 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q62141 from www.uniprot.org...
The NucPred score for your sequence is 0.85 (see score help below)
1 MAHAGSGGSAGRGFGGSRWGRSGSGGHEKLPVHVEDALTYLDQVKIRFGS 50
51 DPATYNGFLEIMKEFKSQSIDTPGVIRRVSQLFHEHPDLIVGFNAFLPLG 100
101 YRIDIPKNGKLNIQSPLSSQDNSHSHGDCGEDFKQMSYKEDRGQVPLESD 150
151 SVEFNNAISYVNKIKTRFLDHPEIYRSFLEILHTYQKEQLHTKGRPFRGM 200
201 SEEEVFTEVANLFRGQEDLLSEFGQFLPEAKRSLFTGNGSCEMNSGQKNE 250
251 EKSLEHNKKRSRPSLLRPVSAPAKKKMKLRGTKDLSIAAVGKYGTLQEFS 300
301 FFDKVRRVLKSQEVYENFLRCIALFNQELVSGSELLQLVSPFLGKFPELF 350
351 AQFKSFLGVKELSFAPPMSDRSGDGISREIDYASCKRIGSSYRALPKTYQ 400
401 QPKCSGRTAICKEVLNDTWVSFPSWSEDSTFVSSKKTPYEEQLHRCEDER 450
451 FELDVVLETNLATIRVLESVQKKLSRMAPEDQEKLRLDDCLGGTSEVIQR 500
501 RAIHRIYGDKAPEVIESLKRNPATAVPVVLKRLKAKEEEWREAQQGFNKI 550
551 WREQYEKAYLKSLDHQAVNFKQNDTKALRSKSLLNEIESVYDEHQEQHSE 600
601 GRSAPSSEPHLIFVYEDRQILEDAAALISYYVKRQPAIQKEDQGTIRQLL 650
651 HRFLPSLFFSQQCPGTSDDSADERDRDRDSAEPERRRPTDEKPPADASPE 700
701 PPKVLDDVYSLFFANNNWYFFLRLHQTLCARLLKIYRQAQKQLLEHRREQ 750
751 EREQLLCEGRREKAADPAMELRLKQPSEVELEEYYPAFLDMVRSLLEGSI 800
801 DPTQYEDTLREMFTIHAYIGFTMDKLVQNIARQLHHLVSDDVCLKVVELY 850
851 LNEQQRGAAGGNLSSRCVRAARETSYQWKAERCMADENCFKVMFLQRRGQ 900
901 VIMTIELLDTEEAQTEDPVEVQHLARYVEQYVGSEGASSSSTEGFLLKPV 950
951 FLQRNLKKFRRWQCEQVRAMRGEAKSSWKRLMGVESACDVDCRFRLGTHK 1000
1001 MVFIVNSEDYMYRRGTLCRAKQVQPLVLLRHHRHFEEWHGRWLEDNVTVA 1050
1051 AAGLVQDWLMGEEEEDMVPCKTLCETAHVHGLPVTRYRVQYSRRPASP 1098
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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