 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q91ZI0 from www.uniprot.org...
The NucPred score for your sequence is 0.57 (see score help below)
1 MARRPLWWGLPGPSTPVLLLLLLSLFPFSREELGGGGDQDWDPGVATTTG 50
51 PRAQIGSGAVALCPESPGVWEDGDPGLGVREPVFMRLRVGRQNARNGRGA 100
101 PEQPNAEVVVQALGSREQEAGQGPGYLLCWHPEISSCGRTGPLRRGSLPL 150
151 DALSPGDSDLRNSSPHPSELLAQPDGSRPVAFQRNARRSIRKRVETSRCC 200
201 GKLWEPGHKGQGERSATSTVDRGPFRRDCLPGSLGSGLGEDSAPRAVRTA 250
251 PTPGSAPRESRTAPGRMRSRGLFRRRFLFERPGPRPPGFPTGPEAKQILS 300
301 TNQARPRRAANRHPQFPQYNYQTLVPENEAAGTSVLRVVAQDPDPGEAGR 350
351 LIYSLAALMNSRSLELFSIDPQSGLIRTAAALDRESMERHYLRVTAQDHG 400
401 SPRLSATTMVAVTVADRNDHAPVFEQAQYRETLRENVEEGYPILQLRATD 450
451 GDAPPNANLRYRFVGSPAVRTAAAAAFEIDPRSGLISTSGRVDREHMESY 500
501 ELVVEASDQGQEPGPRSATVRVHITVLDENDNAPQFSEKRYVAQVREDVR 550
551 PHTVVLRVTATDKDKDANGLVHYNIISGNSRGHFAIDSLTGEIQVMAPLD 600
601 FEAEREYALRIRAQDAGRPPLSNNTGLASIQVVDINDHAPIFVSTPFQVS 650
651 VLENAPLGHSVIHIQAVDADHGENSRLEYSLTGVASDTPFVINSATGWVS 700
701 VSGPLDRESVEHYFFGVEARDHGSPPLSASASVTVTVLDVNDNRPEFTMK 750
751 EYHLRLNEDAAVGTSVVSVTAVDRDANSAISYQITGGNTRNRFAISTQGG 800
801 VGLVTLALPLDYKQERYFKLVLTASDRALHDHCYVHINITDANTHRPVFQ 850
851 SAHYSVSMNEDRPVGSTVVVISASDDDVGENARITYLLEDNLPQFRIDAD 900
901 SGAITLQAPLDYEDQVTYTLAITARDNGIPQKADTTYVEVMVNDVNDNAP 950
951 QFVASHYTGLVSEDAPPFTSVLQISATDRDAHANGRVQYTFQNGEDGDGD 1000
1001 FTIEPTSGIVRTVRRLDREAVPVYELTAYAVDRGVPPLRTPVSIQVTVQD 1050
1051 VNDNAPVFPAEEFEVRVKENSIVGSVVAQITAVDPDDGPNAHIMYQIVEG 1100
1101 NIPELFQMDIFSGELTALIDLDYEARQEYVIVVQATSAPLVSRATVHVRL 1150
1151 VDQNDNSPVLNNFQILFNNYVSNRSDTFPSGIIGRIPAYDPDVSDHLFYS 1200
1201 FERGNELQLLVVNRTSGELRLSRKLDNNRPLVASMLVTVTDGLHSVTAQC 1250
1251 VLRVVIITEELLANSLTVRLENMWQERFLSPLLGHFLEGVAAVLATPTED 1300
1301 VFIFNIQNDTDVGGTVLNVSFSALAPRGAGAGAAGPWFSSEELQEQLYVR 1350
1351 RAALAARSLLDVLPFDDNVCLREPCENYMKCVSVLRFDSSAPFLASTSTL 1400
1401 FRPIQPIAGLRCRCPPGFTGDFCETELDLCYSNPCRNGGACARREGGYTC 1450
1451 VCRPRFTDCELDTEAGRCVPGVCRNGGTCTNAPNGGFRCQCPAGGAFEGP 1500
1501 RCEVAARSFPPSSFVMFRGLRQRFHLTLSLSFATVQPSGLLFYNGRLNEK 1550
1551 HDFLALELVAGQVRLTYSTGESNTVVSPTVPGGLSDGQWHTVHLRYYNKP 1600
1601 RTDALGGAQGPSKDKVAVLSVDDCNVAVALQFGAEIGNYSCAAAGVQTSS 1650
