 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q09798 from www.uniprot.org...
The NucPred score for your sequence is 0.51 (see score help below)
1 MDAWKEITKTTENDGVSTCSLSSIAFDPYSELVWTGHKNGQIKSSFGPSL 50
51 TSYTQFIGHEGPVHQVLPQERGVFSLSSKSLRLSNRKGTIRWRYQDSDCI 100
101 DYRAMFYQSRNNPEVVIGGYHQKLTVVNAERGISIHKDKNVSDIFIMRRN 150
151 RLLCCGSTNGEIILRDPNSFQPVNKVVAHTGTISDIDTSGNLLLSCGYSL 200
201 RHGTYMLDPFVKVWDLRNLSSLVPIPFPAGPTIIRMHPKLSTTAVVCSCS 250
251 GQFHIVDTGNPLDAKLMQIPLTSYLTGMDIASTGDAMVFTDVEDNIHLWS 300
301 PLENPSFSDLKLPIQLPNTSTETVQLENNDPLNSIGLPYYKDELLSSWSK 350
351 YLIFDVGKPILDSNLLIAKQISENSHPVPQEIKSFHRNQIIEVPWLNRKL 400
401 ISEGATPKFHSERQKDIMSGNDIEGSASYFEEIEDTISGPDSIPKFYQRP 450
451 VIKYSKFGIEDFDFGFYNKTKYAGLETDITNSYCNSVLQLLSYVPSFSKA 500
501 AISHSLGPCDLMECLLCELGFLFAMLKESTGRNCQATNFLRAFSNSSFAQ 550
551 SLGIVFDDYSDGTFPDSFVIQKFTKFMLTEISRIADYEDKKDGTSFPVSF 600
601 LLKSFCIPEMQTYRCGICGITSQKIKSSLYIIDLHYPSQQLESILSFEWL 650
651 FKMSLDRRVDLPPGWCEYCLAHQPFLLRSFIRSLPDCLFINTQVKHHEHW 700
701 KLWARKNWLPKKLHLRRVNDTMQCVSQKISNLDKDQQSLSVYVLRGIIYE 750
751 IRQNGEEPHFVSTIRVSDNTSSDNPDDNRWYIFNDFLVKEVTEEEALTVH 800
801 GPWKIPIIVYYEKLDTKIPQWDEVSDYTLLYQPYSLNKNPPINKIQPLTT 850
851 DEMLYPKMLVGIDSEFVALQQEETEVRSDGTKSTIKPSKLSLARVSVLRG 900
901 EGPNKGLPFIDDYVATDDKVTDYLTEYSGIHPGDLDPDRSPYNVVPLKVA 950
951 YKKLRLLVNAGCIFVGHGLQKDFRIINLLVPPEQVVDTVDLFFLSSRQRK 1000
1001 LSLKFLAWYLLDEEIQLTEHDSIEDALTALKLYDCYDKLKSQGKLEETLD 1050
1051 NIYEVGRRFKFRPPSVASMSLEDRNSYGDESVISNQTN 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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