 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O35134 from www.uniprot.org...
The NucPred score for your sequence is 0.81 (see score help below)
1 MLASKHTPWRRLQGISFGMYSAEELKKLSVKSITNPRYVDYLGNPSANGL 50
51 YDLALGPADSKEVCATCVQDFNNCSGHLGHIDLPLTVYNPFLFDKLYLLL 100
101 RGSCLSCHMLTCPRAAIYLLISQLRVLEVGALQAVYELERILSRFLEETG 150
151 DPSAFEIQEELEEYTSKILQNNLLGSQGTHVKNVCESRSKLVAQFWKTHM 200
201 AAKQCPHCKTGRSVVRKEHNSKLIITYPATVHKKSDQEGTELPEGVPEAP 250
251 GIDKAQMGKRGYLTPSSAQEHLFAIWKNEGFFLNYLFSGLDDIGPESSFN 300
301 PSMFFLDFIVVPPSRYRPVNRLGDQMFTNGQTVNLQAVMKDAVLIRKLLA 350
351 LMAQEQKLPCEMTELTIDKENDSSVAIDRSFLGLLPGPSLTDKLYNIWIR 400
401 LQSHVNIVFDSEMDKLMLEKYPGIRQILEKKEGLFRKHMMGKRVDYAARS 450
451 VICPDMYINTNEIGIPMVFATKLTYPQPVTPWNVQELRQAVINGPNVHPG 500
501 ASMVINEDGSRTALSSVDAAQREAVAKQLLTPATGAPKPQGTKVVCRHVK 550
551 NGDILLLNRQPTLHRPSIQAHRARILPEEKVLRLHYANCKAYNADFDGDE 600
601 MNAHFPQSELGRAEAYVLACTDQQYLVPKDGQPLAGLIQDHMVSGANMTI 650
651 RGCFFTREQYMELVYRGLTDKVGRVKLFPPAILKPFPLWTGKQVVSTLLI 700
701 NIIPEDYAPLNLSGKAKIGSKAWVKEKPRPIPDFDPDSMCESQVIIREGE 750
751 LLCGVLDKAHYGSSAYGLVHCCYEIYGGETSGRVLTCLARLFTAYLQLYR 800
801 GFTLGVEDILVKPNADVVRQRIIEESTQCGPQAVKAALSLPETASCDEIQ 850
851 GKWQDAHLSKDQRDFNMIDMKFKEEVNHYSNEINKACMPLGLHRQFPENN 900
901 LQMMVQSGAKGSTVNTMQISCLLGQIELEGRRPPLMASGKSLPCFEPYEF 950
951 TPRAGGFVTGRFLTGIRPPEFFFHCMAGREGLVDTAVKTSRSGYLQRCII 1000
1001 KHLEGLVIQYDLTVRDSDGSVVQFLYGEDGLDIPKTQFLQPKQFPFLAGN 1050
1051 YEVIMKSKHLHEVLSRADPQKVLGHIKAIKKWHHKHSGALLRKGAFLSFS 1100
1101 QKIQAAVKALNLKGSIQNGRSPETQQMLQMWYDLDEESRWKYQKRAAPCP 1150
1151 DPSLSVWRPDIYFASVSETFEKKIDDFSQEWAAQAERSYKKSELSLDRLR 1200
1201 TLLQLKWQRSLCDPGEAVGLLAAQSIGEPSTQMTLNTFHFAGRGEMNVTL 1250
1251 GIPRLREILMVASANIKTPMMSVPVFDTKKALKKVKSLKKRLTRVCLGEV 1300
1301 LQKVDIQESFCMGEKRNKFQVYELRFQFLPHAYYQQEKCLRPEDILHFME 1350
1351 TRFFKLLMEAIKKKKNKASAFRNVNSRRATQKDLNDTEDSGRSQREEERD 1400
1401 EEEEGNIVDAEAEEGDADASDTKRKEKQEEEVDYESEEEGEEEEEEEVQE 1450
1451 EGNIKGDGVHQGHEPDEEEHLGLEEEESSQKPPRRHSRPQGAEAIKRRIQ 1500
1501 AVRESYSFIEDYQYDTEESLWCQVTVKLPLMKINFDMSSLVVSLAHKAIV 1550
1551 YTTKGITRCLLNETTNSKNEKELVLNTEGINLPELFKYSEILDLRRLYSN 1600
1601 DIHAMANTYGIEAALRVIEKEIKDVFAVYGIAVDPRHLSLVADYMCFEGV 1650
1651 YKPLNRFGIQSSSSPLQQMTFETSFQFLKQATMMGSHDELKSPSACLVVG 1700
1701 KVVKGGTGLFELKQPLR 1717
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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