 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8N957 from www.uniprot.org...
The NucPred score for your sequence is 0.89 (see score help below)
1 MNEKRLLFKDRHFTCSKIIGRRFACFAQRLSHRRKQSQCDLLNESTGQLP 50
51 TTCSSAASNSINWNCRVKMTQQMQNLHLCQSKKHSAPSSPNAAKRLYRNL 100
101 SEKLKGSHSSFDEAYFRTRTDRLSLRKTSVNFQGNEAMFEAVEQQDMDAV 150
151 QILLYQYTPEELDLNTPNSEGLTPLDIAIMTNNVPIARILLRTGARESPH 200
201 FVSLESRAMHLNTLVQEAQERVSELSAQVENEGFTLDNTEKEKQLKAWEW 250
251 RYRLYRRMKTGFEHARAPEMPTNVCLMVTSSTSLTVSFQEPLSVNAAVVT 300
301 RYKVEWSMSEDFSPLAGEIIMDNLQTLRCTITGLTMGQQYFVQVSAYNMK 350
351 GWGPAQTTTPACASPSNWKDYDDREPRHKGQSEVLEGLLQQVRALHQHYS 400
401 CRESTKLQTTGRKQSVSRSLKHLFHSSNKFVKTLKRGLYIAVIFYYKDNI 450
451 LVTNEDQVPIVEIDDSHTSSITQDFLWFTKLSCMWEDIRWLRQSIPISSS 500
501 SSTVLQTRQKMLAATAQLQNLLGTHNLGRVYYEPIKDRHGNILIVTIREV 550
551 EMLYSFFNGKWMQISKLQSQRKSLSTPEEPTALDILLITIQDILSYHKRS 600
601 HQRLFPGLYLGYLKLCSSVDQIKVLVTQKLPNILCHVKIRENNNISREEW 650
651 EWIQKLSGSESMESVDHTSDCPMQLFFYELQMAVKALLQQINIPLHQARN 700
701 FRLYTQEVLEMGHNVSFLLLLPASDDVCTAPGQNNPYTPHSGFLNLPLQM 750
751 FELVHFCSYREKFISLYCRLSAVVELDSLNTQQSLREAISDSEVAAAKQR 800
801 HQQVLDFIQQIDEVWREMRWIMDALQYARYKQPVSGLPITKLIDPSDEQS 850
851 LKKINSTSSSHIDCLPSPPPSPEMHRRKTVSDSQPCSDEEACSEVFLPTN 900
901 SDYDSSDALSPRDLDLVYLSSHDIAQQTLSGLSGSAPDVLQVHDVKTPLG 950
951 PGQDPQGEGPNPDHSCAEFLHSLTLTGFTPKNHAKTVSGGRPPLGFLGKR 1000
1001 KPGKHPHYGGFSRHHRWLRIHSETQSLSLSEGIYTQHLSQACGLAQEPKE 1050
1051 AKRAGPALDDPRGLTLAHAASLPEERNSSLQDARPSVRRLYVEPYAAAVV 1100
1101 AQDEKPWASLSPPSGGRITLPSPTGPDVSQEGPTASPMSEILSSML 1146
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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