 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q99550 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MEEFDLVKTLHKTSSSVGSDENSLHSLGLNLNTDRSSPHLSTNGVSSFSG 50
51 KTRPSVIQGTVEVLTSLMQELQNSGKTDSELWKNCETRWLQLFNLVEKQC 100
101 QEQIVAQQEQFHNQIQHIQEEIKNLVKLQTSSASLASCEGNSSNKQVSSE 150
151 SQMGFFSLSSERNESVIHYPESTEPEIQQEMSTSQPDCNVDSCSVSSGYG 200
201 TFCISELNLYKSKDPKEFMEHIDVPKGQYVAPAVPAESLVDGVKNENFYI 250
251 QTPEECHVSLKEDVSISPGEFEHNFLGENKVSEVYSGKTNSNAITSWAQK 300
301 LKQNQPKRAHVEDGGSRSKQGNEQSKKTPIEKSDFAAATHPRAFYLSKPD 350
351 ETPNAWMSDSGTGLTYWKLEEKDMHHSLPETLEKTFISLSSTDVSPNQSN 400
401 TSNEMKLPSLKDIYYKKQRENKQLPERNLTSASNPNHPPEVLTLDPTLHM 450
451 KPKQQISGIQPHGLPNALDDRISFSPDSVLEPSMSSPSDIDSFSQASNVT 500
501 SQLPGFPKYPSHTKASPVDSWKNQTFQNESRTSSTFPSVYTITSNDISVN 550
551 TVDEENTVMVASASVSQSQLPGTANSVPECISLTSLEDPVILSKIRQNLK 600
601 EKHARHIADLRAYYESEINSLKQKLEAKEISGVEDWKITNQILVDRCGQL 650
651 DSALHEATSRVRTLENKNNLLEIEVNDLRERFSAASSASKILQERIEEMR 700
701 TSSKEKDNTIIRLKSRLQDLEEAFENAYKLSDDKEAQLKQENKMFQDLLG 750
751 EYESLGKEHRRVKDALNTTENKLLDAYTQISDLKRMISKLEAQVKQVEHE 800
801 NMLSLRHNSRIHVRPSRANTLATSDVSRRKWLIPGAEYSIFTGQPLDTQD 850
851 SNVDNQLEETCSLGHRSPLEKDSSPGSSSTSLLIKKQRETSDTPIMRALK 900
901 ELDEGKIFKNWGTQTEKEDTSNINPRQTETSVNASRSPEKCAQQRQKRLN 950
951 SASQRSSSLPPSNRKSSTPTKREIMLTPVTVAYSPKRSPKENLSPGFSHL 1000
1001 LSKNESSPIRFDILLDDLDTVPVSTLQRTNPRKQLQFLPLDDSEEKTYSE 1050
1051 KATDNHVNHSSCPEPVPNGVKKVSVRTAWEKNKSVSYEQCKPVSVTPQGN 1100
1101 DFEYTAKIRTLAETERFFDELTKEKDQIEAALSRMPSPGGRITLQTRLNQ 1150
1151 EALEDRLERINRELGSVRMTLKKFHVLRTSANL 1183
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.) |
Go back to the NucPred Home Page.