 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q06409 from www.uniprot.org...
The NucPred score for your sequence is 0.58 (see score help below)
1 MSQQDSQRWLPTDRLIYGVLVKSFLPLQRYPELVYENSNYANVYVGAEVY 50
51 VFEESVDKKWCRAYQCLRPFPEEFISNMNSANDVLPDVKPKVVIFPRKYV 100
101 HFEAEKAVSTMPFFKAPSAEDFKPLISKECESRSFCDSLYVSSTDDISTG 150
151 KPRKTPRPPFPFFRYQKRSFKDEMGPILSLISSHVYSMYSIGEFSIYRKM 200
201 IKLYYDLDTIRFRLSMNLTTEAEKINLIRAATSLRTKIAKFLSSTYRKNK 250
251 LIANSTPRNPDPYGFEGIFARDIDTGELLSYEIDKLRTLVSSSMLCGLTN 300
301 NFPTVPVVESDDESSSNGLFGTVRSSILVNLKDLAWDPSISDPKYQDLSI 350
351 CVYLRTKDEVLTESFTMTKSSNMESALDEIPAMLFKNILETIVHKNKVYL 400
401 VVVLKETIAITTETAPEISSYNISTEESSSHSPFSPFNSSTENKIDHVKK 450
451 GLAAGVINISPVFKFYNGLSVANKAQRFNLYLYSSDSSDSQNFNSSKDAD 500
501 LGWGGLINKIIKDSSEGVSVNPRAVSLSVTVKEIIGKQEAEKVLSTSLVP 550
551 IRSIPTYFYDTMFSQAERIYLNLGRVSLYGLPAADTNIENVTVQISCRNK 600
601 AVKFCKNKLEERSGDWKFVSVRPNESIGESIRIEGVENMNEDETLRVLVY 650
651 LNGFLMAKSNIHIKKKNEIIEYRKGTVFQIMSSKSVPLIHLELEASYFGR 700
701 RYNINPAITNFLVLQTKNVEFDQQLKEHYSVTLKQLNNVSFKDLLKHFDT 750
751 ILAHYLLLLESVNEATDKKGPSSSLPNIVFSEFVKFLNLMLTHQENSRYW 800
801 FNRLYKKVMSKELECPNVAPILIKHMTTIFDRSHSSWTRTGTAICRTILY 850
851 IIVLAIGSSHSDEMPNFSHFFRSLHKFLMLADEPIMADQILLIESIPSML 900
901 ETMTNHCKVEDLVRFAIGLFECCQEKEMNQKMYSRPLSVREEEYLNTKFN 950
951 CLLKLINKKVLQNYLTNTESVDKLRLQFLSKTLEWLLTPYTPGDDKCFHV 1000
1001 ESLRLVNSVFITIIEDYKFDMLQRNLIRLLPYLCKSFVHLRRYCKKARLM 1050
1051 RPRRVFTMLFPREIPCNYIPVDSIVNDEVVVEVLLELAIIICEITKIASS 1100
1101 RFPSYQSFSEIINLCDKDTLFQSNFYSRQITNENVYTITKTVFLFFKQDW 1150
1151 FPGMKWLGVSALLGRSSLILLSLCKDYIIENNSPSPSKESEKRVDMRLWA 1200
1201 EYVKVILLVSNHKSASLTKLAITPRKAVYLISGDLKKISAYILNECWDAL 1250
1251 ATGHYNITYAKKYGLGALSDCQFELFVHNQFLIREIFIFAFHRHIDATRI 1300
1301 CCKILWGLGLNFWRIFGSLQPAVNACIPELFSAYQIGKLRLNDYELERFV 1350
1351 SCLFFMMHVPDSDTFFPACMDFLRDLLGFLHIVNEIYKIPNQEEFDDDRT 1400
1401 ARHIEMFEYLLEANRPELFHKMIYDLFIHFIQKKDFVQAALSLELLAGTY 1450
1451 AWDSNDTLEAISFPPLPEQSSFERKEYLLKESARNFSRGQKPEKALAVYK 1500
1501 DLIKAYDEINYDLNGLAFVHDQIAGIYTRLQSIDRLVPTYFKVSFMGFGF 1550
1551 PKSLRNKSFVFEGLPFEHITSMHDRLLRSYHGSNIVHSQEEVDMLLMNPP 1600
1601 MGKYIHVASVEPCLSISDNYNSSDKKSSINNKVRMYIENRDLRTFSNSRR 1650
1651 LPGAKGVTDLWVEEYTYHTMNTFPTLMNRSEIVKVTKSKLSPLENAIRSL 1700
1701 QVKIQELYGLENMCNKTLKDHGDVNDLFTELSTNITGTISAPVNGGISQY 1750
1751 KAFLEPSTSKQFSTDDLGRLTLAFDELVAVLGRCLTLHAELLPSKDLKPS 1800
1801 HDLLVRLFEENFAEEIERYSRTLSEANRSRNNMITARIISHKNPNKKASF 1850
1851 SGRDHHTSGSNHSQFVLEHSDSFGPNSLLFGKYLTRTLSHSSTTSSLDKS 1900
1901 GIVSGTSSTFLAGSQPNTNTDSQHKHDYSHSG 1932
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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