 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q96QT4 from www.uniprot.org...
The NucPred score for your sequence is 0.81 (see score help below)
1 MSQKSWIESTLTKRECVYIIPSSKDPHRCLPGCQICQQLVRCFCGRLVKQ 50
51 HACFTASLAMKYSDVKLGDHFNQAIEEWSVEKHTEQSPTDAYGVINFQGG 100
101 SHSYRAKYVRLSYDTKPEVILQLLLKEWQMELPKLVISVHGGMQKFELHP 150
151 RIKQLLGKGLIKAAVTTGAWILTGGVNTGVAKHVGDALKEHASRSSRKIC 200
201 TIGIAPWGVIENRNDLVGRDVVAPYQTLLNPLSKLNVLNNLHSHFILVDD 250
251 GTVGKYGAEVRLRRELEKTINQQRIHARIGQGVPVVALIFEGGPNVILTV 300
301 LEYLQESPPVPVVVCEGTGRAADLLAYIHKQTEEGGNLPDAAEPDIISTI 350
351 KKTFNFGQNEALHLFQTLMECMKRKELITVFHIGSDEHQDIDVAILTALL 400
401 KGTNASAFDQLILTLAWDRVDIAKNHVFVYGQQWLVGSLEQAMLDALVMD 450
451 RVAFVKLLIENGVSMHKFLTIPRLEELYNTKQGPTNPMLFHLVRDVKQGN 500
501 LPPGYKITLIDIGLVIEYLMGGTYRCTYTRKRFRLIYNSLGGNNRRSGRN 550
551 TSSSTPQLRKSHESFGNRADKKEKMRHNHFIKTAQPYRPKIDTVMEEGKK 600
601 KRTKDEIVDIDDPETKRFPYPLNELLIWACLMKRQVMARFLWQHGEESMA 650
651 KALVACKIYRSMAYEAKQSDLVDDTSEELKQYSNDFGQLAVELLEQSFRQ 700
701 DETMAMKLLTYELKNWSNSTCLKLAVSSRLRPFVAHTCTQMLLSDMWMGR 750
751 LNMRKNSWYKVILSILVPPAILLLEYKTKAEMSHIPQSQDAHQMTMDDSE 800
801 NNFQNITEEIPMEVFKEVRILDSNEGKNEMEIQMKSKKLPITRKFYAFYH 850
851 APIVKFWFNTLAYLGFLMLYTFVVLVQMEQLPSVQEWIVIAYIFTYAIEK 900
901 VREIFMSEAGKVNQKIKVWFSDYFNISDTIAIISFFIGFGLRFGAKWNFA 950
951 NAYDNHVFVAGRLIYCLNIIFWYVRLLDFLAVNQQAGPYVMMIGKMVANM 1000
1001 FYIVVIMALVLLSFGVPRKAILYPHEAPSWTLAKDIVFHPYWMIFGEVYA 1050
1051 YEIDVCANDSVIPQICGPGTWLTPFLQAVYLFVQYIIMVNLLIAFFNNVY 1100
1101 LQVKAISNIVWKYQRYHFIMAYHEKPVLPPPLIILSHIVSLFCCICKRRK 1150
1151 KDKTSDGPKLFLTEEDQKKLHDFEEQCVEMYFNEKDDKFHSGSEERIRVT 1200
1201 FERVEQMCIQIKEVGDRVNYIKRSLQSLDSQIGHLQDLSALTVDTLKTLT 1250
1251 AQKASEASKVHNEITRELSISKHLAQNLIDDGPVRPSVWKKHGVVNTLSS 1300
1301 SLPQGDLESNNPFHCNILMKDDKDPQCNIFGQDLPAVPQRKEFNFPEAGS 1350
1351 SSGALFPSAVSPPELRQRLHGVELLKIFNKNQKLGSSSTSIPHLSSPPTK 1400
1401 FFVSTPSQPSCKSHLETGTKDQETVCSKATEGDNTEFGAFVGHRDSMDLQ 1450
1451 RFKETSNKIKILSNNNTSENTLKRVSSLAGFTDCHRTSIPVHSKQAEKIS 1500
1501 RRPSTEDTHEVDSKAALIPDWLQDRPSNREMPSEEGTLNGLTSPFKPAMD 1550
1551 TNYYYSAVERNNLMRLSQSIPFTPVPPRGEPVTVYRLEESSPNILNNSMS 1600
1601 SWSQLGLCAKIEFLSKEEMGGGLRRAVKVQCTWSEHDILKSGHLYIIKSF 1650
1651 LPEVVNTWSSIYKEDTVLHLCLREIQQQRAAQKLTFAFNQMKPKSIPYSP 1700
1701 RFLEVFLLYCHSAGQWFAVEECMTGEFRKYNNNNGDEIIPTNTLEEIMLA 1750
1751 FSHWTYEYTRGELLVLDLQGVGENLTDPSVIKAEEKRSCDMVFGPANLGE 1800
1801 DAIKNFRAKHHCNSCCRKLKLPDLKRNDYTPDKIIFPQDEPSDLNLQPGN 1850
1851 STKESESTNSVRLML 1865
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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