 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q15149 from www.uniprot.org...
The NucPred score for your sequence is 0.84 (see score help below)
1 MVAGMLMPRDQLRAIYEVLFREGVMVAKKDRRPRSLHPHVPGVTNLQVMR 50
51 AMASLRARGLVRETFAWCHFYWYLTNEGIAHLRQYLHLPPEIVPASLQRV 100
101 RRPVAMVMPARRTPHVQAVQGPLGSPPKRGPLPTEEQRVYRRKELEEVSP 150
151 ETPVVPATTQRTLARPGPEPAPATDERDRVQKKTFTKWVNKHLIKAQRHI 200
201 SDLYEDLRDGHNLISLLEVLSGDSLPREKGRMRFHKLQNVQIALDYLRHR 250
251 QVKLVNIRNDDIADGNPKLTLGLIWTIILHFQISDIQVSGQSEDMTAKEK 300
301 LLLWSQRMVEGYQGLRCDNFTSSWRDGRLFNAIIHRHKPLLIDMNKVYRQ 350
351 TNLENLDQAFSVAERDLGVTRLLDPEDVDVPQPDEKSIITYVSSLYDAMP 400
401 RVPDVQDGVRANELQLRWQEYRELVLLLLQWMRHHTAAFEERRFPSSFEE 450
451 IEILWSQFLKFKEMELPAKEADKNRSKGIYQSLEGAVQAGQLKVPPGYHP 500
501 LDVEKEWGKLHVAILEREKQLRSEFERLECLQRIVTKLQMEAGLCEEQLN 550
551 QADALLQSDVRLLAAGKVPQRAGEVERDLDKADSMIRLLFNDVQTLKDGR 600
601 HPQGEQMYRRVYRLHERLVAIRTEYNLRLKAGVAAPATQVAQVTLQSVQR 650
651 RPELEDSTLRYLQDLLAWVEENQHRVDGAEWGVDLPSVEAQLGSHRGLHQ 700
701 SIEEFRAKIERARSDEGQLSPATRGAYRDCLGRLDLQYAKLLNSSKARLR 750
751 SLESLHSFVAAATKELMWLNEKEEEEVGFDWSDRNTNMTAKKESYSALMR 800
801 ELELKEKKIKELQNAGDRLLREDHPARPTVESFQAALQTQWSWMLQLCCC 850
851 IEAHLKENAAYFQFFSDVREAEGQLQKLQEALRRKYSCDRSATVTRLEDL 900
901 LQDAQDEKEQLNEYKGHLSGLAKRAKAVVQLKPRHPAHPMRGRLPLLAVC 950
951 DYKQVEVTVHKGDECQLVGPAQPSHWKVLSSSGSEAAVPSVCFLVPPPNQ 1000
1001 EAQEAVTRLEAQHQALVTLWHQLHVDMKSLLAWQSLRRDVQLIRSWSLAT 1050
1051 FRTLKPEEQRQALHSLELHYQAFLRDSQDAGGFGPEDRLMAEREYGSCSH 1100
1101 HYQQLLQSLEQGAQEESRCQRCISELKDIRLQLEACETRTVHRLRLPLDK 1150
1151 EPARECAQRIAEQQKAQAEVEGLGKGVARLSAEAEKVLALPEPSPAAPTL 1200
1201 RSELELTLGKLEQVRSLSAIYLEKLKTISLVIRGTQGAEEVLRAHEEQLK 1250
1251 EAQAVPATLPELEATKASLKKLRAQAEAQQPTFDALRDELRGAQEVGERL 1300
1301 QQRHGERDVEVERWRERVAQLLERWQAVLAQTDVRQRELEQLGRQLRYYR 1350
1351 ESADPLGAWLQDARRRQEQIQAMPLADSQAVREQLRQEQALLEEIERHGE 1400
1401 KVEECQRFAKQYINAIKDYELQLVTYKAQLEPVASPAKKPKVQSGSESVI 1450
1451 QEYVDLRTHYSELTTLTSQYIKFISETLRRMEEEERLAEQQRAEERERLA 1500
1501 EVEAALEKQRQLAEAHAQAKAQAEREAKELQQRMQEEVVRREEAAVDAQQ 1550
