 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9TW65 from www.uniprot.org...
The NucPred score for your sequence is 0.93 (see score help below)
1 MLFSGASTAKPKKDEKKDKKSDRDPKNELQEWVFVRWANHLLGTERLTDY 50
51 KSLQDGSNAIFVYQAIIGQTMAVLGNPSDDWPNVLQNIGDSKTNPQEVME 100
101 GQQKAVLSAWWQLVQFFWKNNAPVQLREEKLSEAIKQWCIEVMKSYEEID 150
151 VYDFTSSFRDGHAFNYLIHSYDRKLINLTKTAEMSAIDRIENAFAVAEKT 200
201 WNVPRLLNPKDLHSDQLDSHSVLCYLMSLYLAMISTSKIETELEAQQIQQ 250
251 QKVAALLASHKMLSSQPSTSSSSALQIPPQTPPTAHHQAMLDRGKSFEQS 300
301 AEGEVRSRKSSSSSQKSGKSKKARREEQLAEFKSCIEQVLTWLLEAEDEL 350
351 TTLTQMPRVELASVRSQFSDFESFMSSLTDSQDTVGRVLLRGQMLSNKSE 400
401 SEEEKESIGANLHLVNTRWEALREQAMQEQAVLQQQIHLLQQSELDTISQ 450
451 WLDAAELEIESFGPLAADSSQALRQIELHTKFQQKLNDFQETIDKLESFV 500
501 AVVDEENDASVATLEDALSAVSVRWGHVCEWAEKRATKLDGLADLLDKTN 550
551 EVFENLSGWLAERENELMTGLKSAHHLENEEQVAQQVRRLQKTEEQLEQE 600
601 HASFVRLSQLSCELVGRLDDSNGAAANAVRLSLDSITQRWDNLVARIEEH 650
651 GKTLVKSGKADVKQVQESQNEQKEQPASSEGLSTDTEGEEQKNQLVDKFL 700
701 LHISKLSHELEPLQDWSEKFEVSRKKDDIRKMMNTCQEKLIQIKEQEARV 750
751 NRLQLELEHLHVAKLNARQLKRANDAFEQFAKGWARIVTKISEAMNVLTG 800
801 QEAGGNGNGSEEAAVAAKIEQWIEAVDKVINELSQLPVNERRSRIDKLEQ 850
851 QLQVQDKNVGFIEKDLLKKAILKKGLEIAGKRLAALKVEEKPVEKEEQLV 900
901 LSNSEEPEAEKHVTFVQETTEKPAPLQEPTSEAQLLEELDGPWSRVGDVV 950
951 AIEHDLLRAKRAVDTARNSQMSNETVEKAETRKAEMEEKRRVTMSARSKF 1000
1001 RMAEETLEEIERNLDRLQVSDLEIADLVRGLEQEAAKLGERVSQRKEAER 1050
1051 TAEKILSMDDDEISQEIVIKTKDSTEKLIKRWNQLELDLEENLRKAKRDQ 1100
1101 DVFIQKRLREGEEALNEIKTAIEGKRESLDAETAAENLDHLESSLDNISS 1150
1151 LFGEIGSLPMDDNSREKLSKLAKAKDQITARANEALAALTRTVSECEDFE 1200
1201 KQIMLFQNWSARIGFLLQARKSADISAFDIPHEYHEDLGNEAELIPKLSR 1250
1251 EFEEWTVKLNEMNSTATEKDDSARMREQLNHANETMAELKRKFNEFKRPK 1300
1301 GFEEKLEKVITTLSNVEMGLDDTTGIDGSECGGALMEVRALVRMLDGAQE 1350
1351 KWKDLAENREQLVKDRVLDEETSKETLQKLQYAKTKSKELYERSSTCIER 1400
1401 LEDCVEMYQRLKMESDEIERFLEEMEGKLDQYAASDRPEEAEIVNELISE 1450
1451 WNRNEAAMKNAEHLQRQLNERAIKIPDDVLSLKRLRADALKNRLNSWCRT 1500
1501 IQEMSEDDESALLEIDELHQNLEKELKLVSDKEPSKIAEKLRFLRADRDR 1550
1551 LSSRTRKLAAKNPRLAATSSDVLAGLNQKWKELEVKASAEKAPAPELRDA 1600
1601 RLSSPSEQPFDKRVQELCDLFENLEAQLDFNGSPVSMVTEYQKRVENLDE 1650
1651 YLDEYRPALDDTIEEGRKIAETGRLELQTHSAIEKLDELTNRIEQVEVEL 1700
1701 DKHRDKVPSLVEQHEQLKKDIDSFLLVLDVFTDRNLDDVDIAKSTRKELA 1750
1751 ERDSHIVSLTSRATAIHCALPGKGPQLHDVTLDKLRDRIEKLEARLSATE 1800
1801 KKPVETVKSTIPDRPEVPEEPEKSSPDRTSRSSLQLAMEAYGTATEDDSV 1850
