAHRAKTSTKKRTLNPE 1050
1051 WNEQLQFVVPFKDLPKKTLQIGVYDHDLGKHDDYIGGILLSTSAKDERGR 1100
1101 QWIKCIENPGTLVEAWHRLELDS 1123
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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