 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9NRC6 from www.uniprot.org...
The NucPred score for your sequence is 0.88 (see score help below)
1 MAGQPHSPRELLGAAGHRSRRPSTELRVPPSPSLTMDSQYETGHIRKLQA 50
51 RHMQMQEKTFTKWINNVFQCGQAGIKIRNLYTELADGIHLLRLLELISGE 100
101 ALPPPSRGRLRVHFLENSSRALAFLRAKVPVPLIGPENIVDGDQTLILGL 150
151 IWVIILRFQISHISLDKEEFGASAALLSTKEALLVWCQRKTASYTNVNIT 200
201 DFSRSWSDGLGFNALIHAHRPDLLDYGSLRPDRPLHNLAFAFLVAEQELG 250
251 IAQLLDPEDVAAAQPDERSIMTYVSLYYHYCSRLHQGQTVQRRLTKILLQ 300
301 LQETELLQTQYEQLVADLLRWIAEKQMQLEARDFPDSLPAMRQLLAAFTI 350
351 FRTQEKPPRLQQRGAAEALLFRLQTALQAQNRRPFLPHEGLGLAELSQCW 400
401 AGLEWAEAARSQALQQRLLQLQRLETLARRFQHKAALRESFLKDAEQVLD 450
451 QARAPPASLATVEAAVQRLGMLEAGILPQEGRFQALAEIADILRQEQYHS 500
501 WADVARRQEEVTVRWQRLLQHLQGQRKQVADMQAVLSLLQEVEAASHQLE 550
551 ELQEPARSTACGQQLAEVVELLQRHDLLEAQVSAHGAHVSHLAQQTAELD 600
601 SSLGTSVEVLQAKARTLAQLQQSLVALVRARRALLEQTLQRAEFLRNCEE 650
651 EEAWLKECGQRVGNAALGRDLSQIAGALQKHKALEAEVHRHQAVCVDLVR 700
701 RGRDLSARRPPTQPDPGERAEAVQGGWQLLQTRVVGRGARLQTALLVLQY 750
751 FADAAEAASWLRERRSSLERASCGQDQAAAETLLRRHVRLERVLRAFAAE 800
801 LRRLEEQGRAASARASLFTVNSALSPPGESLRNPGPWSEASCHPGPGDAW 850
851 KMALPAEPDPDFDPNTILQTQDHLSQDYESLRALAQLRRARLEEAMALFG 900
901 FCSSCGELQLWLEKQTVLLQRVQPQADTLEVMQLKYENFLTALAVGKGLW 950
951 AEVSSSAEQLRQRYPGNSTQIQRQQEELSQRWGQLEALKREKAVQLAHSV 1000
1001 EVCSFLQECGPTQVQLRDVLLQLEALQPGSSEDTCHALQLAQKKTLVLER 1050
1051 RVHFLQSVVVKVEEPGYAESQPLQGQVETLQGLLKQVQEQVAQRARRQAE 1100
1101 TQARQSFLQESQQLLLWAESVQAQLRSKEVSVDVASAQRLLREHQDLLEE 1150
1151 IHLWQERLQQLDAQSQPMAALDCPDSQEVPNTLRVLGQQGQELKVLWEQR 1200
1201 QQWLQEGLELQKFGREVDGFTATCANHQAWLHLDNLGEDVREALSLLQQH 1250
1251 REFGRLLSTLGPRAEALRAHGEKLVQSQHPAAHTVREQLQSIQAQWTRLQ 1300
1301 GRSEQRRRQLLASLQLQEWKQDVAELMQWMEEKGLMAAHEPSGARRNILQ 1350
1351 TLKRHEAAESELLATRRHVEALQQVGRELLSRRPCGQEDIQTRLQGLRSK 1400
1401 WEALNRKMTERGDELQQAGQQEQLLRQLQDAKEQLEQLEGALQSSETGQD 1450
1451 LRSSQRLQKRHQQLESESRTLAAKMAALASMAHGMAASPAILEETQKHLR 1500
1501 RLELLQGHLAIRGLQLQASVELHQFCHLSNMELSWVAEHMPHGSPTSYTE 1550
1551 CLNGAQSLHRKHKELQVEVKAHQGQVQRVLSSGRSLAASGHPQAQHIVEQ 1600
1601 CQELEGHWAELERACEARAQCLQQAVTFQQYFLDVSELEGWVEEKRPLVS 1650
1651 SRDYGRDEAATLRLINKHQALQEELAIYWSSMEELDQTAQTLTGPEVPEQ 1700
1701 QRVVQERLREQLRALQELAATRDRELEGTLRLHEFLREAEDLQGWLASQK 1750
1751 QAAKGGESLGEDPEHALHLCTKFAKFQHQVEMGSQRVAACRLLAESLLER 1800
1801 GHSAGPMVRQRQQDLQTAWSELWELTQARGHALRDTETTLRVHRDLLEVL 1850
