 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q99PJ1 from www.uniprot.org...
The NucPred score for your sequence is 0.52 (see score help below)
1 MFLQFAVWKCLPHGILIASLLVVSWGQYDDDWQYEDCKLARGGPPATIVA 50
51 IDEESRNGTILVDNMLIKGTAGGPDPTIELSLKDNVDYWVLLDPVKQMLF 100
101 LNSTGRVLDRDPPMNIHSIVVQVQCVNKKVGTVIYHEVRIVVRDRNDNSP 150
151 TFKHESYYATVNELTPVGTTIFTGFSGDNGATDIDDGPNGQIEYVIQYNP 200
201 EDPTSNDTFEIPLMLTGNVVLRKRLNYEDKTRYYVIIQANDRAQNLNERR 250
251 TTTTTLTVDVLDGDDLGPMFLPCVLVPNTRDCRPLTYQAAIPELRTPEEL 300
301 NPILVTPPIQAIDQDRNIQPPSDRPGILYSILVGTPEDYPRFFHMHPRTA 350
351 ELTLLEPVNRDFHQKFDLVIKAEQDNGHPLPAFASLHIEILDENNQSPYF 400
401 TMPSYQGYILESAPVGATISESLNLTTPLRIVALDKDIEDTKDPELHLFL 450
451 NDYTSVFTVTPTGITRYLTLLQPVDREEQQTYTFLITAFDGVQESEPVVV 500
501 NIRVMDANDNTPTFPEISYDVYVYTDMSPGDSVIQLTAVDADEGSNGEIS 550
551 YEILVGGKGDFVINKTTGLVSIAPGVELIVGQTYALTVQASDNAPPAERR 600
601 HSICTVYIEVLPPNNQSPPRFPQLMYSLEVSEAMRIGAILLNLQATDREG 650
651 DPITYAIENGDPQRVFNLSETTGILSLGKALDRESTDRYILIVTASDGRP 700
701 DGTSTATVNIVVTDVNDNAPVFDPYLPRNLSVVEEEANAFVGQVRATDPD 750
751 AGINGQVHYSLGNFNNLFRITSNGSIYTAVKLNREARDHYELVVVATDGA 800
801 VHPRHSTLTLYIKVLDIDDNSPVFTNSTYTVVVEENLPAGTSFLQIEAKD 850
851 VDLGANVSYRIRSPEVKHLFALHPFTGELSLLRSLDYEAFPDQEASITFL 900
901 VEAFDIYGTMPPGIATVTVIVKDMNDYPPVFSKRIYKGMVAPDAVKGTPI 950
951 TTVYAEDADPPGMPASRVRYRVDDVQFPYPASIFDVEEDSGRVVTRVNLN 1000
1001 EEPTTIFKLVVVAFDDGEPVMSSSATVRILVLHPGEIPRFTQEEYRPPPV 1050
1051 SELAARGTVVGVISAAAINQSIVYSIVAGNEEDKFGINNVTGVIYVNSPL 1100
1101 DYETRTSYVLRVQADSLEVVLANLRVPSKSNTAKVYIEIQDENDHPPVFQ 1150
1151 KKFYIGGVSEDARMFASVLRVKATDRDTGNYSAMAYRLIIPPIKEGKEGF 1200
1201 VVETYTGLIKTAMLFHNMRRSYFKFQVIATDDYGKGLSGKADVLVSVVNQ 1250
1251 LDMQVIVSNVPPTLVEKKIEDLTEILDRYVQEQIPGAKVVVESIGARRHG 1300
1301 DAYSLEDYSKCDLTVYAIDPQTNRAIDRNELFKFLDGKLLDINKDFQPYY 1350
1351 GEGGRILEIRTPEAVTSIKKRGESLGYTEGALLALAFIIILCCIPAILVV 1400
1401 LVSYRQFKVRQAECTKTARIQSAMPAAKPAAPVPAAPAPPPPPPPPPPGA 1450
1451 HLYEELGESAMHNLFLLYHFEQSRGNNSVPEDRSSHRDGMAFSSSTTESH 1500
1501 EPAHVEGPLKESQPNPARTFSFVPDEDNLSTHNPLYMESIGQRSTNSDLQ 1550
1551 PRTDFEELLAPRTQVKSQSLRGPREKIQRVWNQSVSFPRRLMWKAPNRPE 1600
1601 TIDLVEWQITNQRAECESARCHPSQRGSSNVLLATEDAHESEKEGGHRDT 1650
1651 LIVQQTEQLKSLSSGSSFSSSWSHFSFSTLPTISRAVELGSEPNVVTSPA 1700
1701 DCTLELSPPLRPRILNSLSSKRETPTCASDTEPKRNSFEIAPHPPSISAP 1750
1751 LPHPPLPRPPIAFTTFPLPLSPPNPPPPQLVTFSLPISTPPTSSLPLPPP 1800
1801 LSLPPPPRPPAPRLFPQPPSTSIPSTDSISAPAAKCTASATHARETTSTT 1850
1851 QPPASNPQWGAEPHRHPKGILRHVKNLAELEKSVSNMYSHIEKNCPPADP 1900
1901 SKLHTFCPAEKTGMKITHDQSQETLVRVVEGIDVQPHSQSTSL 1943
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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