1651 KKSLDLTGPLLLGGVPNLPENFPVSHKDFIGCMRDLHIDGRRMDMAAFVA 1700
1701 NNGTMAGCQAKSHFCASGPCKNNGFCSERWGGFSCDCPVGFGGKDCRLTM 1750
1751 AHPYHFQGNGTLSWDFGNDMAVSVPWYLGLSFRTRATKGILMQVQLGPHS 1800
1801 VLLCKLDRGLLSVTLNRASGHTVHLLLDQMTVSDGRWHDLRLELQEEPGG 1850
1851 RRGHHIFMVSLDFTLFQDTMAMGGELQGLKVKQLHVGGLPPSSKEEGHQG 1900
1901 LVGCIQGVWIGFTPFGSSALLPPSHRVNVEPGCTVTNPCASGPCPPHADC 1950
1951 KDLWQTFSCTCRPGYYGPGCVDACLLNPCQNQGSCRHLQGAPHGYTCDCV 2000
2001 SGYFGQHCEHRVDQQCPRGWWGSPTCGPCNCDVHKGFDPNCNKTNGQCHC 2050
2051 KEFHYRPRGSDSCLPCDCYPVGSTSRSCAPHSGQCPCRPGALGRQCNSCD 2100
2101 SPFAEVTASGCRVLYDACPKSLRSGVWWPQTKFGVLATVPCPRGALGAAV 2150
2151 RLCDEDQGWLEPDLFNCTSPAFRELSLLLDGLELNKTALDTVEAKKLAQR 2200
2201 LREVTGQTDHYFSQDVRVTARLLAYLLAFESHQQGFGLTATQDAHFNENL 2250
2251 LWAGSALLAPETGHLWAALGQRAPGGSPGSAGLVQHLEEYAATLARNMEL 2300
2301 TYLNPVGLVTPNIMLSIDRMEHPSSTQGARRYPRYHSNLFRGQDAWDPHT 2350
2351 HVLLPSQASQPSPSEVLPTSSNAENATASSVVSPPAPLEPESEPGISIVI 2400
2401 LLVYRALGGLLPAQFQAERRGARLPQNPVMNSPVVSVAVFHGRNFLRGVL 2450
2451 VSPINLEFRLLQTANRSKAICVQWDPPGPTDQHGMWTARDCELVHRNGSH 2500
2501 ARCRCSRTGTFGVLMDASPRERLEGDLELLAVFTHVVVAVSVTALVLTAA 2550
2551 VLLSLRSLKSNVRGIHANVAAALGVAELLFLLGIHRTHNQLLCTAVAILL 2600
2601 HYFFLSTFAWLLVQGLHLYRMQVEPRNVDRGAMRFYHALGWGVPAVLLGL 2650
2651 AVGLDPEGYGNPDFCWISIHEPLIWSFAGPIVLVIVMNGTMFLLAARTSC 2700
2701 STGQREAKKTSVLTLRSSFLLLLLVSASWLFGLLAVNHSILAFHYLHAGL 2750
2751 CGLQGLAVLLLFCVLNADARAAWTPACLGKKAAPEETRPAPGPGSGAYNN 2800
2801 TALFEESGLIRITLGASTVSSVSSARSGRAQDQDSQRGRSYLRDNVLVRH 2850
2851 GSTAEHTERSLQAHAGPTDLDVAMFHRDAGADSDSDSDLSLEEERSLSIP 2900
2901 SSESEDNGRTRGRFQRPLRRAAQSERLLAHPKDVDGNDLLSYWPALGECE 2950
2951 AAPCALQAWGSERRLGLDSNKDAANNNQPELALTSGDETSLGRAQRQRKG 3000
3001 ILKNRLQYPLVPQSRGTPELSWCRAATLGHRAVPAASYGRIYAGGGTGSL 3050
3051 SQPASRYSSREQLDLLLRRQLSKERLEEVPVPAPVLHPLSRPGSQERLDT 3100
3101 APARLEARDRGSTLPRRQPPRDYPGTMAGRFGSRDALDLGAPREWLSTLP 3150
3151 PPRRNRDLDPQHPPLPLSPQRQLSRDPLLPSRPLDSLSRISNSREGLDQV 3200
3201 PSRHPSREALGPAPQLLRAREDPASGPSHGPSTEQLDILSSILASFNSSA 3250
3251 LSSVQSSSTPSGPHTTATASALGPSTPRSATSHSISELSPDSEVPRSEGH 3300
3301 S 3301
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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