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

NucPred

Fetching Q25452 from www.uniprot.org...

The NucPred score for your sequence is 0.40 (see score help below)

   1  MDDAVCPTETDNVQNKQKATTPKRTQRRGGKQQLDRPERALFCLTLKNPL    50
  51  RIFCIKIVDSKLFEYFILLTIFANCVALAVYTPYPSGDSNITNQMLEKIE   100
 101  YIFLVIFTSECVMKIIAYGFVLHTGSYLRNGWNFLDFFIVVIGMISTALS   150
 151  NLVKEGFDVKALRAFRVLRPLRLVSGVPSLQVVLNSILKAMIPLLHIALL   200
 201  VLFVIIIYAIIGLELFSGKLHKTCRHSNTGEYLNDLDELHACGVGFKCPS   250
 251  GYECFDDWVGPNDGITNFDNFGLSMLTVFQCITLEGWTDVLYSIQDAMGS   300
 301  SWEWIYFVSMVILGAFFVMNLILGVLSGEFSKERTKAKNRGDFQKLREKQ   350
 351  QIEEDLRGYLDWITQAEDIEPDPDAQIIEDCHKNKVKEVVSIDNLKDHEN   400
 401  ETQQTDSWFRSQKKYLERINRRIRRACRKAVKSQAFYWLIILLVFLNTGV   450
 451  LATEHYRQPIWLDQFQEYTNIFFIALFTCEMILKMYSLGFQGYFVSLFNR   500
 501  FDCFVVIGSISEMVLTSSELMAPLGVSVLRCVRLLRVFKVTKYWHSLSNL   550
 551  VASLLNSIQSIASLLLLLFLFIVIFGLLGMQVFGGRFTFKPEEEKPRSNF   600
 601  DSFYQSLLTVFQILTGEDWNVVMYDGIRAYGGVFSFGIVACIYYIILFIC   650
 651  GNYILLNVFLAIAVDNLADADSLSTIEKEDESQIQLDNQIKNEMENEEYL   700
 701  QNGDHISFKAEFGADLDTYLQDEECGSYSDDENTYNKLGGVKQRVSSLPR   750
 751  RNTNTDMDRIKKDIPYGTSFFIFSHTNRFRIFCHRLCNHSNFGNFILCCI   800
 801  MFSSAMLAAENPLKADASRNIVLNKFDYFFTAVFTIELVLKLISYGFVLH   850
 851  DGAFCRSAFNLLDLLVVCVSLISIFFNSNAISVVKILRVLRVLRPLRAIN   900
 901  RAKGLKHVVQCVIVAVKTIGNIVLVTCLLQFMFAVIGVQLFKGKFFSCSD   950
 951  GSKVYESDCHGTYLFYENGDINKPRLKEREWKNNKFHFDDVAKAMLTLFT  1000
1001  VSTFEGWPTLLYVSIDSNKENGGPIYNFRPIVAAYYIIYIIIIAFFMVNI  1050
1051  FVGFVIVTFQNEGEQEYKNCELDKNQRNCIEFALKAKPVRRYIPKHSIQY  1100
1101  KVWWFVTSSSFEYSIFVLIMINTVTLAMKFYKQPEYYSEILDALNMIFTA  1150
1151  VFSLEFIFKLAAFRFKNYFGDAWNTFDFIIVLGSFIDIVYSEIKTKEQAL  1200
1201  ATCDGQSCNKAKGGSTLISINFFRLFRVMRLVKLLSKGEGIRTLLWTFIK  1250
1251  SFQALPYVALLIVMLFFIYAVIGMQVFGKIMLEEGTSIDRNNNFQTFPQA  1300
1301  VLVLFRSATGEAWQEIMMACSPRDDVKCDPESDAVNNCGSSIAFPYFISF  1350
1351  YVLCSFLIINLFVAVIMDNFDYLTRDWSILGPHHLDEFIRLWSEYDPDAK  1400
1401  GRIKHLDVVTLLRKISPPLGFGKLCPHRMACKRLVSMNMPLNSDGTVLFN  1450
1451  ATLFAVVRLPLAIKTDGNIDEANAELRATIKQIWKRTNPRLLDQVVLTGN  1500
1501  DDEVTVGKFYATYLIQDYFRRFKKRKEQEGKCDQTENAVTLQAGLRTLQQ  1550
1551  NSPALKRTISGYLDELASEADPMHRRHHSLFGKVMSSLLRHEEITSSKIK  1600
1601  HLSRTKTIPYQVEFLQHKVQLERNKDCLTSASDDISIEKIIRKQNKYNGQ  1650
1651  YFNSEANFMDNIKYTPRYDGEEYEMEDPKSKDKDEEF               1687

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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