 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q23356 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MSSSGLDEIDLNSLRDPAGIFELIEVVGNGTYGQVYKGRHVKTAQLAAIK 50
51 IMNINEDEEDEIKLEINMLKKHSHHRNVATYYGAFIKKLPSSTGKHDQLW 100
101 LVMEFCGSGSITDLVKNTKGGSLKEEWIAYICREILRGLYHLHQSKVIHR 150
151 DIKGQNVLLTDSAEVKLVDFGVSAQLDKTVGRRNTFIGTPYWMAPEVIAC 200
201 DESPEATYDSRSDLWSLGITALEMAEGHPPLCDMHPMRALFLIPRNPPPK 250
251 LKRNKKWTKKFETFIETVLVKDYHQRPYTGALLRHPFIKEQPHEQTIRHS 300
301 IKEHIDRNRRVKKDDADYEYSGSEDDEPSPNNRGPSMGIRDDSESSSMIP 350
351 MDNTLRKGFQKLQESSRGFAEPGAQQLRRLPQQPAPAPFQYQQSRYVEPR 400
401 RESSEVKLRAVSSRGAADGPRHSPASRPRPVSHHQRSPQQSHPAAPHLAD 450
451 LANYEKRRRSEREERRERERQAHHAMPIARVSASVPAPQQSRKMSEPLLI 500
501 THVKPEDLDVLASELSKMGGHHNGRSREESMSPPPPAPPPREASISSITD 550
551 TIDVGELDNGADAEWDDLKDIMMNGEGTLRGPNKPLPPTPTDGENTLVSD 600
601 VRRNGNGNSGHGAYKGKKIPEIRPGIISLDDDDSDSDNEEGNEPLMFKPI 650
651 NASSSRGALPDLLPKSPQLRRQINDQTRQMSDDRADESASLFGSFYQPNG 700
701 FQNSDSRSSIQHSFSNRDREKSFVGYFGGGAGAGGGTVNRPGRPQDINQV 750
751 QVNVTPNSNGTPAENDAPEIRKYKKKFSGEILCAALWGVNLLIGTDSGLM 800
801 LLDRSGQGKVYPLISRRRFDQMTVLEGQNILATISGRKRRIRVYYLSWLR 850
851 QKILRTEGAGSANTTEKRNGWVNVGDLQGAIHFKIVRYERIKFLVVGLES 900
901 SIEIYAWAPKPYHKFMSFKSFGSLSHVPLIVDLTVEDNARLKVLYGSTGG 950
951 FHAIDLDSAAVYDIYTPAQSGQTTTPHCIVVLPNSNGMQLLLCYDNEGVY 1000
1001 VNTYGRMTKNVVLQWGEMPSSVAYISTGQIMGWGNKAIEIRSVDTGHLDG 1050
1051 VFMHKKAQKLKFLCERNDKVFFSSAKGGGSCQIYFMTLNKPGLTNW 1096
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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