 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q99NF8 from www.uniprot.org...
The NucPred score for your sequence is 0.57 (see score help below)
1 MALHFQSLAELEVLCTHLYVGTDLTERIEAEKALLELIDSPECLSKCQLL 50
51 LEQGTTSYAQLLAATCLSKLVTRINPLPIEQRIDIRNYILNYVASQPKLA 100
101 PFVIQALIQVIAKLTKLGWFEVQKDEFVFREIIADVKKFLQGTVEHCIIG 150
151 VIILCELTQEMNLVDYSRPSAKHRKIATSFRDTSLKDILVLACSLLKQVL 200
201 AKPLNLQDQDQQSLVMQVLKLVLSCLNFDFLGSSADESADDLCTVQIPTT 250
251 WRTIFLEPETLDLFFNLYHSLPPLLSQLALSCLVQFASTRRSLFSSPERA 300
301 KYLGNLIKGVKRILENPQGLSDPGNYHEFCRFLARLKTNYQLGELVLVKE 350
351 YAEVIGLIANFTITSLQHWEFAPNSVHYLLTLWQRMVASVPFVKSAEPHL 400
401 LDTYAPEITKAFITSRLESVAIVVRDNLEDPLDDTATVFQQLEQLCTVSR 450
451 CEYEKTCTLLVQLFDQNAQNYQKLLHAAPGLAVDMAIQEGRLAWLIYLVG 500
501 TVVGGRLTYTSTDEHDAMDGELSCRVFQLISLMDTRLPHCTNEKIELAVL 550
551 WFLDQFRKTYVGDQLQRTSKVYARMSEVLGITDDNHVLETFMTKIVTNLK 600
601 YWGRCEPVISRTLQFLSDLSVGYILLKKLVKIDAVKFMLKNHTSEHFPFL 650
651 GISETYNVGDFRCRTTFYTALTRLLMVDLGEDEDEFENFMLPLTVSFETV 700
701 LQIFNNNFKQEEVKRMLIGLARDLRGIAFALNTKTSYTMLFDWIYPAYLP 750
751 VLQRAIERWYGEPACTTPILKLLAELMQNRSQRLNFDVSSPNGILLFREA 800
801 SKMICTYGNQILSLGSLSKDKIYPMKLKGISICYSALKSALCGNYVSFGV 850
851 FKLYGDNHFDNVLQAFVKMLLSVSHSDLLQYRKLSQSYYPLLECLTQDHM 900
901 SFITNLEPPVLLYVLTSLSEGLTTLDTVVSSSCCTSLDYMVTYLFKHIAK 950
951 EGKKPLRSREAMQAGQRLLHFMQQNPDVLQQMMSVLMNTIVFEDCRNQWS 1000
1001 VSRPLLGLILLNEKYFSELRASLINSQPLPKQEVLGQCFRNLMEGVEQNL 1050
1051 SVKNRDRFTQNLSVFRRDVAEALRSDGHTDLSSLDMMS 1088
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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