 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9UKX3 from www.uniprot.org...
The NucPred score for your sequence is 0.96 (see score help below)
1 MSSDAEMAIFGEAAPYLRKPEKERIEAQNRPFDSKKACFVADNKEMYVKG 50
51 MIQTRENDKVIVKTLDDRMLTLNNDQVFPMNPPKFDKIEDMAMMTHLHEP 100
101 AVLYNLKERYAAWMIYTYSGLFCVTVNPYKWLPVYKPEVVAAYRGKKRQE 150
151 APPHIFSISDNAYQFMLTDRDNQSILITGESGAGKTVNTKRVIQYFATIA 200
201 VTGDKKKETQPGKMQGTLEDQIIQANPLLEAFGNAKTVRNDNSSRFGKFI 250
251 RIHFGATGKLASADIETYLLEKSRVTFQLSSERSYHIFYQIMSNKKPELI 300
301 DLLLISTNPFDFPFVSQGEVTVASIDDSEELLATDNAIDILGFSSEEKVG 350
351 IYKLTGAVMHYGNMKFKQKQREEQAEPDGTEVADKAGYLMGLNSAEMLKG 400
401 LCCPRVKVGNEYVTKGQNVQQVTNSVGALAKAVYEKMFLWMVTRINQQLD 450
451 TKQPRQYFIGVLDIAGFEIFDFNSLEQLCINFTNEKLQQFFNHHMFVLEQ 500
501 EEYKKEGIEWEFIDFGMDLAACIELIEKPMGIFSILEEECMFPKATDTSF 550
551 KNKLYDQHLGKSNNFQKPKPAKGKAEAHFSLVHYAGTVDYNIAGWLDKNK 600
601 DPLNETVVGLYQKSSLKLLSFLFSNYAGAETGDSGGSKKGGKKKGSSFQT 650
651 VSAVFRENLNKLMTNLRSTHPHFVRCLIPNETKTPGVMDHYLVMHQLRCN 700
701 GVLEGIRICRKGFPSRILYADFKQRYRILNASAIPEGQFIDSKNASEKLL 750
751 NSIDVDREQFRFGNTKVFFKAGLLGLLEEMRDEKLVTLMTSTQAVCRGYL 800
801 MRVEFKKMMERRDSIFCIQYNIRSFMNVKHWPWMNLFFKIKPLLKSAEAE 850
851 KEMATMKEDFERTKEELARSEARRKELEEKMVSLLQEKNDLQLQVQSETE 900
901 NLMDAEERCEGLIKSKILLEAKVKELTERLEEEEEMNSELVAKKRNLEDK 950
951 CSSLKRDIDDLELTLTKVEKEKHATENKVKNLSEEMTALEENISKLTKEK 1000
1001 KSLQEAHQQTLDDLQVEEDKVNGLIKINAKLEQQTDDLEGSLEQEKKLRA 1050
1051 DLERAKRKLEGDLKMSQESIMDLENDKQQIEEKLKKKEFELSQLQAKIDD 1100
1101 EQVHSLQFQKKIKELQARIEELEEEIEAEHTLRAKIEKQRSDLARELEEI 1150
1151 SERLEEASGATSAQIEMNKKREAEFQKMRRDLEEATLQHEATAATLRKKQ 1200
1201 ADSVAELGEQIDNLQRVKQKLEKEKSELKMEIDDMASNIEALSKSKSNIE 1250
1251 RTCRTVEDQFSEIKAKDEQQTQLIHDLNMQKARLQTQNGELSHRVEEKES 1300
1301 LISQLTKSKQALTQQLEELKRQMEEETKAKNAMAHALQSSRHDCDLLREQ 1350
1351 YEEEQEAKAELQRALSKANSEVAQWRTKYETDAIQRTEELEEAKKKLAQR 1400
1401 LQEAEENTETANSKCASLEKTKQRLQGEVEDLMRDLERSHTACATLDKKQ 1450
1451 RNFDKVLAEWKQKLDESQAELEAAQKESRSLSTELFKMRNAYEEVVDQLE 1500
1501 TLRRENKNLQEEISDLTEQIAETGKNLQEAEKTKKLVEQEKSDLQVALEE 1550
1551 VEGSLEHEESKILRVQLELSQVKSELDRKVIEKDEEIEQLKRNSQRAAEA 1600
1601 LQSVLDAEIRSRNDALRLKKKMEGDLNEMEIQLGHSNRQMAETQKHLRTV 1650
1651 QGQLKDSQLHLDDALRSNEDLKEQLAIVERRNGLLLEELEEMKVALEQTE 1700
1701 RTRRLSEQELLDASDRVQLLHSQNTSLINTKKKLEADIAQCQAEVENSIQ 1750
1751 ESRNAEEKAKKAITDAAMMAEELKKEQDTSAHLERMKKNLEQTVKDLQHR 1800
1801 LDEAEQLALKGGKKQIQKLENRVRELENELDVEQKRGAEALKGAHKYERK 1850
1851 VKEMTYQAEEDHKNILRLQDLVDKLQAKVKSYKRQAEEAEEQANTQLSRC 1900
1901 RRVQHELEEAAERADIAESQVNKLRAKSRDVGSQKMEE 1938
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.) |
Go back to the NucPred Home Page.