1551 QKRSIQEELQQLRQSSEAEIQAKARQAEAAERSRLRIEEEIRVVRLQLEA 1600
1601 TERQRGGAEGELQALRARAEEAEAQKRQAQEEAERLRRQVQDESQRKRQA 1650
1651 EVELASRVKAEAEAAREKQRALQALEELRLQAEEAERRLRQAEVERARQV 1700
1701 QVALETAQRSAEAELQSKRASFAEKTAQLERSLQEEHVAVAQLREEAERR 1750
1751 AQQQAEAERAREEAERELERWQLKANEALRLRLQAEEVAQQKSLAQAEAE 1800
1801 KQKEEAEREARRRGKAEEQAVRQRELAEQELEKQRQLAEGTAQQRLAAEQ 1850
1851 ELIRLRAETEQGEQQRQLLEEELARLQREAAAATQKRQELEAELAKVRAE 1900
1901 MEVLLASKARAEEESRSTSEKSKQRLEAEAGRFRELAEEAARLRALAEEA 1950
1951 KRQRQLAEEDAARQRAEAERVLAEKLAAIGEATRLKTEAEIALKEKEAEN 2000
2001 ERLRRLAEDEAFQRRRLEEQAAQHKADIEERLAQLRKASDSELERQKGLV 2050
2051 EDTLRQRRQVEEEILALKASFEKAAAGKAELELELGRIRSNAEDTLRSKE 2100
2101 QAELEAARQRQLAAEEERRRREAEERVQKSLAAEEEAARQRKAALEEVER 2150
2151 LKAKVEEARRLRERAEQESARQLQLAQEAAQKRLQAEEKAHAFAVQQKEQ 2200
2201 ELQQTLQQEQSVLDQLRGEAEAARRAAEEAEEARVQAEREAAQSRRQVEE 2250
2251 AERLKQSAEEQAQARAQAQAAAEKLRKEAEQEAARRAQAEQAALRQKQAA 2300
2301 DAEMEKHKKFAEQTLRQKAQVEQELTTLRLQLEETDHQKNLLDEELQRLK 2350
2351 AEATEAARQRSQVEEELFSVRVQMEELSKLKARIEAENRALILRDKDNTQ 2400
2401 RFLQEEAEKMKQVAEEAARLSVAAQEAARLRQLAEEDLAQQRALAEKMLK 2450
2451 EKMQAVQEATRLKAEAELLQQQKELAQEQARRLQEDKEQMAQQLAEETQG 2500
2501 FQRTLEAERQRQLEMSAEAERLKLRVAEMSRAQARAEEDAQRFRKQAEEI 2550
2551 GEKLHRTELATQEKVTLVQTLEIQRQQSDHDAERLREAIAELEREKEKLQ 2600
2601 QEAKLLQLKSEEMQTVQQEQLLQETQALQQSFLSEKDSLLQRERFIEQEK 2650
2651 AKLEQLFQDEVAKAQQLREEQQRQQQQMEQERQRLVASMEEARRRQHEAE 2700
2701 EGVRRKQEELQQLEQQRRQQEELLAEENQRLREQLQLLEEQHRAALAHSE 2750
2751 EVTASQVAATKTLPNGRDALDGPAAEAEPEHSFDGLRRKVSAQRLQEAGI 2800
2801 LSAEELQRLAQGHTTVDELARREDVRHYLQGRSSIAGLLLKATNEKLSVY 2850
2851 AALQRQLLSPGTALILLEAQAASGFLLDPVRNRRLTVNEAVKEGVVGPEL 2900
2901 HHKLLSAERAVTGYKDPYTGQQISLFQAMQKGLIVREHGIRLLEAQIATG 2950
2951 GVIDPVHSHRVPVDVAYRRGYFDEEMNRVLADPSDDTKGFFDPNTHENLT 3000
3001 YLQLLERCVEDPETGLCLLPLTDKAAKGGELVYTDSEARDVFEKATVSAP 3050
3051 FGKFQGKTVTIWEIINSEYFTAEQRRDLLRQFRTGRITVEKIIKIIITVV 3100
3101 EEQEQKGRLCFEGLRSLVPAAELLESRVIDRELYQQLQRGERSVRDVAEV 3150
