 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q59X11 from www.uniprot.org...
The NucPred score for your sequence is 0.87 (see score help below)
1 MIPQWIPQNIQKRLLLYVLQQLSLFSEIDLPNLEEVSLNNIILKDVALDP 50
51 EKVGKLPGCNLRYGQIGSLELTTISGISGVNIDVNDAEIVISPDFDIDEN 100
101 MTNQVAFSLAQSTANLANTIMLNTNDGSDMNETSDPASEDDDEDDIDDKI 150
151 TKPIPPKRRTSSVTGNKTTALGGVMQKAVEIALSRLSIKVNSLKIKIVSD 200
201 LTDLQMEVDSVSINSTNGTRTVSIKGVKLRTLKPNVNPGEGFQSGHAPQK 250
251 KQQGSDNDSPTDANKHGSENDNDDDDDDYGNESLMDSMVFSHEEASSIYM 300
301 SATSRSFEKSAASGIPGEVDNKATDKEDYSEDPPIIFYMDDCTIEFDGLS 350
351 TISNLEIEVGNINLAFTPLTPTLVSIFQGVAKSLKIKYYQQKKKTKSRSA 400
401 QRNEKFPQYTNDNDEIPEDQSESDDASHEPFFNRFKVNSFVISATSALSE 450
451 NGLFANKNGINIIFFNINIKQKNELLLYGGVETFKIIRFEDDNTYEIFHF 500
501 DKPQSAPSSAPSYSGSNDVAGTSSSLSSSTGSATSKADIRFEVFKKSEES 550
551 DDLEVTVLMAKSAHFNFDLQSLLILSNFAKAVSSIYDEYGLLKSVIDKLD 600
601 TRDKKWSGGTNNSKMSSKSEFILQTATIFVNFIISDDCQLQLIVFPIKFN 650
651 LRQEQLTISKILLNCTNGDTQVEGVIILTDVSLITKNQEFRAYFQSTNTT 700
701 TSANTHPLPRKTTMNSKLSVIVQKFSSNVSMDRLKFIGEKLKNFSNEFIE 750
751 RSPTQSNSLENSFLNEPVERQRLESSLHMNSSLFSTRRPGRRLGLGFNNS 800
801 PSVFLGSTRVTMASFQVCFKEATFNITGVFPKFGNFSVQMSDISFYKLKN 850
851 DILGHILSVSVQRKKGDLVENLIHQYQDLSPNSLEFPLLSIKCKLGDKTT 900
901 KIEITARNLVLEYYTNWLLLMDKEESIIDAVEEEIIEKVTPSQHSSSQNK 950
951 LDIRYSMYDCMVGLTPGRLSCKSYLIIGKGDSDISFGVDQFYVKCSFRNI 1000
1001 SMVLIDDTKNILPFSEPSTSSSSSSSSATRQTPYVYIQPLDYYSKLGYIH 1050
1051 LGLINVAHVGITFNTDIEALKDRNEKLGIKDSLTFVDLKTNLDECQFNLC 1100
1101 ADTANTLIQLVNDLKLPLNFKDEDKMKVDFADGINVMQGIDQNIFKGLTE 1150
1151 TLTELNLNGTENGSTSESSSQEASSLMFEEGHFDRGNRSLYDNSHVDPLH 1200
1201 ININLSKVKIYLHDGYDWKDTRKAIRGAVKNFETAQTAKTVAKEKEKKRK 1250
1251 VEFETRDIEVQEDVFQETLFQSIHVVAPRNQNARDMATSINLDLQNDKDG 1300
1301 ESRDVSTANSGKSYKNLKLRRSAKHKLLFDLKSIEVGVNVYSTRDPRRDK 1350
1351 TDENMKYELLNFIELRVGTVDIYDNVSTSTWNKFLSYMNILGDREIGTSM 1400
1401 VKVSILNVRPDPAMVSGEAIMNVSVLPLRLHIDQDALDFLVRFFEFKDER 1450
1451 FELPPDEMVYIQKFEISSIKLKLDYKPKKVDYAGLRSGKAGEFANFFTLD 1500
1501 GSTLTLPKVKLFGIPGAPKIGIGLGRAWLPVFQSTQVIGIISGVSPLRSV 1550
1551 VNIGGGFKDLVAIPISEYKKDGRLWRSIQKGTVSFAKTTGYEILNLGVKL 1600
1601 ASGTQVLLEQGEEMLGGEGSSVRSPNLGGSDNRRNSNASDELPVEVAKPK 1650
1651 SQNNLLVSSQILNKASTKIETHSYDTKKLYSNIELDDEDMDDNRINGINK 1700
1701 ELLSKSIFLLAPAEEKLAKLQPHTKGNHEGLTEEEEDEDEDEEYQLYAYE 1750
1751 NEEELQEKLVSLYSNQPETIEQGLKSAYKSLGTNFKLTKKQLLKLRRELA 1800
1801 ETDTIQDSMVTVLKNSPIILMRPLIGSTEAVSKLLMGVGNQIDGKKLVEK 1850
1851 KDKYPT 1856
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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