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

NucPred

Fetching O15440 from www.uniprot.org...

The NucPred score for your sequence is 0.46 (see score help below)

   1  MKDIDIGKEYIIPSPGYRSVRERTSTSGTHRDREDSKFRRTRPLECQDAL    50
  51  ETAARAEGLSLDASMHSQLRILDEEHPKGKYHHGLSALKPIRTTSKHQHP   100
 101  VDNAGLFSCMTFSWLSSLARVAHKKGELSMEDVWSLSKHESSDVNCRRLE   150
 151  RLWQEELNEVGPDAASLRRVVWIFCRTRLILSIVCLMITQLAGFSGPAFM   200
 201  VKHLLEYTQATESNLQYSLLLVLGLLLTEIVRSWSLALTWALNYRTGVRL   250
 251  RGAILTMAFKKILKLKNIKEKSLGELINICSNDGQRMFEAAAVGSLLAGG   300
 301  PVVAILGMIYNVIILGPTGFLGSAVFILFYPAMMFASRLTAYFRRKCVAA   350
 351  TDERVQKMNEVLTYIKFIKMYAWVKAFSQSVQKIREEERRILEKAGYFQS   400
 401  ITVGVAPIVVVIASVVTFSVHMTLGFDLTAAQAFTVVTVFNSMTFALKVT   450
 451  PFSVKSLSEASVAVDRFKSLFLMEEVHMIKNKPASPHIKIEMKNATLAWD   500
 501  SSHSSIQNSPKLTPKMKKDKRASRGKKEKVRQLQRTEHQAVLAEQKGHLL   550
 551  LDSDERPSPEEEEGKHIHLGHLRLQRTLHSIDLEIQEGKLVGICGSVGSG   600
 601  KTSLISAILGQMTLLEGSIAISGTFAYVAQQAWILNATLRDNILFGKEYD   650
 651  EERYNSVLNSCCLRPDLAILPSSDLTEIGERGANLSGGQRQRISLARALY   700
 701  SDRSIYILDDPLSALDAHVGNHIFNSAIRKHLKSKTVLFVTHQLQYLVDC   750
 751  DEVIFMKEGCITERGTHEELMNLNGDYATIFNNLLLGETPPVEINSKKET   800
 801  SGSQKKSQDKGPKTGSVKKEKAVKPEEGQLVQLEEKGQGSVPWSVYGVYI   850
 851  QAAGGPLAFLVIMALFMLNVGSTAFSTWWLSYWIKQGSGNTTVTRGNETS   900
 901  VSDSMKDNPHMQYYASIYALSMAVMLILKAIRGVVFVKGTLRASSRLHDE   950
 951  LFRRILRSPMKFFDTTPTGRILNRFSKDMDEVDVRLPFQAEMFIQNVILV  1000
1001  FFCVGMIAGVFPWFLVAVGPLVILFSVLHIVSRVLIRELKRLDNITQSPF  1050
1051  LSHITSSIQGLATIHAYNKGQEFLHRYQELLDDNQAPFFLFTCAMRWLAV  1100
1101  RLDLISIALITTTGLMIVLMHGQIPPAYAGLAISYAVQLTGLFQFTVRLA  1150
1151  SETEARFTSVERINHYIKTLSLEAPARIKNKAPSPDWPQEGEVTFENAEM  1200
1201  RYRENLPLVLKKVSFTIKPKEKIGIVGRTGSGKSSLGMALFRLVELSGGC  1250
1251  IKIDGVRISDIGLADLRSKLSIIPQEPVLFSGTVRSNLDPFNQYTEDQIW  1300
1301  DALERTHMKECIAQLPLKLESEVMENGDNFSVGERQLLCIARALLRHCKI  1350
1351  LILDEATAAMDTETDLLIQETIREAFADCTMLTIAHRLHTVLGSDRIMVL  1400
1401  AQGQVVEFDTPSVLLSNDSSRFYAMFAAAENKVAVKG               1437

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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