![SBC logo](/sbclogo150.png) | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching O97592 from www.uniprot.org...
The NucPred score for your sequence is 0.98 (see score help below)
1 MLWWEEVEDCYEREDVQKKTFTKWVNAQFSKFGKQHIENLFSDLQDGRRL 50
51 LDLLEGLTGQKLPKEKGSTRVHALNNVNKALRVLQKNNVDLVNIGSTDIV 100
101 DGNHKLTLGLIWNIILHWQVKNVMKNIMAGLQQTNSEKILLSWVRQSTRN 150
151 YPQVNVINFTTSWSDGLALNALIHSHRPDLFDWNSVVCQQSATQRLEHAF 200
201 NIAKYQLGIEKLLDPEDVATTYPDKKSILMYITSLFQVLPQQVSIEAIQE 250
251 VEMLPRPSQVTREEHFQIHHQMHYSQQITVSLAQGYERAPSFPKPRFKSY 300
301 AYTQAAYVTTSDPTRSPLPSQHLETPEDKSFGRSLTETEANLDSYQTALE 350
351 EVLSWLLSAEDALQAQGEISNDVEEVKEQFHTHEGYMMDLTSHQGRVGNV 400
401 LQLGSQLIGTGKLSEDEETEVQEQMNLLNSRWECLRVASMEKQSNLHKVL 450
451 MDLQNQQLKELNDWLTKTEERTRKMEKEPLGPDIEDLKRQVQQHKVLQED 500
501 LEQEQVRVNSLTHMVVVVDESSGDHATAALEEQLKVLGDRWANICRWTED 550
551 RWVLLQDILLKWQRFTEEQCLFSAWLSEKEDAVNKIHTTGFKDQSEVLSN 600
601 LQKLAVLKTDLEKKKQTMDKLCSLNQDLLSALKNTVVAHKMEAWLDNFAQ 650
651 RWDNLVQKLEKSSAQISQAVTTTQPSLTQTTVMETVTMVTTREHILVKHA 700
701 QEELPPPPPQKKRQIIVDSEIRKRLDVDITELHSWITRSEAVLQSPEFAI 750
751 YRKEGNFSDLKEKVNAIEREKAEKFRKLQDASRSAQALVEQMVNEGVNAD 800
801 SIKQASEQLNSRWIEFCQLLSERLNWLEYQNNIITFYNQLQQLEQMTTTA 850
851 ENWLKTQPTTTSEPTAIKSQLKICKDEINRLSALQPQIERLKIQSIALKE 900
901 KGQGPMFLDADFVAFTNHFNQVFADVQAREKELQTIFDSLPPMRYQETMS 950
951 TILTWIQQSETKLSIPQVTVTEYDIMEQRLGELQALQSSLQEQQNGLNYL 1000
1001 STTVKEMSKKAPLSDISRKYQSEFEEIEGRWKKLSSQLVEHCQKLEEQMA 1050
1051 KLRKIQNHIKTLKKWITEVDVFLKEEWPALGDSEILKRQLKQCRLLVNDI 1100
1101 QTIQPSLNSVNEGAQKMKNEAEPEFAGRLETELRELNTQWDYMCRQVYAR 1150
1151 KEALKGGLDKTVSLQKDLSEMHEWMTQAEEEYLERDFEYKTPDELQTAVE 1200
1201 EMKRAKEEAQQKEAKVKLLTESVNSVIAQAPPAAQEALKKELDTLTTNYQ 1250
1251 WLCTRLNGKCKTLEEVWACWHELLSYLEKANKWLSEVEVKLKTTENISGG 1300
1301 AEEIAEVLDSLENLMQHSEDNPNQIRILAQTLTDGGVMDELINEELETFN 1350
1351 SRWRELHEEAVRRQKLLEQSIQSAQEIEKSLHLIQESLSSIDKQLAAYIA 1400
1401 DKVDAAQMPQEAQKIQSDLTSHEISLEEMKKHNQGKETAQRVLSQIDVAQ 1450
1451 KKLQDVSMKFRLFQKPANFEQRLQESKMILDEVKMHLPALETKSVEQEVV 1500
1501 QSQLNHCVNLYKSLSEVKSEVEMVIKTGRQIVQKKQTENPKELDERVTAL 1550
1551 KLHYNELGAKVTERKQQLEKCLKLSRKMRKEMNALTEWLAATDMELTKRS 1600
1601 AVEGMPSNLDSEVAWGKATQKEIEKQKVHLKSVTEVGEALKTVLGKKEML 1650
1651 VEDKLSLLNSNWIAVTSRAEEWLNLLLEYQKHMETFDQNVDYITNWIIQA 1700
1701 DALLDESEKKKPQQKEDILKRLKAEMNDIRPKVDSTRDQAANLMANRGDH 1750
1751 CRKVVEPKISELNHRFAAISHRIKTGKASIPLKELEQFNSDIQKLLEPLE 1800
1801 AEIQQGVNLKEEDFNKDMSEDNEGTVKELLQRGDNLQQRITDERKREEIK 1850
