 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6CA87 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MSKRTQDLATTHANGSVDSATAPGASKRRRLADPVLDTPVELLASGRRTS 50
51 GRHRPVEDASRQATQQQQAPGTPGGRQQRRAAAAAKESLSTPKRAPAKPK 100
101 EKTPKATPKKTPSRRNGRRRSVKVEEVEEEEPEEEEGPEEEEAPEEEVEG 150
151 DDEEEVQVEEEAEPVSLTPLEEKKQELAKLISDNDSRVRLLFHLKQFVSL 200
201 VFYDPAEAKQDQSSVWEQVSMRESIIGTRTRLTQFQQNYDLWTKYLERKT 250
251 GGHMRSTRRQIRSKQGALEDDFVIKLKEEMTAVEEEEEEELVEEEEEEEE 300
301 EEEQEEDEEQEQQEEEEEEQEEEVTSRRGSRRSAPTKAKGKSKTASKTSK 350
351 SKSKASSKSKSKSKGKGQARASKLSKSRRYVNAVDSSSEEESDYDPNKPY 400
401 DVSKEVWEPIDTGWLLPDSEDEYYHFDDKFAQHMFPNGVKLKLNVSLKPP 450
451 RVTHPAHLLLDVAEGQTPDNRERLEGFMSSFKLLDEEMTLEEYEEHYERE 500
501 LETLDKINEMKREGVLQGLADEEEGESLTVAEIRRGFNDPERSTRPTHWD 550
551 HVVAQACHFAKLMADERKAHVSQAKRLAAAVDQHFRRLEGAEERDKKAQA 600
601 KLLKTMARKMAQDVMRRWKLAEKVVLKKKEQEAKEEERKQGKKKLKEILE 650
651 NSAQLLEARVRGDNDTPETEEGEKEEVEAVSDDAMSDVDMEDDREQVEVD 700
701 TRDDDELTVEELRAKYAALDNIKVERAEEEDEEDEENGDDEDEDEEEDDA 750
751 EIEEETETTTPALETPIDTPAEEDEFSSDTDITLDSEDESSSEQESDYEA 800
801 ETTAPGLAALMGGPKAIEEDEEEDDAFVIKEEEEEVEVEDDEEEEKADTE 850
851 VDRKVETVSEAVGEAVEEIKSNGVESKPTSNGVDVTELDRVTPERAPAVE 900
901 PPFLLRGTLRAYQQLGLEWLAGLYNNDTNGILADEMGLGKTIQTISLLSY 950
951 LACEHHIWGPHLIIVPTSVMLNWEMEFKRFAPGFKVMTYYGNPVQRREKR 1000
1001 RGWNKEDTWHVCITSYQLVLQDLFAFRRKRWHYMILDEAHNIKNFRSQRW 1050
1051 QSLLHFNTVRRLLLTGTPLQNNLMELWSLLYFLMPSSRNQMDMPGFANLK 1100
1101 DFQEWFSRPIDKMVEGGVDEEAKTTVSKLHQILRPYLLRRLKKDVEKQMP 1150
1151 AKYEHVVYCRLSKRQRYLYDDFMSRAQTRETLKTGNFLSIINCLMQLRKV 1200
1201 CNHPDLFEVRPIVTSFVQEQSVITPYERVSDRVKSLLVNTVDGGYAPSEV 1250
1251 SLSFLGFNAELEDMSTHEATSFRKYHNVQTVKNRIRELEKFCPAETPEEE 1300
1301 RYNDIEGHYKHMHHASFQQVIGSLKRVEYLHQIALAKKPVYGRNLVEVCT 1350
1351 INTSRLQPDRPEETNESSYHWQLTHLRHPTVQECANNMAPYIERFACITP 1400
1401 KAVTLNMAELSLGGIGPILQQRYFKQVTPKKSQRVVVGPPAAIADPFHQA 1450
1451 QVKLSIAFPDKRLLQYDCGKLQRLATLLQDLIAGGHRALIFTQMTKVLDV 1500
1501 LEQFLNIHGLRYMRLDGATKIEQRQLLTERFNTDPKIPVFILSTRSGGLG 1550
1551 INLTGADTVIFYDSDWNPSMDKQCQDRCHRIGQTRDVHIYRFVSEHTIES 1600
1601 NILKKANQKQILDNVVIQDGEFTTDYFNKMSVHDMLGLEPDDDAAPVADT 1650
1651 LNLSGKNLERALAQAEDADDAAAAKVATKETNLDVEDFDETQKENNKGAT 1700
1701 PGSRSTSATPMEKENTGELSSAMDSPTPVATPDVAVDNGGGDDDDSDSDE 1750
1751 SDSGIGHIDEYMIKFIEDGWFW 1772
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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