| Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P31380 from www.uniprot.org...
The NucPred score for your sequence is 1.00 (see score help below)
1 MSGSHSNDEDDVVQVPETSSPTKVASSSPLKPTSPTVPDASVASLRSRFT 50
51 FKPSDPSEGAHTSKPLPSGSPEVALVNLAREFPDFSQTLVQAVFKSNSFN 100
101 LQSARERLTRLRQQRQNWTWNKNASPKKSETPPPVKKSLPLANTGRLSSI 150
151 HGNINNKSSKITVAKQKTSIFDRYSNVINQKQYTFELPTNLNIDSEALSK 200
201 LPVNYNKKRRLVRADQHPIGKSYESSATQLGSAREKLLANRKYGRHANDN 250
251 DEEEEESMMTDDDDASGDDYTESTPQINLDEQVLQFINDSDIVDLSDLSD 300
301 TTMHKAQLIASHRPYSSLNAFVNTNFNDKDTEENASNKRKRRAAASANES 350
351 ERLLDKITQSIRGYNAIESVIKKCSSYGDLVTSQMKKWGVQVEGDNSELD 400
401 LMNLGEDDDDDNDDGNNDNNNSNNNNTAGADATSKEKEDTKAVVEGFDET 450
451 SAEPTPAPAPAPVERETKRIRNTTKPKVVEDEDDDVDLEAIDDELPQSEH 500
501 EDDDYEEEDEDYNDEEEDVEYDDGDDDDDDDDEFVATRKNTHVISTTSRN 550
551 GRKPIVKFFKGKPRLLSPEISLKDYQQTGINWLNLLYQNKMSCILADDMG 600
601 LGKTCQVISFFAYLKQINEPGPHLVVVPSSTLENWLREFQKFAPALKIEP 650
651 YYGSLQEREELRDILERNAGKYDVIVTTYNLAAGNKYDVSFLKNRNFNVV 700
701 VYDEGHMLKNSTSERFAKLMKIRANFRLLLTGTPLQNNLKELMSLLEFIM 750
751 PNLFISKKESFDAIFKQRAKTTDDNKNHNPLLAQEAITRAKTMMKPFILR 800
801 RRKDQVLKHLPPKHTHIQYCELNAIQKKIYDKEIQIVLEHKRMIKDGELP 850
851 KDAKEKSKLQSSSSKNLIMALRKASLHPLLFRNIYNDKIITKMSDAILDE 900
901 PAYAENGNKEYIKEDMSYMTDFELHKLCCNFPNTLSKYQLHNDEWMQSGK 950
951 IDALKKLLKTIIVDKQEKVLIFSLFTQVLDILEMVLSTLDYKFLRLDGST 1000
1001 QVNDRQLLIDKFYEDKDIPIFILSTKAGGFGINLVCANNVIIFDQSFNPH 1050
1051 DDRQAADRAHRVGQTKEVNITTLITKDSIEEKIHQLAKNKLALDSYISED 1100
1101 KKSQDVLESKVSDMLEDIIYDENSKPKGTKE 1131
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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