 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P12845 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MDYENDPGWKYLRRSREEMLQDQSRAYDSKKNVWIPDSEDGYIEGVITKT 50
51 AGDNVTVSIGQGAEKTVKKDVVQEMNPPKFEKTEDMSNLTFLNDASVLYN 100
101 LKARYAAMLIYTYSGLFCVVINPYKRLPIYTDSVARMFMGKRRTEMPPHL 150
151 FAVSDEAYRNMLQNHENQSMLITGESGAGKTENTKKVISYFAAVGAAQQE 200
201 TFGAKKAATEEDKNKKKVTLEDQIVQTNPVLEAFGNAKTVRNNNSSRFGK 250
251 FIRIHFSKQGRVASCDIEHYLLEKSRVIRQAPGERCYHIFYQVFSDYLPN 300
301 LKKDLLLNKPVKDYWFIAQAELIIDGINDKEEHQLTDEAFDILKFTPTEK 350
351 MECYRLVAAMMHMGNMKFKQRPREEQAEPDGTDDAERAAKCFGIDSEEFL 400
401 KALTRPRVKVGNEWVNKGQNIEQVNWAVGAMAKGLYSRIFNWLVKKCNQT 450
451 LDQKGISRDHFIGVLDIAGFEIFDFNSFEQLWINFVNEKLQQFFNHHMFV 500
501 LEQEEYAREGIQWTFIDFGLDLQACIELIEKPLGIIAMLDEECIVPKATD 550
551 LTLAQKLIDQHLGKHPNFEKPKPPKGKQAEAHFAMRHYAGTVRYNCLNWL 600
601 EKNKDPLNDTVVTVMKASKEHALIVEVWQDYTTQEEAAAAAAKGTAGAKK 650
651 KGKSGSFMTVSMLYRESLNKLMTMLHSTHPHFIRCIIPNEKKASGVIDAG 700
701 LVLNQLTCNGVLEGIRICRKGFPNRTLHPDFVQRYALLAADESIIGKTDA 750
751 KKGSALMLARLVKEKKLEEENFRVGLTKVFFKAGIVAHLEDLRDQSLAQL 800
801 ITGLQAQIRWYYQTIERKRRVEKITALKIIQRNIRSWAELRTWVWFKLYG 850
851 KVKPLVNSGKIEAQYEKLQETVATLKDTVVQEEEKKRQLQEGAERLNKET 900
901 ADLLAQLEASKGSTREVEERMTAMNEQKVALEGKLADASKKLEVEEARAV 950
951 EINKQKKLVEAECADLKKNCQDVDLSLRKVEAEKNAKEHQIRALQDEMRQ 1000
1001 QDENISKLNKERKNQEEQNKKLTEDLQAAEEQNLAANKLKAKLMQSLEDS 1050
1051 EQTMEREKRNRADMDKNKRKAEGELKIAQETLEELNKSKSDAENALRRKE 1100
1101 TELHTLGMKLEDEQAAVAKLQKGIQQDEARVKDLHDQLADEKDARQRADR 1150
1151 SRADQQAEYDELTEQLEDQARATAAQIELGKKKDAELTKLRRDLEESGLK 1200
1201 FGEQLTVLKKKGSDAIQELSDQIEQLQKQKGRIEKEKGHMQREFDESSAA 1250
1251 LDQEAKLRADQERIAKGYEVRLLELRLKADEQSRQLQDFVSSKGRLNSEN 1300
1301 SDLARQVEELEAKIQAANRLKLQFSNELDHAKRQAEEESRERQNLSNLSK 1350
1351 NLARELEQLKESIEDEVAGKNEASRQLSKASVELDQWRTKFETEGLIGAD 1400
1401 EFDEVKKRQNQKTSEIQDALDACNAKIVALENARSRLTAEADANRLEAEH 1450
1451 HAQAVSSLEKKQKAFDKVIDEWKKKVDDLYLELDGAQRDARQLSGEAHKL 1500
1501 RGQHDTLADQVEGLRRENKSLSDETRDLTESLSEGGRATHALSKNLRRLE 1550
1551 MEKEELQRGLDEAEAALESEESKALRCQIEVSQIRAEIEKRIAEKEEEFE 1600
1601 NHRKVHQQTIDSIQATLDSETKAKSELFRVKKKLEADINELEIALDHANK 1650
1651 ANEDAQKNIRRYLDQIRELQQTVDEEQKRREEFREHLLAAERKLAVAKQE 1700
1701 QEELIVKLEALERARRVVESSVKEHQEHNNELNSQNVALAAAKSQLDNEI 1750
1751 ALLNSDIAEAHTELSASEDRGRRAASDAAKLAEDLRHEQEQSQQLERFKK 1800
1801 QLESAVKDLQERADAAEAAVMKGGAKAIQKAEQRLKAFQSDLETESRRAG 1850
1851 EASKTLARADRKVREFEFQVAEDKKNYDKLQELVEKLTAKLKLQKKQLEE 1900
1901 AEEQANSHLSKYRTVQLSLETAEERADSAEQCLVRIRSRTRANAEQK 1947
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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