 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P11531 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MLWWEEVEDCYEREDVQKKTFTKWINAQFSKFGKQHIDNLFSDLQDGKRL 50
51 LDLLEGLTGQKLPKEKGSTRVHALNNVNKALRVLQKNNVDLVNIGSTDIV 100
101 DGNHKLTLGLIWNIILHWQVKNVMKTIMAGLQQTNSEKILLSWVRQSTRN 150
151 YPQVNVINFTSSWSDGLALNALIHSHRPDLFDWNSVVSQHSATQRLEHAF 200
201 NIAKCQLGIEKLLDPEDVATTYPDKKSILMYITSLFQVLPQQVSIEAIQE 250
251 VEMLPRTSSKVTREEHFQLHHQMHYSQQITVSLAQGYEQTSSSPKPRFKS 300
301 YAFTQAAYVATSDSTQSPYPSQHLEAPRDKSLDSSLMETEVNLDSYQTAL 350
351 EEVLSWLLSAEDTLRAQGEISNDVEEVKEQFHAHEGFMMDLTSHQGLVGN 400
401 VLQLGSQLVGKGKLSEDEEAEVQEQMNLLNSRWECLRVASMEKQSKLHKV 450
451 LMDLQNQKLKELDDWLTKTEERTKKMEEEPFGPDLEDLKCQVQQHKVLQE 500
501 DLEQEQVRVNSLTHMVVVVDESSGDHATAALEEQLKVLGDRWANICRWTE 550
551 DRWIVLQDILLKWQHFTEEQCLFSTWLSEKEDAMKNIQTSGFKDQNEMMS 600
601 SLHKISTLKIDLEKKKPTMEKLSSLNQDLLSALKNKSVTQKMEIWMENFA 650
651 QRWDNLTQKLEKSSAQISQAVTTTQPSLTQTTVMETVTMVTTREQIMVKH 700
701 AQEELPPPPPQKKRQITVDSELRKRLDVDITELHSWITRSEAVLQSSEFA 750
751 VYRKEGNISDLQEKVNAIAREKAEKFRKLQDASRSAQALVEQMANEGVNA 800
801 ESIRQASEQLNSRWTEFCQLLSERVNWLEYQTNIITFYNQLQQLEQMTTT 850
851 AENLLKTQSTTLSEPTAIKSQLKICKDEVNRLSALQPQIEQLKIQSLQLK 900
901 EKGQGPMFLDADFVAFTNHFNHIFDGVRAKEKELQTIFDTLPPMRYQETM 950
951 SSIRTWIQQSESKLSVPYLSVTEYEIMEERLGKLQALQSSLKEQQNGFNY 1000
1001 LSDTVKEMAKKAPSEICQKYLSEFEEIEGHWKKLSSQLVESCQKLEEHMN 1050
1051 KLRKFQNHIKTLQKWMAEVDVFLKEEWPALGDAEILKKQLKQCRLLVGDI 1100
1101 QTIQPSLNSVNEGGQKIKSEAELEFASRLETELRELNTQWDHICRQVYTR 1150
1151 KEALKAGLDKTVSLQKDLSEMHEWMTQAEEEYLERDFEYKTPDELQTAVE 1200
1201 EMKRAKEEALQKETKVKLLTETVNSVIAHAPPSAQEALKKELETLTTNYQ 1250
1251 WLCTRLNGKCKTLEEVWACWHELLSYLEKANKWLNEVELKLKTMENVPAG 1300
1301 PEEITEVLESLENLMHHSEENPNQIRLLAQTLTDGGVMDELINEELETFN 1350
1351 SRWRELHEEAVRKQKLLEQSIQSAQEIEKSLHLIQESLEFIDKQLAAYIT 1400
1401 DKVDAAQMPQEAQKIQSDLTSHEISLEEMKKHNQGKDANQRVLSQIDVAQ 1450
1451 KKLQDVSMKFRLFQKPANFEQRLEESKMILDEVKMHLPALETKSVEQEVI 1500
1501 QSQLSHCVNLYKSLSEVKSEVEMVIKTGRQIVQKKQTENPKELDERVTAL 1550
1551 KLHYNELGAKVTERKQQLEKCLKLSRKMRKEMNVLTEWLAATDTELTKRS 1600
1601 AVEGMPSNLDSEVAWGKATQKEIEKQKAHLKSVTELGESLKMVLGKKETL 1650
1651 VEDKLSLLNSNWIAVTSRVEEWLNLLLEYQKHMETFDQNIEQITKWIIHA 1700
1701 DELLDESEKKKPQQKEDILKRLKAEMNDMRPKVDSTRDQAAKLMANRGDH 1750
1751 CRKVVEPQISELNRRFAAISHRIKTGKASIPLKELEQFNSDIQKLLEPLE 1800
1801 AEIQQGVNLKEEDFNKDMSEDNEGTVNELLQRGDNLQQRITDERKREEIK 1850