3151 DTVRRALRGANVIAGVWLEEAGQKLSIYNALKKDLLPSDMAVALLEAQAG 3200
3201 TGHIIDPATSARLTVDEAVRAGLVGPEFHEKLLSAEKAVTGYRDPYTGQS 3250
3251 VSLFQALKKGLIPREQGLRLLDAQLSTGGIVDPSKSHRVPLDVACARGCL 3300
3301 DEETSRALSAPRADAKAYSDPSTGEPATYGELQQRCRPDQLTGLSLLPLS 3350
3351 EKAARARQEELYSELQARETFEKTPVEVPVGGFKGRTVTVWELISSEYFT 3400
3401 AEQRQELLRQFRTGKVTVEKVIKILITIVEEVETLRQERLSFSGLRAPVP 3450
3451 ASELLASGVLSRAQFEQLKDGKTTVKDLSELGSVRTLLQGSGCLAGIYLE 3500
3501 DTKEKVSIYEAMRRGLLRATTAALLLEAQAATGFLVDPVRNQRLYVHEAV 3550
3551 KAGVVGPELHEQLLSAEKAVTGYRDPYSGSTISLFQAMQKGLVLRQHGIR 3600
3601 LLEAQIATGGIIDPVHSHRVPVDVAYQRGYFSEEMNRVLADPSDDTKGFF 3650
3651 DPNTHENLTYRQLLERCVEDPETGLRLLPLKGAEKAEVVETTQVYTEEET 3700
3701 RRAFEETQIDIPGGGSHGGSTMSLWEVMQSDLIPEEQRAQLMADFQAGRV 3750
3751 TKERMIIIIIEIIEKTEIIRQQGLASYDYVRRRLTAEDLFEARIISLETY 3800
3801 NLLREGTRSLREALEAESAWCYLYGTGSVAGVYLPGSRQTLSIYQALKKG 3850
3851 LLSAEVARLLLEAQAATGFLLDPVKGERLTVDEAVRKGLVGPELHDRLLS 3900
3901 AERAVTGYRDPYTEQTISLFQAMKKELIPTEEALRLLDAQLATGGIVDPR 3950
3951 LGFHLPLEVAYQRGYLNKDTHDQLSEPSEVRSYVDPSTDERLSYTQLLRR 4000
4001 CRRDDGTGQLLLPLSDARKLTFRGLRKQITMEELVRSQVMDEATALQLRE 4050
4051 GLTSIEEVTKNLQKFLEGTSCIAGVFVDATKERLSVYQAMKKGIIRPGTA 4100
4101 FELLEAQAATGYVIDPIKGLKLTVEEAVRMGIVGPEFKDKLLSAERAVTG 4150
4151 YKDPYSGKLISLFQAMKKGLILKDHGIRLLEAQIATGGIIDPEESHRLPV 4200
4201 EVAYKRGLFDEEMNEILTDPSDDTKGFFDPNTEENLTYLQLMERCITDPQ 4250
4251 TGLCLLPLKEKKRERKTSSKSSVRKRRVVIVDPETGKEMSVYEAYRKGLI 4300
4301 DHQTYLELSEQECEWEEITISSSDGVVKSMIIDRRSGRQYDIDDAIAKNL 4350
4351 IDRSALDQYRAGTLSITEFADMLSGNAGGFRSRSSSVGSSSSYPISPAVS 4400
4401 RTQLASWSDPTEETGPVAGILDTETLEKVSITEAMHRNLVDNITGQRLLE 4450
4451 AQACTGGIIDPSTGERFPVTDAVNKGLVDKIMVDRINLAQKAFCGFEDPR 4500
4501 TKTKMSAAQALKKGWLYYEAGQRFLEVQYLTGGLIEPDTPGRVPLDEALQ 4550
4551 RGTVDARTAQKLRDVGAYSKYLTCPKTKLKISYKDALDRSMVEEGTGLRL 4600
4601 LEAAAQSTKGYYSPYSVSGSGSTAGSRTGSRTGSRAGSRRGSFDATGSGF 4650
4651 SMTFSSSSYSSSGYGRRYASGSSASLGGPESAVA 4684
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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