SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching P28827 from www.uniprot.org...

The NucPred score for your sequence is 0.62 (see score help below)

   1  MRGLGTCLATLAGLLLTAAGETFSGGCLFDEPYSTCGYSQSEGDDFNWEQ    50
  51  VNTLTKPTSDPWMPSGSFMLVNASGRPEGQRAHLLLPQLKENDTHCIDFH   100
 101  YFVSSKSNSPPGLLNVYVKVNNGPLGNPIWNISGDPTRTWNRAELAISTF   150
 151  WPNFYQVIFEVITSGHQGYLAIDEVKVLGHPCTRTPHFLRIQNVEVNAGQ   200
 201  FATFQCSAIGRTVAGDRLWLQGIDVRDAPLKEIKVTSSRRFIASFNVVNT   250
 251  TKRDAGKYRCMIRTEGGVGISNYAELVVKEPPVPIAPPQLASVGATYLWI   300
 301  QLNANSINGDGPIVAREVEYCTASGSWNDRQPVDSTSYKIGHLDPDTEYE   350
 351  ISVLLTRPGEGGTGSPGPALRTRTKCADPMRGPRKLEVVEVKSRQITIRW   400
 401  EPFGYNVTRCHSYNLTVHYCYQVGGQEQVREEVSWDTENSHPQHTITNLS   450
 451  PYTNVSVKLILMNPEGRKESQELIVQTDEDLPGAVPTESIQGSTFEEKIF   500
 501  LQWREPTQTYGVITLYEITYKAVSSFDPEIDLSNQSGRVSKLGNETHFLF   550
 551  FGLYPGTTYSFTIRASTAKGFGPPATNQFTTKISAPSMPAYELETPLNQT   600
 601  DNTVTVMLKPAHSRGAPVSVYQIVVEEERPRRTKKTTEILKCYPVPIHFQ   650
 651  NASLLNSQYYFAAEFPADSLQAAQPFTIGDNKTYNGYWNTPLLPYKSYRI   700
 701  YFQAASRANGETKIDCVQVATKGAATPKPVPEPEKQTDHTVKIAGVIAGI   750
 751  LLFVIIFLGVVLVMKKRKLAKKRKETMSSTRQEMTVMVNSMDKSYAEQGT   800
 801  NCDEAFSFMDTHNLNGRSVSSPSSFTMKTNTLSTSVPNSYYPDETHTMAS   850
 851  DTSSLVQSHTYKKREPADVPYQTGQLHPAIRVADLLQHITQMKCAEGYGF   900
 901  KEEYESFFEGQSAPWDSAKKDENRMKNRYGNIIAYDHSRVRLQTIEGDTN   950
 951  SDYINGNYIDGYHRPNHYIATQGPMQETIYDFWRMVWHENTASIIMVTNL  1000
1001  VEVGRVKCCKYWPDDTEIYKDIKVTLIETELLAEYVIRTFAVEKRGVHEI  1050
1051  REIRQFHFTGWPDHGVPYHATGLLGFVRQVKSKSPPSAGPLVVHCSAGAG  1100
1101  RTGCFIVIDIMLDMAEREGVVDIYNCVRELRSRRVNMVQTEEQYVFIHDA  1150
1151  ILEACLCGDTSVPASQVRSLYYDMNKLDPQTNSSQIKEEFRTLNMVTPTL  1200
1201  RVEDCSIALLPRNHEKNRCMDILPPDRCLPFLITIDGESSNYINAALMDS  1250
1251  YKQPSAFIVTQHPLPNTVKDFWRLVLDYHCTSVVMLNDVDPAQLCPQYWP  1300
1301  ENGVHRHGPIQVEFVSADLEEDIISRIFRIYNAARPQDGYRMVQQFQFLG  1350
1351  WPMYRDTPVSKRSFLKLIRQVDKWQEEYNGGEGRTVVHCLNGGGRSGTFC  1400
1401  AISIVCEMLRHQRTVDVFHAVKTLRNNKPNMVDLLDQYKFCYEVALEYLN  1450
1451  SG                                                  1452

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

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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