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

NucPred

Fetching P04146 from www.uniprot.org...

The NucPred score for your sequence is 0.84 (see score help below)

   1  MDKAKRNIKPFDGEKYAIWKFRIRALLAEQDVLKVVDGLMPNEVDDSWKK    50
  51  AERCAKSTIIEYLSDSFLNFATSDITARQILENLDAVYERKSLASQLALR   100
 101  KRLLSLKLSSEMSLLSHFHIFDELISELLAAGAKIEEMDKISHLLITLPS   150
 151  CYDGIITAIETLSEENLTLAFVKNRLLDQEIKIKNDHNDTSKKVMNAIVH   200
 201  NNNNTYKNNLFKNRVTKPKKIFKGNSKYKVKCHHCGREGHIKKDCFHYKR   250
 251  ILNNKNKENEKQVQTATSHGIAFMVKEVNNTSVMDNCGFVLDSGASDHLI   300
 301  NDESLYTDSVEVVPPLKIAVAKQGEFIYATKRGIVRLRNDHEITLEDVLF   350
 351  CKEAAGNLMSVKRLQEAGMSIEFDKSGVTISKNGLMVVKNSGMLNNVPVI   400
 401  NFQAYSINAKHKNNFRLWHERFGHISDGKLLEIKRKNMFSDQSLLNNLEL   450
 451  SCEICEPCLNGKQARLPFKQLKDKTHIKRPLFVVHSDVCGPITPVTLDDK   500
 501  NYFVIFVDQFTHYCVTYLIKYKSDVFSMFQDFVAKSEAHFNLKVVYLYID   550
 551  NGREYLSNEMRQFCVKKGISYHLTVPHTPQLNGVSERMIRTITEKARTMV   600
 601  SGAKLDKSFWGEAVLTATYLINRIPSRALVDSSKTPYEMWHNKKPYLKHL   650
 651  RVFGATVYVHIKNKQGKFDDKSFKSIFVGYEPNGFKLWDAVNEKFIVARD   700
 701  VVVDETNMVNSRAVKFETVFLKDSKESENKNFPNDSRKIIQTEFPNESKE   750
 751  CDNIQFLKDSKESENKNFPNDSRKIIQTEFPNESKECDNIQFLKDSKESN   800
 801  KYFLNESKKRKRDDHLNESKGSGNPNESRESETAEHLKEIGIDNPTKNDG   850
 851  IEIINRRSERLKTKPQISYNEEDNSLNKVVLNAHTIFNDVPNSFDEIQYR   900
 901  DDKSSWEEAINTELNAHKINNTWTITKRPENKNIVDSRWVFSVKYNELGN   950
 951  PIRYKARLVARGFTQKYQIDYEETFAPVARISSFRFILSLVIQYNLKVHQ  1000
1001  MDVKTAFLNGTLKEEIYMRLPQGISCNSDNVCKLNKAIYGLKQAARCWFE  1050
1051  VFEQALKECEFVNSSVDRCIYILDKGNINENIYVLLYVDDVVIATGDMTR  1100
1101  MNNFKRYLMEKFRMTDLNEIKHFIGIRIEMQEDKIYLSQSAYVKKILSKF  1150
1151  NMENCNAVSTPLPSKINYELLNSDEDCNTPCRSLIGCLMYIMLCTRPDLT  1200
1201  TAVNILSRYSSKNNSELWQNLKRVLRYLKGTIDMKLIFKKNLAFENKIIG  1250
1251  YVDSDWAGSEIDRKSTTGYLFKMFDFNLICWNTKRQNSVAASSTEAEYMA  1300
1301  LFEAVREALWLKFLLTSINIKLENPIKIYEDNQGCISIANNPSCHKRAKH  1350
1351  IDIKYHFAREQVQNNVICLEYIPTENQLADIFTKPLPAARFVELRDKLGL  1400
1401  LQDDQSNAE                                           1409

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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