 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q63ZW7 from www.uniprot.org...
The NucPred score for your sequence is 0.51 (see score help below)
1 MPENPAAEKMQVLQVLDRLRGKLQEKGDTTQNEKLSAFYETLKSPLFNQI 50
51 LTLQQSIKQLKGQLSHIPSDCSANFDFSRKGLLVFTDGSITNGNAQRPCS 100
101 NVTASELLPWTQKSASEDFNSVIQQMAQGRHVEYIDIERPSTGGLGFSVV 150
151 ALRSQSLGLIDIFVKEVHPGSVADRDHRLKENDQILAINDTPLDQNISHQ 200
201 QAIALLQQATGSLRLVVAREVGHTQGRASTSSADTTLPETVCWGHTEEVE 250
251 LINDGSGLGFGIVGGKSSGVVVRTIVPGGLADRDGRLQTGDHILKIGGTN 300
301 VQGMTSEQVAQVLRNCGNSVRMLVARDPVGEIAVTPPTPVSLPVALPAVA 350
351 TRTLDSDRSPFETYSVELVKKDGQSLGIRIVGYVGTAHPGEASGIYVKSI 400
401 IPGSAAYHNGQIQVNDKIVAVDGVNIQGFANQDVVEVLRNAGQVVHLTLV 450
451 RRKTSLSASPFEHSSSRETVAEPPKVPERAGSPKPEANLSVEAEEIGERL 500
501 DNLKNNTVQALEKPDVYPEKVPGSPENELKSRWENLLGPDYEVMVATLDA 550
551 QIADDEELQKYSKLLPIHTLRLGMEVDSFDGHHYISSVAPGGPVDTLNLL 600
601 QPEDELLEVNGMQLYGKSRREAVSFLKEVPPPFTLVCCRRLFDDEASVDE 650
651 PRTMEPALLEAEVDHSVDVNIEDDDDGELALWSPEVKTVELVKDCKGLGF 700
701 SILDYQDPLDPTRSVIVIRSLVADGVAERSGELLPGDRLVSVNEFSLDNA 750
751 TLAEAVEVLKAVPPGVVHLGICKPLVEDEKEERFSLHSNNNGDSSEPADA 800
801 VHEIHSSLILEAPQGFRDEPYLEELVDEPFLDLGKSLQFQQKDVDSSSEA 850
851 WEMHEFLSPPLDGRGEEREMLVDEEYELYQDHLRAMESNPPPPHIREAAP 900
901 ASPVLELQAGTQWLHANLSGGERLECHDAESMMSAYPQEMQQYSYSTADM 950
951 MEETFGLDSRAPIPSSEGNGQHGRFDDMGHLHSLTSSSLDLGMMIPSDLQ 1000
1001 GPGVLVDLPAVAQRREQEDLPLYRLPSARVVTKPSSHMGLVSSRHANAAC 1050
1051 ELPEREEGEGEETPNFSHWGPPRIVEIFREPNVSLGISIVGGQTVIKRLK 1100
1101 NGEELKGIFIKQVLEDSPAGKTNALKTGDKILEVSGVDLQNASHAEAVEA 1150
1151 IKSAGNPVVFVVQSLSSTPRVIPTVNNKGKTPAPNQDQNTQERKAKRHGT 1200
1201 APPPMKLPPPYRAPSADMEGSEEDCALTDKKIRQRYADLPGELHIIELEK 1250
1251 DKNGLGLSLAGNKDRSRMSIFVVGINPEGPAAADGRMRIGDELLEINNQI 1300
1301 LYGRSHQNASAIIKTAPTRVKLVFIRNEDAVSQMAVAPFPELSHSPSPVE 1350
1351 DLGGTELVSSEEESSVDAKHLPEPESSKPEDLSQVVDDNMVAEQQKESES 1400
1401 PDSAACQIKQQTYSTQVSSSSQDSPSSPAPLCQSAHADVTGSGNFQAPLP 1450
1451 VDPAPLSVDPATCPIVPGQEMIIEISKGRSGLGLSIVGGKDTPLDAIVIH 1500
1501 EVYEEGAAARDGRLWAGDQILEVNGVDLRSSSHEEAITALRQTPQKVRLV 1550
1551 VYRDEAQYRDEENLEVFLVDLQKKTGRGLGLSIVGKRSGSGVFISDIVKG 1600
1601 GAADLDGRLIRGDQILSVNGEDMRHASQETVATILKCVQGLVQLEIGRLR 1650
1651 AGSWAASRKTSQNSQGDQHSAHSSCRPSFAPVITSLQNLVGTKRSSDPPQ 1700
1701 KCTEEEPRTVEIIRELSDALGISIAGGKGSPLGDIPIFIAMIQANGVAAR 1750
1751 TQKLKVGDRIVSINGQPLDGLSHTDAVNLLKNAFGRIILQVVADTNISAI 1800
1801 ATQLEIMSAGSQLGSPTADRHPEDTEEQMQRTAD 1834
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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