 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8INR6 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MATPQVKDLVLRSPAGSSDVISFAWPLQIGHGQDKHDNGIDIIDTIKFVC 50
51 DELPSMSSAFEETNLHQIDTACYKTMTGLVDRFNKAVDSIVALEKGTSLP 100
101 AERLNKFAHPSLLRHILQLVYNAAVLDPDKLNQYEPFSPEVYGETSYELV 150
151 QQMLKHVTVSKEDTFIDLGSGVGQVVLQMAGSFPLKTCIGIEKADTPARY 200
201 AERMDVIFRQYMGWFGKRFCEYKLIKGDFLVDEHRENITSSTLVFVNNFA 250
251 FGPTVDHQLKERFADLRDGARVVSSKSFCPLNFRITDRNLSDIGTIMHVS 300
301 EIPPLKGSVSWTCKPVSYYLHVIDRTILERYFQRLKTKGGNDHESVGTVR 350
351 TTRDRAKREANVGQHHHNNHHSNNHANSNNHQRDREQSNGATATAAHQQR 400
401 HQSQSPANVSGAGIVLAASGQQAASKTRQQLQHQHNQQQRSLDMESSTES 450
451 DGDATNGNGGNTTTATNTTSASNGPMTRKVWSDWCSSKGKSSQSDDEENN 500
501 NSNSNGGSNGGSIGGGSVGRQARATTQKKRKKLTRKAAIASKSAAAAQRE 550
551 AEAAAAAAVSVPSKESSSKEDPPRAASAGPGRKGRMKKGARGRKSLKIVG 600
601 LEALHKQTVLSTSLDTMTKKLPAAPGTVDQQLTALLTENMSHAELDIPTA 650
651 PQDTPYALQILLDVFRSQYTSMIEHMKSSAYVPQVQKQIAQEQERMARLK 700
701 NRASQLDKQIKVLIDDSVALLKVRMNELGIHVNSPNDLIAQAKEIVGRHK 750
751 DLQHTASRMRNEVTFYEGEQKLLLNKQLKNLPEYQKLCGTVNGKVKLEVP 800
801 PELSETTAQELVLKEIANTLSQRKKLYAQVSTIEQETSVLQKTAEERSTA 850
851 ATLLAQGTNMIVSTGSSSSSSTTVCASAVTAQSNKLNSVKNSRRNREHRA 900
901 RSQEWPEVPEVGKIQESNPEVLAQKIVETCRQIEAGKFQGAGAPSSQVNG 950
951 KNKAIIEVPPPPATAPVSIKSSPGHHYKDTTLMPAPKQQQQQQMTLSQLP 1000
1001 KCELPGLSTSRKQESPKVANFEDRLKSIITTALNEDQEQRSKAVESSPSP 1050
1051 SPLHSPAPKRSKQHPAGAINPAQSLPNNLHNIITVSTQGLMHLNANTTIS 1100
1101 PITPPLPGPGAGATASTAPPPPANLPYGAYGGAVAKTTISGKYQAAKEPK 1150
1151 YSPVRQAPLPPPPSHMASLYPAGQQTTPADLGYQRRRSSVSATSYEHYMV 1200
1201 QQQQQLQQQQLMLAAAAHAAQRQQMRVEEQQQQQQHQHHHHHHHHHPQHR 1250
1251 LPQHVQHQHPHQHHPNEFKAPPADSHLQRSSSREQLIVEPPQTQPLELLP 1300
1301 RASSANSDYSGYRIRPPSRPSSNSSQPDYTQVSPAKMALRRHLSQEKLSQ 1350
1351 HVTPQATPPLPGHGGAPTSGKTIGDLVNGEIERTLEISHQSIINAAVNMS 1400
1401 TSGASFMERAFLNERSNDRLLINLNAQRPERVHVRPLSEESQDPQPTSYA 1450
1451 QERGPGLGAGGAAAGGNSNLATLAHVAYAQKAQGGARANAGTAPPATHSS 1500
1501 SARSGRDYQPVALPRAELKGSIEAYFHEEQQQKQSKGAGSAGSSSLRGPR 1550
1551 LNGANPPLEGLAASLQDHVRARKYKEETEERQRRAAAAASSSAGPPAGME 1600
1601 LPTHYAHQAPPAHSYHHHGASINGTPHKVELGIKRSSPLAPHQQPPRPSK 1650
1651 LAHYEPPTTQQQHAHAHLYANGQVLPPPPAHDATTPSPTPSSSSSSCGRR 1700
1701 SNSNNGKLLVDPPLLMSPEINSLLGDERPLQLSHHQQQQQQMLHHHQSQQ 1750
1751 QQHLQLTQQQLRVAHLGHGLSHGHSTMPTLGGQRNGNGNAADDVNDLATQ 1800
1801 RTITNYDPRRRLRTTLSGPTKLSAAHSNQNLNGYVMADSSSSCPTIPQ 1848
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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