 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P62297 from www.uniprot.org...
The NucPred score for your sequence is 0.91 (see score help below)
1 PNEEAAAVRLSRGPAAERGFTIWPXAFVLQPKEKIVVSITWTPLKGGRVR 50
51 ETVTFLVNDILKHQAILLGNAEEPKKKKRTLWDTINKKKVSASSRHNKKV 100
101 SNIQNVNKTFNVSPKADKVRSPLQACENLATNGNCSPPESNPLILEENKL 150
151 PISPISPAFQECHRETCLPLHVRRSTTYTSLPASENGELEKADGANTAKD 200
201 FHFNEKGITETSFDSIDNVNSQTEENGKLTLTPNYSSSLNITQSQGHFLS 250
251 PDSFVNNSHASNNEPEFVKCLSPDMFVKGNTRPVLLESKRVHEICRKILS 300
301 PDSFINDNYGLNEDLETESVNPILSPNQFLKDNIAYICISQQTCQLPLST 350
351 RRFQDSQPPQDERKNAAVPCISECQQLESPKATFEASKALEVMSNSYTFK 400
401 KQNQPKFSAVQDISSHSREKPIKRRPILSATVTKRKPTCAVXNQMETVKP 450
451 KAKRCLNVVVGDCEKETDDQKEKDDFHPLLPTRDLILSRPKSSKNIVTPP 500
501 CKAASVARKRKSKGHTGDENVRVRVTECSEVQEVKRTHFSPLASKTSTVK 550
551 HTHKVLTSSLKRVSHREKVNLKRKTDSLGYRTPTSKTNKRTRPFVPVAQS 600
601 NLTFIKALKAGIPRHPMPFAAKNIFYDERWKEKQEQGFTWWLNFILTPDD 650
651 FTVKTNISEVNASTLLLGVESQHKISVPKAPTKDEVSLRAYTARCRLNRL 700
701 RRAACRLFTSEKMVKAMKKLEIEIEARRLIVRKDRHLWKDVGERQKVLNW 750
751 LLSYNPLWLRIGLETIYGELVPLEDNSDVTGLAMFILNRLLWNPDIAAEY 800
801 RHPSVPHLYRDGHEEALSKFTLKKLLLLVCFLDYAKISRLIDHDPCLFCK 850
851 DAEFKASXDILLAFSRDFLGGEGDLSRHLSLLGFPVTHVQMPFDEFDFAV 900
901 KNLAVDLQCGVRLVRTMELLTQNWNLSKKLRIPAISRLQKMHNVDIVLEI 950
951 LKSRGIQLNDEHGNAILSKDIVDRHREKTLALLWKIALAFQVDISLNLDQ 1000
1001 LKEEIDFLKKTQSMKKTMSALLCRPDAVISKKRDERHSGPFEQYSESVKL 1050
1051 LMDWVNAVCGFYNKKVENFTVSFSDGRVLCYLIHHYHPCYVPFDAICQRT 1100
1101 TQTVECTHTGSVVLNSSSESDGSFLDLSXKSPDQENTSELYKELLENEKK 1150
1151 NFQLVRSAARDLGGIPAMIHHSDMSNTIPDEKVVITYLSFLCARLLDLRK 1200
1201 ETRAARLIQTTWRQYKLKKDLKHHQERDKAARIIQSAIINFLTKQRFKKK 1250
1251 VSAALVIQKYWRRALAKRKLLMLKKEKLERVHSKSASIIQRYWRRYSTRK 1300
1301 QFLKLKYYSIILQSKIRMIIAVASYKRYHWATVTIQXHWRAHVRSKQDRQ 1350
1351 RYELLRSSTLVIQSAFRRWRRHKRQSQINAAITLQRAFREWRVQKRAQEE 1400
1401 RAAVVIQSWYRMHRESQKYIHLRSCVIIIQARFRCFQAQKLYTRTRESIL 1450
1451 TLQKHYRAYVKGKVERTGYLQKRAAAIRLQAAFRGRRARNLCKQIRAACV 1500
1501 LQSCWRMRQDRLRFLNLKKNIIRLQAHIRRRQQLQTYQKMKKAALVIQIH 1550
1551 FRAYISAKEVLASYQKTRSAVIVLQSACRRMQARKKFLHILTAVVKIQSY 1600
1601 YRAYASRRKFLRLKKATVKLQSIVRMKQARKQYLHLRAIAQQREEHLRAS 1650
1651 CIKLQAFLRGYLVRKQVRLQRKAAVLLQSYFRMRKMRLEYLKVCQAAVVI 1700
1701 QRYYRAHRAGAQQRKHFLQVRRAVTCLQAAYRGYKVRRQLQQQSAAALKI 1750
