 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9JLH5 from www.uniprot.org...
The NucPred score for your sequence is 0.81 (see score help below)
1 MMDSGMEEDVTLPGTLSGCSGLHPVLPSDLDVISDTTGLGNGVLPIMSEE 50
51 KVSPTRARNMKDFENQITELKKENFNLKLRIYFLEERIQQEFAGPTEHIY 100
101 KKNIELKVEVESLKRELQERDQLLVKASKAVESLAEGGGSEIQRVKEDAR 150
151 KKVQQVEELLTKRIHLLEEDVKAAQAELEKAFAGTETEKALRLSLESKLS 200
201 AMKKMQEGDLEMTLALEEKDRLIEELKLSLKSKEALIQCLKEEKSQMASP 250
251 DENVSSGELRGLSATLREEKERDAEERQKERNHFEERIQALQEDLREKER 300
301 EIATEKKNSLKRDKAIQGLTMALKSKEKEVEELNSIIKELTADSTQSREA 350
351 PLKTQVSEFEVRESENCEAALAEKEALLAKLHSENVTKNTENHRLLRNVK 400
401 KVTQELNDLKKEKLRLERDLEEAHREGNRGARTIHDLRNEVEKLRKEVCE 450
451 REKAVEKHYKSLPGESSSKFHSQEQVVKGLTESASQEDLLLQKSNEKDLE 500
501 AIQQNCYLMTAEELKFGSDGLITEKCSQQSPDSKLIFSKEKQQSEYEGLT 550
551 GDLKTEQNVYAHLAKNLQDTDSKLQAELKRVLALRKQLEQDVLAYRNLQT 600
601 ALQEQLSEIRKREEEPFSFYSDQTSYLSICLEEHSQFQLEHFSQEEIKKK 650
651 VIDLIQLVKDLHADNQHLKKTIFDISCMGVQGNDRLESTKQAELMASKAD 700
701 EDTLKFKADDENHFQSDQHLEQSREIMEDYAEGGGKDGYVRHMDSNILDH 750
751 DGAHTPDTSEDHSLEDELLSLLATFFSKKATPSLESRPDLLKALGALLLE 800
801 RICLAEQGSPGDHSDSKAEKALEQVAVRLRDELGHSCLANSFSKSHSELK 850
851 SPRGTWLVKTGDEAKVELKSVSVQTMTIEDSTRGFKPERKREAWAGKPEE 900
901 AVFSTELESEALGEMPGLQATHLSFPSAIDKDDQKTGLLIQLKTPELLEN 950
951 LYNLPASQEVVAQLQGQVLELQKELKEYKIRNKQLLDKLILAEAMMEGMA 1000
1001 VPNSTPVNVPAAQAVVRTAFQGKPGEQEGHETTHSAGRDKEVDSDQYTSF 1050
1051 EIDSEICPPDDLALLPACKENLEDFLGPPSIATYLDSKSQLSVKVSVVGT 1100
1101 DQSENINLPDDTEALKQKIHDLQTELEGYRNIIVQLQKHSQCSEAIITVL 1150
1151 CGTEGAQDGLNKPKGHIDEEEMTFSSLHQVRYVKHMKILRPLTPEIIDGK 1200
1201 MLESLKQQLVEQEQELQKEQDLNLELFGEIHNLQNKFRDLSPSRYDSLVQ 1250
1251 SQARELSLQRQQIKDSHDICVVCHQHMSTMIKAFEELLQASDVDSCVAEG 1300
1301 FREQLTQCAGLLEQLEKLFLHGKSARVEPHTQTELLRRLRTEEDNLPYQH 1350
1351 LLPESPEPSASHALSDDEMSEKSFLSREPKPDSETEKYPTIASRFPQDLL 1400
1401 MEHIQEIRTLRKHLEESIKTNEKLRKQLERQGCETDQGSTNVSAYSSELH 1450
1451 NSLTSEIQFLRKQNEALSTMLEKGSKEKQKENEKLRESLARKTESLEHLQ 1500
1501 LEYASVREENERLRRDISEKERQNQQLTQEVCSSLQELSRVQEEAKSRQQ 1550
1551 LLLQKDELLQSLQMELKVYEKLAEEHQKLQQESRGEACGGGQKGQDPFSN 1600
1601 LHGLLKEIQVLRDQAERSIQTNNTLKSKLEKQLSQGSKQAQEGALTLAVQ 1650
1651 ALSVTEWSLQLDKHDVNKCPEASDNSFDLFESTQAMAPKSASETPVLSGT 1700
1701 DVDSLSCDSTSSATSPSCMPCLVAGRHLWASKSGHHMLCLIEDYDALYKQ 1750
1751 ISWGQTLLAKMDIQTQEALSPTSQKLGPKASFSVPLSKFLSSMNTAKLIL 1800
1801 EKASRLLKLFWRVSVPTNGQCSLHCDQIGEMKAEITKLHKKLFEQEKKLQ 1850
1851 NTAKLLQQSKHQEKIIFDQLVITHQVLRKARGNLELRPRAAHPGTSSPSR 1900
1901 PGS 1903
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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