 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O54889 from www.uniprot.org...
The NucPred score for your sequence is 0.83 (see score help below)
1 MLASKHTPWRRLQGISFGMYSAEELKKLSVKSITNPRYVDSLGNPSADGL 50
51 YDLALGPADSKEVCSTCVQDFNNCSGHLGHIDLPLTVYNPLLFDKLYLLL 100
101 RGSCLNCHMLTCPRAAIHLLVCQLKVLDVGALQAVYELERILSRFLEETS 150
151 DPSAFEIQEELEEYTSKILQNNLLGSQGAHVKNVCESRSKLVAHFWKTHM 200
201 AAKRCPHCKTGRSVVRKEHNSKLTITYPAMVHKKSGQKDAELPEGAPAAP 250
251 GIDEAQMGKRGYLTPSSAQEHLFAIWKNEGFFLNYLFSGLDDIGPESSFN 300
301 PSMFFLDFIVVPPSRYRPINRLGDQMFTNGQTVNLQAVMKDAVLIRKLLA 350
351 VMAQEQKLPCEMTEITIDKENDSSGAIDRSFLSLLPGQSLTDKLYNIWIR 400
401 LQSHVNIVFDSDMDKLMLEKYPGIRQILEKKEGLFRKHMMGKRVDYAARS 450
451 VICPDMYINTNEIGIPMVFATKLTYPQPVTPWNVQELRQAVINGPNVHPG 500
501 ASMVINEDGSRTALSAVDATQREAVAKQLLTPSTGIPKPQGAKVVCRHVK 550
551 NGDILLLNRQPTLHRPSIQAHRAHILPEEKVLRLHYANCKAYNADFDGDE 600
601 MNAHFPQSELGRAEAYVLACTDQQYLVPKDGQPLAGLIQDHMVSGANMTI 650
651 RGCFFTREQYMELVYRGLTDKVGRVKLFPPAILKPFPLWTGKQVVSTLLI 700
701 NIIPEDYTPLNLTGKAKIGSKAWVKEKPRPVPDFDPDSMCESQVIIREGE 750
751 LLCGVLDKAHYGSSAYGLVHCCYEIYGGETSGRVLTCLARLFTAYLQLYR 800
801 GFTLGVEDILVKPNADVMRQRIIEESTQCGPRAVRAALNLPEAASCDEIQ 850
851 GKWQDAIWRKDQRDFNMIDMKFKEEVNHYSNEINKACMPFGLHRQFPENN 900
901 LQMMVQSGAKGSTVNTMQISCLLGQIELEGRRPPLMASGKSLPCFEPYEF 950
951 TPRAGGFVTGRFLTGIRPPEFFFHCMAGREGLVDTAVKTSRSGYLQRCII 1000
1001 KHLEGLVIQYDLTVRDSDGSVVQFLYGEDGLDIPKTQFLQPKQFPFLASN 1050
1051 YEVIMKSKHLHEVLSRADPQKVLRHFRAIKKWHHRHSSALLRKGAFLSFS 1100
1101 QKIQAAVKALNLEGKTQNGRSPETQQMLQMWHELDEQSRRKYQKRAAPCP 1150
1151 DPSLSVWRPDIHFASVSETFEKKIDDYSQEWAAQAEKSHNRSELSLDRLR 1200
1201 TLLQLKWQRSLCDPGEAVGLLAAQSIGEPSTQMTLNTFHFAGRGEMNVTL 1250
1251 GIPRLREILMVASANIKTPMMSVPVFNTKKALRRVKSLKKQLTRVCLGEV 1300
1301 LQKVDIQESFCMGEKQNKFRVYELRFQFLPHAYYQQEKCLRPEDILHFME 1350
1351 TRFFKLLMEAIKKKNSKASAFRSVNTRRATQKDLDDTEDSGRNRREEERD 1400
1401 EEEEGNIVDAEAEEGDADASDTKRKEKQEEEVDYESEEEGEEEEEEDVQE 1450
1451 EENIKGEGAHQTHEPDEEEGSGLEEESSQNPPCRHSRPQGAEAMERRIQA 1500
1501 VRESHSFIEDYQYDTEESLWCQVTVKLPLMKINFDMSSLVVSLAHNAIVY 1550
1551 TTKGITRCLLNETINSKNEKEFVLNTEGINLPELFKYSEVLDLRRLYSND 1600
1601 IHAVANTYGIEAALRVIEKEIKDVFAVYGIAVDPRHLSLVADYMCFEGVY 1650
1651 KPLNRFGIQSSSSPLQQMTFETSFQFLKQATMMGSHDELKSPSACLVVGK 1700
1701 VVKGGTGLFELKQPLR 1716
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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