1751 QAAFRGYRQRTKYQSMLQSALKIQRWYRTRKMVSALRSHFFKTRTAAISL 1800
1801 QSAYRGWKVRKQMRKEHEAAVKIQSAFRTARAQKEFRLLKTAASVIQQHL 1850
1851 RARATGLRQRTEYMALRRAAVTLQSAWRGRAARRRIQKQQRCAIIIQACY 1900
1901 RRHVQWKRWEIMKKAARLIQMHYRAYRTGRKQHHLFLKTKGAAIILQSAF 1950
1951 RGVRARKKVKEMHQAATTIQSRYRAYQARKKYASYRAAAVIIQRWYRAAK 2000
2001 LAGCQREEYLAVKKAALKIQAVYRGVRERRQTRRMHMAATLIKAAFKMQQ 2050
2051 SRRRYQQMRTAAIVIQVRYRAYRQGRAQRAKYLTTLKAVALLQAALRGAR 2100
2101 VRQNLRRMRTAATLIQAHYRGRRQQAYFNKLKKVTKTVQQKYRAGRERHA 2150
2151 QLRRYNQLRRSAICIQAAFRGMRARKRLKAMHSAAAVIQRRFRTLVMRRR 2200
2201 FLSLRKTAVWVQRKYRAKVCARHHLQQLQLQKAAIKIQSWYRGWMVRKKT 2250
2251 QEMRRAATVLQAAFRRHRARARYQAWRRASQVIQQRFRAGQAARLQRRQY 2300
2301 LQQXRSALVLQAAFRGMRIRRRLKRMHASATLIQSRFRSVRVRKRFLSLK 2350
2351 KAAVFVQRKYRATICAKHHLQRFLELKKAIIIIQAFYRRRMVKKQLQEMH 2400
2401 RAAALIQASFRMHRARLAFQTWKLAXVLIQQHYRAYRAAKLQRALYIRWR 2450
2451 HSAVVIQAAYKGLKARQLLREKHRAAVIIQSTYRMYRQHFSYQKLQWATK 2500
2501 VIQERYRVSKRKALQHDALKAAACARADFQDMVIRGLIQERQHQAAITVQ 2550
2551 KHFRAFKTRKRYLHFRAKVVFVQRRYRVLMAVRTQAAICIQSCFRGFKAR 2600
2601 RGIQGMHLAATRIQSCYRRHRARADYQAKKRAVVVIQNHYRSYVRVKMER 2650
2651 KEFLAIQKSARTIQAAFRGMKVRQKLKTMPDEKMAAPATRPAFYCHRTES 2700
2701 QHEAGQSPALVAQGLYKTSLVGPSQETEHHSQRKAAVTIQKAFRKMVTRR 2750
2751 LEKQRSAAVQIQSFLQMAVYRRRFLQQKRAALTLQRYFRTQQSRKRFLLY 2800
2801 REAAVGLQNPHRAFLPAKHQRELYSQIRSSVIIIQARVKGFIQKRKFRKL 2850
2851 KDSTIKIQAVWRRHKARKYLREVKAACRIQAWYRCRKARKEYLAVLRAVR 2900
2901 IIQRCFCTQQQRRRFLNVRASAVIIQRRWRAVLSGRTTHEQSLMTKRHQA 2950
2951 ACLIQANFRGYKARQVFLQQKSAALTIQRFIRARKAGKHQRMKYVELKKS 3000
3001 TVVLQALVRGWLVRKRISEQRAKIRLLHFAAAAFYHLSALRIQRAYRRHM 3050
3051 ALKNANNKQLNSAICIQRWFRARSQRKRFLQKYSIVNIQREAREQASQHS 3100
3101 RAASVIQRAVRHFLLRKKQENLNKRIAKIQALWRGYSWRKKNDTSKTKAI 3150
3151 RQRLQCVNREIREENKLYHRTVFALHHLLTYKYLSTVLEALKHLEAVTRL 3200
3201 SSVCCEKMAQSGAISKVFVLIRSCNRSVPCMEVIRYAVQVLLNVAKYEKT 3250
3251 TSAIYBVENCVDTLLELLQMYQEKSGDKVADKSRSIFTKTCCLLAVLLKT 3300
3301 TTRASDVQSRSKVVDRIYSLYKLTAHKHKVNTERILCKQKKNSSVSLSFF 3350
3351 PETPVRTRMVSRLKPDWVLRRDNV 3374
Positively and negatively influencing subsequences are coloured according to the following scale:
(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)
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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