 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9NQX4 from www.uniprot.org...
The NucPred score for your sequence is 0.90 (see score help below)
1 MAVAELYTQYNRVWIPDPEEVWKSAEIAKDYRVGDKVLRLLLEDGTELDY 50
51 SVNPESLPPLRNPDILVGENDLTALSYLHEPAVLHNLRIRFAESKLIYTY 100
101 SGIILVAMNPYKQLPIYGDAIIHAYSGQNMGDMDPHIFAVAEEAYKQMAR 150
151 NNRNQSIIVSGESGAGKTVSARYAMRYFATVSKSGSNAHVEDKVLASNPI 200
201 TEAVGNAKTTRNDNSSRFGKYTEISFDEQNQIIGANMSTYLLEKSRVVFQ 250
251 SENERNYHIFYQLCASAQQSEFKHLKLGSAEEFNYTRMGGNTVIEGVNDR 300
301 AEMVETQKTFTLLGFKEDFQMDVFKILAAILHLGNVQITAVGNERSSVSE 350
351 DDSHLKVFCELLGLESGRVAQWLCNRKIVTSSETVVKPMTRPQAVNARDA 400
401 LAKKIYAHLFDFIVERINQALQFSGKQHTFIGVLDIYGFETFDVNSFEQF 450
451 CINYANEKLQQQFNMHVFKLEQEEYMKEDIPWTLIDFYDNQPVIDLIEAK 500
501 MGILELLDEECLLPHGTDENWLQKLYNNFVNRNPLFEKPRMSNTSFVIQH 550
551 FADKVEYKCEGFLEKNRDTVYDMLVEILRASKFHLCANFFQENPTPPSPF 600
601 GSMITVKSAKQVIKPNSKHFRTTVGSKFRSSLYLLMETLNATTPHYVRCI 650
651 KPNDEKLPFEFDSKRIVQQLRACGVLETIRISAQSYPSRWTYIEFYSRYG 700
701 ILMTKQELSFSDKKEVCKVVLHRLIQDSNQYQFGKTKIFFRAGQVAYLEK 750
751 LRLDKLRQSCVMVQKHMRGWLQRKKFLRERRAALIIQQYFRGQQTVRKAI 800
801 TAVALKEAWAAIIIQKHCRGYLVRSLYQLIRMATITMQAYSRGFLARRRY 850
851 RKMLEEHKAVILQKYARAWLARRRFQSIRRFVLNIQLTYRVQRLQKKLED 900
901 QNKENHGLVEKLTSLAALRAGDVEKIQKLEAELEKAATHRRNYEEKGKRY 950
951 RDAVEEKLAKLQKHNSELETQKEQIQLKLQEKTEELKEKMDNLTKQLFDD 1000
1001 VQKEERQRMLLEKSFELKTQDYEKQIQSLKEEIKALKDEKMQLQHLVEGE 1050
1051 HVTSDGLKAEVARLSKQVKTISEFEKEIELLQAQKIDVEKHVQSQKREMR 1100
1101 EKMSEITKQLLESYDIEDVRSRLSVEDLEHLNEDGELWFAYEGLKKATRV 1150
1151 LESHFQSQKDCYEKEIEALNFKVVHLSQEINHLQKLFREENDINESIRHE 1200
1201 VTRLTSENMMIPDFKQQISELEKQKQDLEIRLNEQAEKMKGKLEELSNQL 1250
1251 HRSQEEEGTQRKALEAQNEIHTKEKEKLIDKIQEMQEASDHLKKQFETES 1300
1301 EVKCNFRQEASRLTLENRDLEEELDMKDRVIKKLQDQVKTLSKTIGKAND 1350
1351 VHSSSGPKEYLGMLQYKREDEAKLIQNLILDLKPRGVVVNMIPGLPAHIL 1400
1401 FMCVRYADSLNDANMLKSLMNSTINGIKQVVKEHLEDFEMLSFWLSNTCH 1450
1451 FLNCLKQYSGEEEFMKHNSPQQNKNCLNNFDLSEYRQILSDVAIRIYHQF 1500
1501 IIIMEKNIQPIIVPGMLEYESLQGISGLKPTGFRKRSSSIDDTDGYTMTS 1550
1551 VLQQLSYFYTTMCQNGLDPELVRQAVKQLFFLIGAVTLNSLFLRKDMCSC 1600
1601 RKGMQIRCNISYLEEWLKDKNLQNSLAKETLEPLSQAAWLLQVKKTTDSD 1650
1651 AKEIYERCTSLSAVQIIKILNSYTPIDDFEKRVTPSFVRKVQALLNSRED 1700
1701 SSQLMLDTKYLFQVTFPFTPSPHALEMIQIPSSFKLGFLNRL 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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