 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q5EAK6 from www.uniprot.org...
The NucPred score for your sequence is 0.78 (see score help below)
1 MSALLNEIQRILGDLQSGKAASRNKGIQQLDEKLSSCREDLDKLFLSKTS 50
51 DISWTTIFEASKEALFKQAGNLEDVNEKVFKTLAGKNYLYDNVLEKITQF 100
101 NLEAGSQTSGNGHFLAKTSIFSAFEDGIKMRVVVKYFGDRILSLLEKGIY 150
151 SSVSYVRDLKINEYSRILSYLFELNVDMDEVLRTRILKCITRTVSLAKDR 200
201 VQLHVDLVEYLPELSSFALSAFGARKTEIVRVYLIFASELAVNYNHQLNV 250
251 HMQEILPKLCEYHDEDAFRDDTRNLFFQCVSKSLHSMYLKMDMCDFNTLG 300
301 VPVHEKWPQTLLRLKTIVNVEIRKNSWARCKNALLSNNKFSDPFIKMSAL 350
351 AMYIVLWHLETKKADENGEGDAPKKIPKPADKMETIFSLIDKKENTFNDV 400
401 WLAIFTEILQLSSVILNVANYQMALTTVAEIMQMYGNAKNLRNLRLCLAH 450
451 LLTKEQELLHSKSIREDFLGELWSQMANQLISETTTNSEEIKEKQLVLQM 500
501 LIRHNKLNQKLSSTLLNNIISNEMLKRNECLATIREIFIHADKCGQDKAS 550
551 ADLEPIIAWAYGSADRFIAAQMIHNIDSIDAQLQADTFAISIINFLDVQQ 600
601 LRQISQSEHIVPSTERNLLAYKYNEQLICFDKDYATPFESITHIQSETKN 650
651 CLIQSNYDCLMRGLNFEIAKENKPAAIIKNLNSLLKLICTMERLLHYKVF 700
701 DADTYTGCPLIKRIGLYLSHIEFQLKANGAEILDKSDLPEILRLEIYVLD 750
751 VFRTNLVLLDYLERQPIEMLVEFVGAALKLHSMQRERSVDADHGTITRLC 800
801 LNILAGLCAYNSHRDEAFEHIVKVTMRWHPQDVLIVTKMLCSCQTISEAS 850
851 SSWLVSKLKTLFQQHHQDAELMDKVVQHMPTIFYFVRHKENHLDDMLMAL 900
901 NSLLRIAIKKSYTSNLTAKIVRCVGLIAQRCPDIYLLENFAVICKSTAKF 950
951 ITMPTLEVRFATLFTFTILLESNCVTSDAIGHSRTHWDFCQELYESIEFK 1000
1001 KLTYNNEDAIQNSNALIVQMLIAIFLRSSFHQEIALKELLHHCALRRLTE 1050
1051 REFISLQSMSSCHRQTVRDLIRPFAAILLHHWSSKRWPISKFPYFLCYST 1100
1101 KSEFRKTHASEIMAYTFLYGKTEDIERCSKSISEELALPILASFLLIKNS 1150
1151 SCSESEGQNFKEHLQLLSENLSYSQLNATDVDLDLDILCYVISMLHDPQE 1200
1201 MMRLFGSLAICNRTASWYSLSGESLFKCLNFHIDPEMRPSMDSRIQSMTT 1250
1251 LQTKHSRVLVDIFGRLKTNCYSASFSSQALHDFFLYCEVADAVYDAARKN 1300
1301 ETIVTQCSFFVRDIWFFVVRLLIHTKFIRVQMAALTFLELLLNKHNFRLD 1350
1351 DYQNHFGDIAKLLSNFQLCCEAKEVREKTMSIVMYILESKKGHINLNSFL 1400
1401 EETTDCEFLKPLREDCKSSQPNIDRADVANYLRSFLLSPTPERLRDLRTY 1450
1451 IAEHKDKVQEHEKLLFGVINKLIQMTRDAHNKTTSIDSLKCLAQIGPLKI 1500
1501 STVSYYFQTDFEAFEKSNGEPMEAFLGVVCHSLDTSLFQFDPKTHEGLVS 1550
1551 VAIQVVNSKPGSNIMERYKNLRIFADKSTASTFLHSNKQIRRIDWLSILK 1600
1601 ATKSLSYEPWMCAFVSKVFQMCGWLGFDKLAATSFAFAKTCLLPFIKLLL 1650
1651 ENSLEHVESLSQMLDYFFEGFTSSTAPNSQEIFRNKRAIKKFLHICEYIR 1700
1701 IFNNWTIPINLSNVVMASNHCQAYFLSIMYLELWACSESPKSKADFLDNE 1750
1751 CFQDGAKKAYESIGCLDAIPGFVNPMRSRLDFLGHGSNLSTILLESDHLD 1800
1801 RASGQLCIDIMKGNGLWSFAKLQQHQNIEPDYEIFWRLGQWDSLTDPKHQ 1850
1851 QNQTVVRTSLDLEQEFKRHHFVALRSIGQREEENSLSAIEQAYSCVRDIL 1900
1901 MEISVECLQSVYKYLTWLCSLQQAEDFCQIQFGTQLDPASTTKIFRKWQT 1950
1951 ELELKYGNFSCKEYVIAHQIALLKLAGTRASRRMSEFYQKDPISTYLMKG 2000
2001 IEECKSAGKLNLAAKYTATLRELPNIRESIKISVLLEDAEINLKMGNQQI 2050
2051 AKAILDYVTNNNEFVYCVQRVPALRMQGEFLLDCNAETLSWVQSHKFNNS 2100
2101 LKLIDDFVQHRQTLSEKYRDIFDWHQLDAYASKQRTAAYATIAKYADREY 2150
2151 QQLHDYRHSQEYQTLKDIIEQNRQTAEKVTQRENQDRRVISVQMKRYASL 2200
2201 DEQQLNQIEEKLTEYLRLALTNYMAYCRLDSGFSSAAIYRIISLWFTNAT 2250
2251 SKQCQECIKDEILTVPSYKFICAANQLTARLNSKNTSLLKGLTDLLVQCG 2300
2301 KDHPYHTFYQLYPLVFAHLDGENSNTERSGIARKIIAMICEKNGTAGECS 2350
2351 KQLESLLPALITFANEGKTNDNRPVSDSVRNKQFDKVRRWRNLNAVHCPT 2400
2401 LELPVMPSKEYSIISVVKWTNETTQCGGLNAPVKIMCVCSDGKIRAQLVK 2450
2451 GKDDLRQDAVMQQVFGIVNELLNQDSEFIERKLKLRTYKVTPLSMRSGIL 2500
2501 EWCTNSVPVGHYLVVEGKGGAHARYRPNDWNNNKCRKLSSDHLKSPKETR 2550
2551 YAIYKKICENIKPVFHYFLLEKFPIPGVWFERRLAYTNSVATTSMVGYVL 2600
2601 GLGDRHTQNILVDQQTAEVIHIDFGIAFEQGKIQTTPETVPFRLTRDFVA 2650
2651 PMGICGTKGVFAKSCEATMHILRRYKSVFTTILEVLLYDPLFIWGVLKKK 2700
2701 QSPQQSGEESVNLVAQRALLLVQNKLDGREAGTMGDSNVEAQVERLINEA 2750
2751 TLPSNLCMLFPGWDPHL 2767
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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