 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9P2N4 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 MQFVSWATLLTLLVRDLAEMGSPDAAAAVRKDRLHPRQVKLLETLSEYEI 50
51 VSPIRVNALGEPFPTNVHFKRTRRSINSATDPWPAFASSSSSSTSSQAHY 100
101 RLSAFGQQFLFNLTANAGFIAPLFTVTLLGTPGVNQTKFYSEEEAELKHC 150
151 FYKGYVNTNSEHTAVISLCSGMLGTFRSHDGDYFIEPLQSMDEQEDEEEQ 200
201 NKPHIIYRRSAPQREPSTGRHACDTSEHKNRHSKDKKKTRARKWGERINL 250
251 AGDVAALNSGLATEAFSAYGNKTDNTREKRTHRRTKRFLSYPRFVEVLVV 300
301 ADNRMVSYHGENLQHYILTLMSIVASIYKDPSIGNLINIVIVNLIVIHNE 350
351 QDGPSISFNAQTTLKNFCQWQHSKNSPGGIHHDTAVLLTRQDICRAHDKC 400
401 DTLGLAELGTICDPYRSCSISEDSGLSTAFTIAHELGHVFNMPHDDNNKC 450
451 KEEGVKSPQHVMAPTLNFYTNPWMWSKCSRKYITEFLDTGYGECLLNEPE 500
501 SRPYPLPVQLPGILYNVNKQCELIFGPGSQVCPYMMQCRRLWCNNVNGVH 550
551 KGCRTQHTPWADGTECEPGKHCKYGFCVPKEMDVPVTDGSWGSWSPFGTC 600
601 SRTCGGGIKTAIRECNRPEPKNGGKYCVGRRMKFKSCNTEPCLKQKRDFR 650
651 DEQCAHFDGKHFNINGLLPNVRWVPKYSGILMKDRCKLFCRVAGNTAYYQ 700
701 LRDRVIDGTPCGQDTNDICVQGLCRQAGCDHVLNSKARRDKCGVCGGDNS 750
751 SCKTVAGTFNTVHYGYNTVVRIPAGATNIDVRQHSFSGETDDDNYLALSS 800
801 SKGEFLLNGNFVVTMAKREIRIGNAVVEYSGSETAVERINSTDRIEQELL 850
851 LQVLSVGKLYNPDVRYSFNIPIEDKPQQFYWNSHGPWQACSKPCQGERKR 900
901 KLVCTRESDQLTVSDQRCDRLPQPGHITEPCGTDCDLRWHVASRSECSAQ 950
951 CGLGYRTLDIYCAKYSRLDGKTEKVDDGFCSSHPKPSNREKCSGECNTGG 1000
1001 WRYSAWTECSKSCDGGTQRRRAICVNTRNDVLDDSKCTHQEKVTIQRCSE 1050
1051 FPCPQWKSGDWSECLVTCGKGHKHRQVWCQFGEDRLNDRMCDPETKPTSM 1100
1101 QTCQQPECASWQAGPWGQCSVTCGQGYQLRAVKCIIGTYMSVVDDNDCNA 1150
1151 ATRPTDTQDCELPSCHPPPAAPETRRSTYSAPRTQWRFGSWTPCSATCGK 1200
1201 GTRMRYVSCRDENGSVADESACATLPRPVAKEECSVTPCGQWKALDWSSC 1250
1251 SVTCGQGRATRQVMCVNYSDHVIDRSECDQDYIPETDQDCSMSPCPQRTP 1300
1301 DSGLAQHPFQNEDYRPRSASPSRTHVLGGNQWRTGPWGACSSTCAGGSQR 1350
1351 RVVVCQDENGYTANDCVERIKPDEQRACESGPCPQWAYGNWGECTKLCGG 1400
1401 GIRTRLVVCQRSNGERFPDLSCEILDKPPDREQCNTHACPHDAAWSTGPW 1450
1451 SSCSVSCGRGHKQRNVYCMAKDGSHLESDYCKHLAKPHGHRKCRGGRCPK 1500
1501 WKAGAWSQCSVSCGRGVQQRHVGCQIGTHKIARETECNPYTRPESERDCQ 1550
1551 GPRCPLYTWRAEEWQECTKTCGEGSRYRKVVCVDDNKNEVHGARCDVSKR 1600
1601 PVDRESCSLQPCEYVWITGEWSECSVTCGKGYKQRLVSCSEIYTGKENYE 1650
1651 YSYQTTINCPGTQPPSVHPCYLRDCPVSATWRVGNWGSCSVSCGVGVMQR 1700
1701 SVQCLTNEDQPSHLCHTDLKPEERKTCRNVYNCELPQNCKEVKRLKGASE 1750
1751 DGEYFLMIRGKLLKIFCAGMHSDHPKEYVTLVHGDSENFSEVYGHRLHNP 1800
1801 TECPYNGSRRDDCQCRKDYTAAGFSSFQKIRIDLTSMQIITTDLQFARTS 1850
1851 EGHPVPFATAGDCYSAAKCPQGRFSINLYGTGLSLTESARWISQGNYAVS 1900
1901 DIKKSPDGTRVVGKCGGYCGKCTPSSGTGLEVRVL 1935
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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