1851 ISEAVTVGQKSVDQVDPVEQLEPVEPVEPKLEVKQLKDEATEEEEKRTII 1900
1901 LPDETEKVIETIPAARPSAGPSEGTVAEVSTSEILKARPAQESIERTVRE 1950
1951 VPVDEYEETANISSGDELQDHKISSAVPDSESEIASMFEVLDSIEDSHTN 2000
2001 FEEFPFDYLDSADDDLKKTLLKLESCEKTLAKNEMTINIAQAENARERIT 2050
2051 MLRQMALQRKDKLPKFNEEWNAMQELIQLADALVDEAERYESDQIPQMDR 2100
2101 KSAPNVLGELRKRVANAEGPVIDLVKKLSQLVPRMQEDSPKSQDIRQKVY 2150
2151 GIEDRFRRVGQAEGAAISKALSSALTEPELKLELDEVVRWCEMAEKEAAQ 2200
2201 NVNSLDGDGLEKLDGRLAQFTKELQERKDDMVQLEMAKNMIIPSLKGDAH 2250
2251 HDLRRNFSDTAKRVAMVRDELSDAHKWVATSRDTCDTFWADIDSLEQLAR 2300
2301 DVVRRANGIRMAVIYTPSRENVEGVLRDVQRLKMSIGDVKKRVQTANLPP 2350
2351 AIKLAGKNAKRVVQVLTETATTIADCHDIPTYLIDEMNDSGGDTTESRST 2400
2401 VVEMTSVHTKQSSSSSSNKTPSAGGESDDAHTLNGDDEQSEEDQKIYSRE 2450
2451 SSSTLPRGVSSLGSTGSSGVLDPVAVQLTHTRHWLHDVERDASITVDLAQ 2500
2501 WQPARELWQSIQGIIDEIRLRSVHVTGAHDASPNRQVRQQAAQLLTEMRR 2550
2551 TIENCEKRCLILNQISDIARQNEASRNEMELWLKSASDVIGERRVEELSE 2600
2601 EVVRQELQVLERVVEQLTERKDKMAEINSQANKIVDTYTKDEAHNLSHLL 2650
2651 SRLNMSWTKFNDNIRIRRAVLEASLRSRRDFHSALSEFEKWLSRQEDNCS 2700
2701 KLSADTSNHQAIKDTSKRKNWTQSFKTLNAELNAHEDVMKSVEKMGKMLA 2750
2751 ESLESGNEKVELLKRVGETTRRWTALRKTTNEIGERLEKAEQEWEKLSDG 2800
2801 LADLLSWVEAKKQAIMDEQPTGGSLSAVMQQASFVKGLQREIESKTANYK 2850
2851 STVEEAHSFLMQHDLRPKLHSPHVLDDDYEKEELANLEQRRRGLEINANC 2900
2901 ERLKKNWAELGIEVESWDKLVQHAMQRLQELERNLAECQLHLTSSENEIE 2950
2951 TMKAVEKIHLEDLKIAREETDQISKRIDEVRLFVDDVNDAAARLLAEDLK 3000
3001 LDEHAKGQIEHVNKRYSTLKRAIRIRQAAVRNAASDFGPTSEHFLNQSVT 3050
3051 LPWQRAISKSNLLPYYIEQTSEKTQWEHPVWVEIVKELSQFNRVKFLAYR 3100
3101 TAMKLRALQKRLCLDLVDLTLLEKAFVRLKGLSAEECPGLEGMVCALLPM 3150
3151 YEALHAKYPNQVQSVSLAVDICINFLLNLFDQSRDGIMRVLSFKIAMIVF 3200
3201 SNIPLEEKYRYLFKLVSQDGHATQKQIALLLYDLIHIPRLVGESAAFGGT 3250
3251 NVEPSVRSCFETVRLAPTISEGAFIDWVKKEPQSIVWLAVMHRLVISEST 3300
3301 KHASKCNVCKMFPIIGIRYRCLTCFNCDLCQNCFFSQRTAKSHRTNHPMQ 3350
3351 EYCEKTTSSDDARDFAKMIRNKFRASKRQKGYLPIDVAEEGIPLTCPPAK 3400
3401 VTNQATEQMNADTSQMTAHLAKLSAEHGGGAEHMEPVQSPLQIINQVEQL 3450
3451 QRDEMDQMLHRLQFENKQLRKELEWKRGAASTMEIDRSSKRHQERHQSES 3500
3501 RGGTLPLRNGRSVVSLKSTQSQNDVMDEAKALRLHKQRLEHRSRILEQQN 3550
3551 EQLEMQLQRLKKVIDAQKQQAPLSTNSLLRGSHHQPWSPERARSGSASTL 3600
3601 DRGLIVSSRHQEQAEAAGGGAEDSSDEAGGAGGGPRGSSVGQMQNLMTAC 3650
3651 DDLGKAMESLVVSVVYDSDDEEND 3674
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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