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

NucPred

Fetching Q91VN0 from www.uniprot.org...

The NucPred score for your sequence is 0.48 (see score help below)

   1  METAPTRAPPPPPPPLLLLVLYCSLVPAAASPLLLFANRRDVRLVDAGGV    50
  51  KLESTIVASGLEDAAAVDFQFSKGAVYWTDVSEEAIKQTYLNQTGAAAQN   100
 101  IVISGLVSPDGLACDWVGKKLYWTDSETNRIEVANLNGTSRKVLFWQDLD   150
 151  QPRAIALDPAHGYMYWTDWGEAPRIERAGMDGSTRKIIVDSDIYWPNGLT   200
 201  IDLEEQKLYWADAKLSFIHRANLDGSFRQKVVEGSLTHPFALTLSGDTLY   250
 251  WTDWQTRSIHACNKWTGEQRKEILSALYSPMDIQVLSQERQPPFHTPCEE   300
 301  DNGGCSHLCLLSPREPFYSCACPTGVQLQDNGKTCKTGAEEVLLLARRTD   350
 351  LRRISLDTPDFTDIVLQVGDIRHAIAIDYDPLEGYVYWTDDEVRAIRRAY   400
 401  LDGSGAQTLVNTEINDPDGIAVDWVARNLYWTDTGTDRIEVTRLNGTSRK   450
 451  ILVSEDLDEPRAIVLHPVMGLMYWTDWGENPKIECANLDGRDRHVLVNTS   500
 501  LGWPNGLALDLQEGKLYWGDAKTDKIEVINIDGTKRKTLLEDKLPHIFGF   550
 551  TLLGDFIYWTDWQRRSIERVHKVKASRDVIIDQLPDLMGLKAVNVAKVVG   600
 601  TNPCADGNGGCSHLCFFTPRATKCGCPIGLELLSDMKTCIIPEAFLVFTS   650
 651  RATIHRISLETNNNDVAIPLTGVKEASALDFDVSNNHIYWTDVSLKTISR   700
 701  AFMNGSSVEHVIEFGLDYPEGMAVDWMGKNLYWADTGTNRIEVARLDGQF   750
 751  RQVLVWRDLDNPRSLALDPTKGYIYWTEWGGKPRIVRAFMDGTNCMTLVD   800
 801  KVGRANDLTIDYADQRLYWTDLDTNMIESSNMLGQERMVIADDLPYPFGL   850
 851  TQYSDYIYWTDWNLHSIERADKTSGRNRTLIQGHLDFVMDILVFHSSRQD   900
 901  GLNDCVHSNGQCGQLCLAIPGGHRCGCASHYTLDPSSRNCSPPSTFLLFS   950
 951  QKFAISRMIPDDQLSPDLVLPLHGLRNVKAINYDPLDKFIYWVDGRQNIK  1000
1001  RAKDDGTQPSMLTSPSQSLSPDRQPHDLSIDIYSRTLFWTCEATNTINVH  1050
1051  RLDGDAMGVVLRGDRDKPRAIAVNAERGYMYFTNMQDHAAKIERASLDGT  1100
1101  EREVLFTTGLIRPVALVVDNALGKLFWVDADLKRIESCDLSGANRLTLED  1150
1151  ANIVQPVGLTVLGRHLYWIDRQQQMIERVEKTTGDKRTRVQGRVTHLTGI  1200
1201  HAVEEVSLEEFSAHPCARDNGGCSHICIAKGDGTPRCSCPVHLVLLQNLL  1250
1251  TCGEPPTCSPDQFACTTGEIDCIPGAWRCDGFPECADQSDEEGCPVCSAS  1300
1301  QFPCARGQCVDLRLRCDGEADCQDRSDEANCDAVCLPNQFRCTSGQCVLI  1350
1351  KQQCDSFPDCADGSDELMCEINKPPSDDIPAHSSAIGPVIGIILSLFVMG  1400
1401  GVYFVCQRVMCQRYTGASGPFPHEYVGGAPHVPLNFIAPGGSQHGPFPGI  1450
1451  PCSKSVMSSMSLVGGRGSVPLYDRNHVTGASSSSSSSTKATLYPPILNPP  1500
1501  PSPATDPSLYNVDVFYSSGIPATARPYRPYVIRGMAPPTTPCSTDVCDSD  1550
1551  YSTSRWKSSKYYLDLNSDSDPYPPPPTPHSQYLSAEDSCPPSPGTERSYC  1600
1601  HLFPPPPSPCTDSS                                      1614

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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