 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q13129 from www.uniprot.org...
The NucPred score for your sequence is 0.94 (see score help below)
1 MADGKGDAAAVAGAGAEAPAVAGAGDGVETESMVRGHRPVSPAPGASGLR 50
51 PCLWQLETELREQEVSEVSSLNYCRSFCQTLLQYASNKNASEHIVYLLEV 100
101 YRLAIQSFASARPYLTTECEDVLLVLGRLVLSCFELLLSVSESELPCEVW 150
151 LPFLQSLQESHDALLEFGNNNLQILVHVTKEGVWKNPVLLKILSQQPVET 200
201 EEVNKLIAQEGPSFLQMRIKHLLKSNCIPQATALSKLCAESKEISNVSSF 250
251 QQAYITCLCSMLPNEDAIKEIAKVDCKEVLDIICNLESEGQDNTAFVLCT 300
301 TYLTQQLQTASVYCSWELTLFWSKLQRRIDPSLDTFLERCRQFGVIAKTQ 350
351 QHLFCLIRVIQTEAQDAGLGVSILLCVRALQLRSSEDEEMKASVCKTIAC 400
401 LLPEDLEVRRACQLTEFLIEPSLDGFNMLEELYLQPDQKFDEENAPVPNS 450
451 LRCELLLALKAHWPFDPEFWDWKTLKRHCHQLLGQEASDSDDDLSGYEMS 500
501 INDTDVLESFLSDYDEGKEDKQYRRRDLTDQHKEKRDKKPIGSSERYQRW 550
551 LQYKFFCLLCKRECIEARILHHSKMHMEDGIYTCPVCIKKFKRKEMFVPH 600
601 VMEHVKMPPSRRDRSKKKLLLKGSQKGICPKSPSAIPEQNHSLNDQAKGE 650
651 SHEYVTFSKLEDCHLQDRDLYPCPGTDCSRVFKQFKYLSVHLKAEHQNND 700
701 ENAKHYLDMKNRREKCTYCRRHFMSAFHLREHEQVHCGPQPYMCVSIDCY 750
751 ARFGSVNELLNHKQKHDDLRYKCELNGCNIVFSDLGQLYHHEAQHFRDAS 800
801 YTCNFLGCKKFYYSKIEYQNHLSMHNVENSNGDIKKSVKLEESATGEKQD 850
851 CINQPHLLNQTDKSHLPEDLFCAESANSQIDTETAENLKENSDSNSSDQL 900
901 SHSSSASMNEELIDTLDHSETMQDVLLSNEKVFGPSSLKEKCSSMAVCFD 950
951 GTKFTCGFDGCGSTYKNARGMQKHLRKVHPYHFKPKKIKTKDLFPSLGNE 1000
1001 HNQTTEKLDAEPKPCSDTNSDSPDEGLDHNIHIKCKREHQGYSSESSICA 1050
1051 SKRPCTEDTMLELLLRLKHLSLKNSITHGSFSGSLQGYPSSGAKSLQSVS 1100
1101 SISDLNFQNQDENMPSQYLAQLAAKPFFCELQGCKYEFVTREALLMHYLK 1150
1151 KHNYSKEKVLQLTMFQHRYSPFQCHICQRSFTRKTHLRIHYKNKHQIGSD 1200
1201 RATHKLLDNEKCDHEGPCSVDRLKGDCSAELGGDPSSNSEKPHCHPKKDE 1250
1251 CSSETDLESSCEETESKTSDISSPIGSHREEQEGREGRGSRRTVAKGNLC 1300
1301 YILNKYHKPFHCIHKTCNSSFTNLKGLIRHYRTVHQYNKEQLCLEKDKAR 1350
1351 TKRELVKCKKIFACKYKECNKRFLCSKALAKHCSDSHNLDHIEEPKVLSE 1400
1401 AGSAARFSCNQPQCPAVFYTFNKLKHHLMEQHNIEGEIHSDYEIHCDLNG 1450
1451 CGQIFTHRSNYSQHVYYRHKDYYDDLFRSQKVANERLLRSEKVCQTADTQ 1500
1501 GHEHQTTRRSFNAKSKKCGLIKEKKAPISFKTRAEALHMCVEHSEHTQYP 1550
1551 CMVQGCLSVVKLESSIVRHYKRTHQMSSAYLEQQMENLVVCVKYGTKIKE 1600
1601 EPPSEADPCIKKEENRSCESERTEHSHSPGDSSAPIQNTDCCHSSERDGG 1650
1651 QKGCIESSSVFDADTLLYRGTLKCNHSSKTTSLEQCNIVQPPPPCKIENS 1700
1701 IPNPNGTESGTYFTSFQLPLPRIKESETRQHSSGQENTVKNPTHVPKENF 1750
1751 RKHSQPRSFDLKTYKPMGFESSFLKFIQESEEKEDDFDDWEPSEHLTLSN 1800
1801 SSQSSNDLTGNVVANNMVNDSEPEVDIPHSSSDSTIHENLTAIPPLIVAE 1850
1851 TTTVPSLENLRVVLDKALTDCGELALKQLHYLRPVVVLERSKFSTPILDL 1900
1901 FPTKKTDELCVGSS 1914
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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