 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P19069 from www.uniprot.org...
The NucPred score for your sequence is 0.67 (see score help below)
1 MRLLWGLLWAFGLFASSLQKPRLLLFSPSVVNLGVPLSVGVQLQDARQGE 50
51 VVTGFVFLRNPSHNNDRCSPKKAFTLTSQQDFVHLSLQVPQSDAKSCGLF 100
101 GLRRSPEVQLVAQSPWLRDVLAKETDTQGVNLLFASRRGHFFVQTDQPVY 150
151 NPGQRVQYRVFALDQKMRPSKDSLLVTVENSRGLRVRKKEVRDPSSIFQD 200
201 SFLIPDISEPGTWRISAQFSDSLEANSSTKFEVKKYVLPNFEVKITPRKP 250
251 YILVTSNHLGEIQVDIEARYIYGKPVQGVAYVRFGLLDEDGTKNFLRGLE 300
301 TQLKLKDGKSHVSLSRVELEGALQKLRLSVPDLQGLRLYTSAAVIESPGG 350
351 EIEEAELTSWHFVPSAFSLDLSNTKRHLVPGAPFLLQALVREASGPPAPD 400
401 VPVKVSVTLSGSVPKVPEIVQNTDRMGQVNMAINIPWGTTRLQLLVSAGS 450
451 LYPAVARLEVRAPPSGSSGFLSIERPDPRAPRVQETVTLNLRSVGLSRAT 500
501 FPYYYYMVLSRGEIVSVGRERRQELTSVSVFVDHHLAPAFYFVAFYYHKG 550
551 QPVANSLRVDVEAGACEGKLELRLDGTKDYRNGDSAKLQLLTDSEALVAL 600
601 GAVDTALYAVGSRTHKPLDMAKVFEVMNSYNLGCGPGGGDSAPQVFRAVG 650
651 LAFSDGDLWTPVRETLSCPKEEKARKKRSVDFQKAVSEKLGQFASPEAKR 700
701 CCQDGLTRLPMVRSCEQRAARVLQPACREPFLSCCQFAESLRKKSRAESP 750
751 GGLGRAMEVLQEEELLEEDMILVRSFFPENWLWRVLRVDRSETLTVWLPD 800
801 SMTTWEIHGVSLSQSKGLCVATPARLRVFREFHLHVRLPASIRRFEQLEL 850
851 RPVLYNYLEENLTMSVHIAPVEGLCLAGGGGLAQQVHVPAGSARPVPFFV 900
901 VPTAATAVSLKVVARGTTLVGDAVSKVLQIEKEGAIHQEELVYELNPLDH 950
951 RARTLEIPGNSDPNMIPEGESSSFVRVTASNPLETLGSEGALSPGGIASH 1000
1001 LRLPTGCGEQTMTLLAPTLAASRYLDRTEQWSKLPPETKDRAVDLIQKGY 1050
1051 MRIQEYRKSDGSYAAWLSRESSTWLTAFVLKVLSLAQDQVGGSPEKLQET 1100
1101 ASWLLGMQQADGSFHDPCPVIHRDMQGGLVGSDETVALTAFVVIALQHGL 1150
1151 NAFQDQSAEALKQRVKASILKADSYLGGKASAGLLGAHAAAITAYALTLT 1200
1201 KAPQDLQDVAHNNLMVMAQEIGDNRYWGSVTTSQSNVVSPTLAPLSPTDP 1250
1251 MPQAPALWIETTAYGLLHLLLREGKAELADQVANWLMHQASFHGGFRSTQ 1300
1301 DTVMAMDALSAYWIASHTTENKELNVTLSAMGRRGFKSHILQLDSRQVQG 1350
1351 LEEELQFSLSSKISVKVGGNSKGTLKVLRTYHVLDMTNTTCQDLRIEVTV 1400
1401 MGYVEYTRQANADYEEDYEYDEFLAGDDPGAPLRPVMPLQLFEGRRNRRR 1450
1451 REAPKVAEEQEPRVQYTVCIWREGKMRLSGMAIADITLLSGFSALSADLE 1500
1501 KLTSLSDRYVSHFETQGPHVLLYFDSVPTSRECVGFGAMQEVAVGLVQPA 1550
1551 SAVVYDYYSPERRCSVFYGAPEKSKLLSTLCSGDVCQCAEGKCPRQRRAL 1600
1601 ERGLQDEDRYRMKFACYHPRVEYGFQVRVLREDSRAAFRLFETKIIQVLH 1650
1651 FTKDAKAAADQTRNFLVRDSCRLHLEPGREYLIMGLDGITSDLKGDPQYL 1700
1701 LDSKSWIEEMPSERLCRSTRQRAACAQLNDFIQEYSTLGCQV 1742
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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