1851 IKQQLLQTKHNALKDLRSQRRKKALEISHQWYQYKRQADDLLKCLDEIEK 1900
1901 KLASLPEPRDERKLKEIDRELQKKKEELNAVRRQAEGLSENGAAMAVEPT 1950
1951 QIQLSKRWRQIESNFAQFRRLNFAQIHTLHEETMVVTTEDMPLDVSYVPS 2000
2001 TYLTEISHILQALSEVDHLLNTPELCAKDFEDLFKQEESLKNIKDNLQQI 2050
2051 SGRIDIIHKKKTAALQSATSMEKVKVQEAVAQMDFQGEKLHRMYKERQGR 2100
2101 FDRSVEKWRHFHYDMKVFNQWLNEVEQFFKKTQNPENWEHAKYKWYLKEL 2150
2151 QDGIGQRQAVVRTLNATGEEIIQQSSKTDVNILQEKLGSLSLRWHDICKE 2200
2201 LAERRKRIEEQKNVLSEFQRDLNEFVLWLEEADNIAITPLGDEQQLKEQL 2250
2251 EQVKLLAEELPLRQGILKQLNETGGAVLVSAPIRPEEQDKLEKKLKQTNL 2300
2301 QWIKVSRALPEKQGELEVHLKDFRQLEEQLDHLLLWLSPIRNQLEIYNQP 2350
2351 SQAGPFDIKEIEVTVHGKQADVERLLSKGQHLYKEKPSTQPVKRKLEDLR 2400
2401 SEWEAVNHLLRELRTKQPDRAPGLSTTGASASQTVTLVTQSVVTKETVIS 2450
2451 KLEMPSSLLLEVPALADFNRAWTELTDWLSLLDRVIKSQRVMVGDLEDIN 2500
2501 EMIIKQKATLQDLEQRRPQLEELITAAQNLKNKTSNQEARTIITDRIERI 2550
2551 QIQWDEVQEQLQNRRQQLNEMLKDSTQWLEAKEEAEQVIGQVRGKLDSWK 2600
2601 EGPHTVDAIQKKITETKQLAKDLRQRQISVDVANDLALKLLRDYSADDTR 2650
2651 KVHMITENINTSWGNIHKRVSEQEAALEETHRLLQQFPLDLEKFLSWITE 2700
2701 AETTANVLQDASRKEKLLEDSRGVRELMKPWQDLQGEIETHTDIYHNLDE 2750
2751 NGQKILRSLEGSDEAPLLQRRLDNMNFKWSELQKKSLNIRSHLEASSDQW 2800
2801 KRLHLSLQELLVWLQLKDDELSRQAPIGGDFPAVQKQNDIHRAFKRELKT 2850
2851 KEPVIMSTLETVRIFLTEQPLEGLEKLYQEPRELPPEERAQNVTRLLRKQ 2900
2901 AEEVNAEWDKLNLRSADWQRKIDEALERLQELQEAADELDLKLRQAEVIK 2950
2951 GSWQPVGDLLIDSLQDHLEKVKALRGEIAPLKENVNRVNDLAHQLTTLGI 3000
3001 QLSPYNLSTLEDLNTRWRLLQVAVEDRVRQLHEAHRDFGPASQHFLSTSV 3050
3051 QGPWERAISPNKVPYYINHETQTTCWDHPKMTELYQSLADLNNVRFSAYR 3100
3101 TAMKLRRLQKALCLDLLSLSAACDALDQHNLKQNDQPMDILQIINCLTTI 3150
3151 YDRLEQEHNNLVNVPLCVDMCLNWLLNVYDTGRTGRIRVLSFKTGIISLC 3200
3201 KAHLEDKYRYLFKQVASSTGFCDQRRLGLLLHDSIQIPRQLGEVASFGGS 3250
3251 NIEPSVRSCFQFANNKPEIEAALFLDWMRLEPQSMVWLPVLHRVAAAETA 3300
3301 KHQAKCNICKECPIIGFRYRSLKHFNYDICQSCFFSGRVAKGHKMHYPMV 3350
3351 EYCTPTTSGEDVRDFAKVLKNKFRTKRYFAKHPRMGYLPVQTVLEGDNME 3400
3401 TPVTLINFWPVDSAPASSPQLSHDDTHSRIEHYASRLAEMENSNGSYLND 3450
3451 SISPNESIDDEHLLIQHYCQSLNQDSPLSQPRSPAQILISLESEERGELE 3500
3501 RILADLEEENRNLQAEYDRLKQQHEHKGLSPLPSPPEMMPTSPQSPRDAE 3550
3551 LIAEAKLLRQHKGRLEARMQILEDHNKQLESQLHRLRQLLEQPQAEAKVN 3600
3601 GTTVSSPSTSLQRSDSSQPMLLRVVGSQTSESMGEEDLLSPPQDTSTGLE 3650
3651 EVMEQLNNSFPSSRGRNAPGKPMREDTM 3678
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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