 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q16363 from www.uniprot.org...
The NucPred score for your sequence is 0.52 (see score help below)
1 MALSSAWRSVLPLWLLWSAACSRAASGDDNAFPFDIEGSSAVGRQDPPET 50
51 SEPRVALGRLPPAAEKCNAGFFHTLSGECVPCDCNGNSNECLDGSGYCVH 100
101 CQRNTTGEHCEKCLDGYIGDSIRGAPQFCQPCPCPLPHLANFAESCYRKN 150
151 GAVRCICNENYAGPNCERCAPGYYGNPLLIGSTCKKCDCSGNSDPNLIFE 200
201 DCDEVTGQCRNCLRNTTGFKCERCAPGYYGDARIAKNCAVCNCGGGPCDS 250
251 VTGECLEEGFEPPTGMDCPTISCDKCVWDLTDDLRLAALSIEEGKSGVLS 300
301 VSSGAAAHRHVNEINATIYLLKTKLSERENQYALRKIQINNAENTMKSLL 350
351 SDVEELVEKENQASRKGQLVQKESMDTINHASQLVEQAHDMRDKIQEINN 400
401 KMLYYGEEHELSPKEISEKLVLAQKMLEEIRSRQPFFTQRELVDEEADEA 450
451 YELLSQAESWQRLHNETRTLFPVVLEQLDDYNAKLSDLQEALDQALNYVR 500
501 DAEDMNRATAARQRDHEKQQERVREQMEVVNMSLSTSADSLTTPRLTLSE 550
551 LDDIIKNASGIYAEIDGAKSELQVKLSNLSNLSHDLVQEAIDHAQDLQQE 600
601 ANELSRKLHSSDMNGLVQKALDASNVYENIVNYVSEANETAEFALNTTDR 650
651 IYDAVSGIDTQIIYHKDESENLLNQARELQAKAESSSDEAVADTSRRVGG 700
701 ALARKSALKTRLSDAVKQLQAAERGDAQQRLGQSRLITEEANRTTMEVQQ 750
751 ATAPMANNLTNWSQNLQHFDSSAYNTAVNSARDAVRNLTEVVPQLLDQLR 800
801 TVEQKRPASNVSASIQRIRELIAQTRSVASKIQVSMMFDGQSAVEVHSRT 850
851 SMDDLKAFTSLSLYMKPPVKRPELTETADQFILYLGSKNAKKEYMGLAIK 900
901 NDNLVYVYNLGTKDVEIPLDSKPVSSWPAYFSIVKIERVGKHGKVFLTVP 950
951 SLSSTAEEKFIKKGEFSGDDSLLDLDPEDTVFYVGGVPSNFKLPTSLNLP 1000
1001 GFVGCLELATLNNDVISLYNFKHIYNMDPSTSVPCARDKLAFTQSRAASY 1050
1051 FFDGSGYAVVRDITRRGKFGQVTRFDIEVRTPADNGLILLMVNGSMFFRL 1100
1101 EMRNGYLHVFYDFGFSGGPVHLEDTLKKAQINDAKYHEISIIYHNDKKMI 1150
1151 LVVDRRHVKSMDNEKMKIPFTDIYIGGAPPEILQSRALRAHLPLDINFRG 1200
1201 CMKGFQFQKKDFNLLEQTETLGVGYGCPEDSLISRRAYFNGQSFIASIQK 1250
1251 ISFFDGFEGGFNFRTLQPNGLLFYYASGSDVFSISLDNGTVIMDVKGIKV 1300
1301 QSVDKQYNDGLSHFVISSVSPTRYELIVDKSRVGSKNPTKGKIEQTQASE 1350
1351 KKFYFGGSPISAQYANFTGCISNAYFTRVDRDVEVEDFQRYTEKVHTSLY 1400
1401 ECPIESSPLFLLHKKGKNLSKPKASQNKKGGKSKDAPSWDPVALKLPERN 1450
1451 TPRNSHCHLSNSPRAIEHAYQYGGTANSRQEFEHLKGDFGAKSQFSIRLR 1500
1501 TRSSHGMIFYVSDQEENDFMTLFLAHGRLVYMFNVGHKKLKIRSQEKYND 1550
1551 GLWHDVIFIRERSSGRLVIDGLRVLEESLPPTEATWKIKGPIYLGGVAPG 1600
1601 KAVKNVQINSIYSFSGCLSNLQLNGASITSASQTFSVTPCFEGPMETGTY 1650
1651 FSTEGGYVVLDESFNIGLKFEIAFEVRPRSSSGTLVHGHSVNGEYLNVHM 1700
1701 KNGQVIVKVNNGIRDFSTSVTPKQSLCDGRWHRITVIRDSNVVQLDVDSE 1750
1751 VNHVVGPLNPKPIDHREPVFVGGVPESLLTPRLAPSKPFTGCIRHFVIDG 1800
1801 HPVSFSKAALVSGAVSINSCPAA 1823
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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