1851 TQVQEKATSLPNNVARDLCGLEAQLRSHQGLERELVGTERQLQELLETAG 1900
1901 RVQKLCPGPQAHAVQQRQQAVTQAWAVLQRRMEQRRAQLERARLLARFRT 1950
1951 AVRDYASWAARVRQDLQVEESSQEPSSGPLKLSAHQWLRAELEAREKLWQ 2000
2001 QATQLGQQALLAAGTPTKEVQEELRALQDQRDQVYQTWARKQERLQAEQQ 2050
2051 EQLFLRECGRLEEILAAQEVSLKTSALGSSVEEVEQLIRKHEVFLKVLTA 2100
2101 QDKKEAALRERLKTLRRPRVRDRLPILLQRRMRVKELAESRGHALHASLL 2150
2151 MASFTQAATQAEDWIQAWAQQLKEPVPPGDLRDKLKPLLKHQAFEAEVQA 2200
2201 HEEVMTSVAKKGEALLAQSHPRAGEVSQRLQGLRKHWEDLRQAMALRGQE 2250
2251 LEDRRNFLEFLQRVDLAEAWIQEKEVKMNVGDLGQDLEHCLQLRRRLREF 2300
2301 RGNSAGDTVGDACIRSISDLSLQLKNRDPEEVKIICQRRSQLNNRWASFH 2350
2351 GNLLRYQQQLEGALEIHVLSRELDNVTKRIQEKEALIQALDCGKDLESVQ 2400
2401 RLLRKHEELEREVHPIQAQVESLEREVGRLCQRSPEAAHGLRHRQQEVAE 2450
2451 SWWQLRSRAQKRREALDALHQAQKLQAMLQELLVSAQRLRAQMDTSPAPR 2500
2501 SPVEARRMLEEHQECKAELDSWTDSISLARSTGQQLLTAGHPFSSDIRQV 2550
2551 LAGLEQELSSLEGAWQEHQLQLQQALELQLFLSSVEKMERWLCSKEDSLA 2600
2601 SEGLWDPLAPMEPLLWKHKMLEWDLEVQAGKISALEATARGLHQGGHPEA 2650
2651 QSALGRCQAMLLRKEALFRQAGTRRHRLEELRQLQAFLQDSQEVAAWLRE 2700
2701 KNLVALEEGLLDTAMLPAQLQKQQNFQAELDASMHQQQELQREGQRLLQG 2750
2751 GHPASEAIQERLEELGALWGELQDNSQKKVAKLQKACEALRLRRSMEELE 2800
2801 NWLEPIEVELRAPTVGQALPGVGELLGTQRELEAAVDKKARQAEALLGQA 2850
2851 QAFVREGHCLAQDVEEQARRLLQRFKSLREPLQERRTALEARSLLLKFFR 2900
2901 DADEEMAWVQEKLPLAAAQDYGQSLSAVRHLQEQHQNLESEMSSHEALTR 2950
2951 VVLGTGYKLVQAGHFAAHEVAARVQQLEKAMAHLRAEAARRRLLLQQAQE 3000
3001 AQQFLTELLEAGSWLAERGHVLDSEDMGHSAEATQALLRRLEATKRDLEA 3050
3051 FSPRIERLQQTAALLESRKNPESPKVLAQLQAVREAHAELLRRAEARGHG 3100
3101 LQEQLQLHQLERETLLLDAWLTTKAATAESQDYGQDLEGVKVLEEKFDAF 3150
3151 RKEVQSLGQAKVYALRKLAGTLERGAPRRYPHIQAQRSRIEAAWERLDQA 3200
3201 IKARTENLAAAHEVHSFQQAAAELQGRMQEKTALMKGEDGGHSLSSVRTL 3250
3251 QQQHRRLERELEAMEKEVARLQTEACRLGQLHPAAPGGLAKVQEAWATLQ 3300
3301 AKAQERGQWLAQAAQGHAFLGRCQELLAWAQERQELASSEELAEDVAGAE 3350
3351 QLLGQHEELGQEIRECRLQAQDLRQEGQQLVDNSHFMSAEVTECLQELEG 3400
3401 RLQELEEAWALRWQRCAESWGLQKLRQRLEQAEAWLACWEGLLLKPDYGH 3450
3451 SVSDVELLLHRHQDLEKLLAAQEEKFAQMQKTEMEQELLLQPQELKPGRA 3500
3501 GSSLTSFQWRPSGHQGLGAQLAETRDPQDAKGTPTMEGSLEFKQHLLPGG 3550
3551 RQPSSSSWDSCRGNLQGSSLSLFLDERMAAEKVASIALLDLTGARCERLR 3600
3601 GRHGRKHTFSLRLTSGAEILFAAPSEEQAESWWRALGSTAAQSLSPKLKA 3650
3651 KPVSSLNECTTKDARPGCLLRSDP 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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