1851 IKQQLLQTKHNALKDLRSQRRKKALEISHQWYQYKRQADDLLKCLDDIEK 1900
1901 KLASLPEPRDERKIKEIDRELQKKKEELNAVRRQAEGLSEDGAAMAVEPT 1950
1951 QIQLSKRWREIESKFAQFRRLNFAQIHTVHEESVVAMTEDMPLEISYVPS 2000
2001 TYLTEITHVSQALSEVEELLNAPDLCAQDFEDLFKQEESLKNIKDSLQQI 2050
2051 SGRIDIIHNKKTAALHSATPAERAKLQEALSRLDFQWERVNNMYKDRQGR 2100
2101 FDRSVEKWRRFHYDMKILNQWLTEAEQFLKKTQIPENWEHAKYKWYLKEL 2150
2151 QDGIGQRQSVVRVLNATGEEIIQQSSKTDASILQEKLGSLNLRWQEVCKQ 2200
2201 LAERKKRLEEQKNILSEFQRDVNEFVLWLEEADNVANIPLEPGNEQQLKE 2250
2251 KLEQVKLLAEELPLRQGILKQLNETGGTVLVSAPLSPEEQDKLENKLKQT 2300
2301 NLQWIKVSRNLPEKQEEIEAHVKDLGQLEEQLNHLLLWLSPIRNQLEIYN 2350
2351 QPNQTGPFDIKEIEVAVQAKQPDVEGILSKGQHLYKEKPATQPAKRKLED 2400
2401 LSSDWKVVTQLLQELRAKQPGPAPGLTTVRAPPSQTVTLVTQPAVTKETA 2450
2451 ISKLEMPSSLLLEVPALADFNRAWTELTDWLSLLDRVIKSQRVMVGDLED 2500
2501 INEMIIKQKATLQDLEQRRPQLEELITAAQNLKNKTSNQEARTIITDRIE 2550
2551 RIQSQWDEVQEHLQNRRLQLTEMLKDSTQWLEAKEEAEQVLGQARAKLES 2600
2601 WKEAPYTVDAIQKKITETKQLAKDLRQWQINVDVANDLALKLLRDYSADD 2650
2651 TRKVHMITENINASWASIHKRLSEREAALEETHRLLQQFPLDLEKFLAWL 2700
2701 TEAETTANVLQDATHKERLLEDSKGVRELMKQWQDLQGEIEAHTDIYHNL 2750
2751 DENGQKVLRSLEGSDDAALLQRRLDNMNFKWSELRKKSLNIRSHLEASSD 2800
2801 QWKRLHLSLQELLVWLQLKDDELSRQAPIGGDFPAVQKQNDVHRAFKREL 2850
2851 KTKEPVIMSTLETVRIFLTEQPLEGLEKLYQEPRELPPEERAQNVTRLLR 2900
2901 KQAEEVNTQWEKLNVHSADWQRKIDEALERLQELQEATDELDLKLRQAEV 2950
2951 IKGSWQPVGDLLIDSLQDHLEKVKALRGEITPLKENVSYVNDLARQLTTL 3000
3001 GIQLSPYNLNTLEDLNTRWKLLQVAIEDRIRQLHEAHRDFGPASQHFLST 3050
3051 SVQGPWERAISPNKVPYYINHETQTTCWDHPKMTELYQSLADLNNVRFSA 3100
3101 YRTAMKLRRLQKALCLDLLSLSAACDALDQHNLKQNDQPMDILQVINCLT 3150
3151 TIYDRLEQEHNNLVNVPLCVDMCLNWLLNVYDTGRTGRIRVLSFKTGIIS 3200
3201 LCKAHLEDKYRYLFKQVASSTGFCDQRRLGLLLHDSIQIPRQLGEVASFG 3250
3251 GSNIEPSVRSCFQFANNKPEIEAALFLDWMRLEPQSMVWLPVLHRVAAAE 3300
3301 TAKHQAKCNICKECPIIGFRYRSLKHFNYDICQSCFFSGRVAKGHKMHYP 3350
3351 MVEYCTPTTSGEDVRDFAKVLKNKFRTKRYFAKHPRMGYLPVQTVLEGDN 3400
3401 METPVTLINFWPVDSAPASSPQLSHDDTHSRIEHYASRLKKMENSNGSYL 3450
3451 NDSISPNESIDDEHLLIQHYWRSLNQESPLSQPRSPAQILISLESEERGE 3500
3501 LERILADLEGRNRNLQAEYDRLKQQHEHKGLSPLPSPPEMMPTSPQSPRD 3550
3551 AELIAEAKLLRQHKGRLEARMQILEDHNKQLESQLHRLRQLLEQPQAEAK 3600
3601 VNGTTVSSPSTSLQRSDSSQPMLLRVVGSQTSESMGEEDLLSPPQDTSTG 3650
3651 LEEVMEQLNHSFPSSRGRNTPGKPMREDTM 3680
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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