 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5R607 from www.uniprot.org...
The NucPred score for your sequence is 0.64 (see score help below)
1 MFSLDSFRKDRAQHRQRQCKLPPPRLPPMCVNPAPGGTISRASRDLLKEF 50
51 PQPKNLLNSVIGRALGISHAKDKLVYVHTNGPKKKKVTLHIKWPKSVEVE 100
101 GYGSKKIDAERQAAAAACQLFKGWGLLGPRNELFDAAKYRVLADRFGSPA 150
151 DSWWRPEPTMPPTSWRQLNPESIRPGGPGGLSRSLGREEEEDEEEELEEG 200
201 TIDVTDFLSMTQQDSHTPLRDSRGSSFEMTDDDSAIRALTQFPLPKNLLA 250
251 KVIQIATSSSTAKNLMQFHTVGTKTKLSTLTLLWPCPMTFVAKGRRKAEA 300
301 ENKAAALACKKLKSLGLVDRNNEPLTHAMYNLASLRELGETQRRPCTIQV 350
351 PEPILRKIETFLNHYPVESSWIAPELRLQSDDILPLGKDSGPLSDPITGK 400
401 PYVPLLEAEEVRLSQSLLELWRRRGPVWQEAPQLPVDPHRDTILNAIEQH 450
451 PVVVISGDTGCGKTTRIPQLLLERYVTEGRGARCNVIITQPRRISAVSVA 500
501 QRVSHELGPSLRRNVGFQVRLESKPPARGGALLFCTVGILLRKLQSNPSL 550
551 EGVSHVIVDEVHERDVNTDFLLILLKGLQRLNPALRLVLMSATGDNERFS 600
601 RYFGGCPVIKVPGFMYPVKEHYLEDILAKLGKHQYLHRHRHHESEDECAL 650
651 DLDLVTDLVLHIDARGEPGGILCFLPGWQEIKGVQQRLQEALGMHESKYL 700
701 ILPVHSNIPMMDQKAIFQQPPVGVRKIVLATNIAETSTTINDIVHVVDSG 750
751 LHKEERYDLKTKVSCLETVWVSRANVIQRRGRAGRCQSGFAYHLFPRSRL 800
801 EKMVPFQVPEILRTPLENLVLQAKIHMPEKTAVEFLSKAVDSPNIKAVDE 850
851 AVILLQEIGVLDQREYLTTLGQRLAHISTEPRLAKAIVLAAIFRCLHPLL 900
901 VVVSCLTRDPFSSSLQNRAEVDKVKALLSHDSGSDHLAFVRAVAGWEEVL 950
951 RWQDRSSRENYLEENLLYAPSLRFIHGLIKQFSENIYEAFLVGKPSDCTL 1000
1001 ASAQCNEYSEEEELVKGVLMAGLYPNLIQVRQGKVTRQGKFKPNSVTYRT 1050
1051 KSGNILLHKSTINREATRLRSRWLTYFMAVKSNGSVFVRDSSQVHPLAVL 1100
1101 LLTDGDVHIRDDGRRATISLSDSDLLRLEGDSRTVRLLKELRRALGRMVE 1150
1151 RSLRSELAALPPSVQEEHGQLLALLAELLRGPCGSFDVRKTADD 1194
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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