 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8IZQ1 from www.uniprot.org...
The NucPred score for your sequence is 0.88 (see score help below)
1 MNMVKRIMGRPRQEECSPQDNALGLMHLRRLFTELCHPPRHMTQKEQEEK 50
51 LYMMLPVFNRVFGNAPPNTMTEKFSDLLQFTTQVSRLMVTEIRRRASNKS 100
101 TEAASRAIVQFLEINQSEEASRGWMLLTTINLLASSGQKTVDCMTTMSVP 150
151 STLVKCLYLFFDLPHVPEAVGGAQNELPLAERRGLLQKVFVQILVKLCSF 200
201 VSPAEELAQKDDLQLLFSAITSWCPPYNLPWRKSAGEVLMTISRHGLSVN 250
251 VVKYIHEKECLSTCVQNMQQSDDLSPLEIVEMFAGLSCFLKDSSDVSQTL 300
301 LDDFRIWQGYNFLCDLLLRLEQAKEAESKDALKDLVNLITSLTTYGVSEL 350
351 KPAGITTGAPFLLPGFAVPQPAGKGHSVRNVQAFAVLQNAFLKAKTSFLA 400
401 QIILDAITNIYMADNANYFILESQHTLSQFAEKISKLPEVQNKYFEMLEF 450
451 VVFSLNYIPCKELISVSILLKSSSSYHCSIIAMKTLLKFTRHDYIFKDVF 500
501 REVGLLEVMVNLLHKYAALLKDPTQALNEQGDSRNNSSVEDQKHLALLVM 550
551 ETLTVLLQGSNTNAGIFREFGGARCAHNIVKYPQCRQHALMTIQQLVLSP 600
601 NGDDDMGTLLGLMHSAPPTELQLKTDILRALLSVLRESHRSRTVFRKVGG 650
651 FVYITSLLVAMERSLSCPPKNGWEKVNQNQVFELLHTVFCTLTAAMRYEP 700
701 ANSHFFKTEIQYEKLADAVRFLGCFSDLRKISAMNVFPSNTQPFQRLLEE 750
751 DVISIESVSPTLRHCSKLFIYLYKVATDSFDSRAEQIPPCLTSESSLPSP 800
801 WGTPALSRKRHAYHSVSTPPVYPPKNVADLKLHVTTSSLQSSDAVIIHPG 850
851 AMLAMLDLLASVGSVTQPEHALDLQLAVANILQSLVHTERNQQVMCEAGL 900
901 HARLLQRCSAALADEDHSLHPPLQRMFERLASQALEPMVLREFLRLASPL 950
951 NCGAWDKKLLKQYRVHKPSSLSYEPEMRSSMITSLEGLGTDNVFSLHEDN 1000
1001 HYRISKSLVKSAEGSTVPLTRVKCLVSMTTPHDIRLHGSSVTPAFVEFDT 1050
1051 SLEGFGCLFLPSLAPHNAPTNNTVTTGLIDGAVVSGIGSGERFFPPPSGL 1100
1101 SYSSWFCIEHFSSPPNNHPVRLLTVVRRANSSEQHYVCLAIVLSAKDRSL 1150
1151 IVSTKEELLQNYVDDFSEESSFYEILPCCARFRCGELIIEGQWHHLVLVM 1200
1201 SKGMLKNSTAALYIDGQLVNTVKLHYVHSTPGGSGSANPPVVSTVYAYIG 1250
1251 TPPAQRQIASLVWRLGPTHFLEEVLPSSNVTTIYELGPNYVGSFQAVCMP 1300
1301 CKDAKSEGVVPSPVSLVPEEKVSFGLYALSVSSLTVARIRKVYNKLDSKA 1350
1351 IAKQLGISSHENATPVKLIHNSAGHLNGSARTIGAALIGYLGVRTFVPKP 1400
1401 VATTLQYVGGAAAILGLVAMASDVEGLYAAVKALVCVVKSNPLASKEMER 1450
1451 IKGYQLLAMLLKKKRSLLNSHILHLTFSLVGTVDSGHETSIIPNSTAFQD 1500
1501 LLCDFEVWLHAPYELHLSLFEHFIELLTESSEASKNAKLMREFQLIPKLL 1550
1551 LTLRDMSLSQPTIAAISNVLSFLLQGFPSSNDLLRFGQFISSTLPTFAVC 1600
1601 EKFVVMEINNEEKLDTGTEEEFGGLVSANLILLRNRLLDILLKLIYTSKE 1650
1651 KTSINLQACEELVKTLGFDWIMMFMEEHLHSTTVTAAMRILVVLLSNQSI 1700
1701 LIKFKEGLSGGGWLEQTDSVLTNKIGTVLGFNVGRSAGGRSTVREINRDA 1750
1751 CHFPGFPVLQSFLPKHTNVPALYFLLMALFLQQPVSELPENLQVSVPVIS 1800
1801 CRSKQGCQFDLDSIWTFIFGVPASSGTVVSSIHNVCTEAVFLLLGMLRSM 1850
1851 LTSPWQSEEEGSWLREYPVTLMQFFRYLYHNVPDLASMWMSPDFLCALAA 1900
1901 TVFPFNIRPYSEMVTDLDDEVGSPAEEFKAFAADTGMNRSQSEYCNVGTK 1950
1951 TYLTNHPAKKFVFDFMRVLIIDNLCLTPASKQTPLIDLLLEASPERSTRT 2000
2001 QQKEFQTYILDSVMDHLLAADVLLGEDASLPITSGGSYQVLVNNVFYFTQ 2050
2051 RVVDKLWQGMFNKESKLLIDFIIQLIAQSKRRSQGLSLDAVYHCLNRTIL 2100
2101 YQFSRAHKTVPQQVALLDSLRVLTVNRNLILGPGNHDQEFISCLAHCLIN 2150
2151 LHVGSNVDGFGLEAEARMTTWHIMIPSDIEPDGSYSQDISEGRQLLIKAV 2200
2201 NRVWTELIHSKKQVLEELFKVTLPVNERGHVDIATARPLIEEAALKCWQN 2250
2251 HLAHEKKCISRGEALAPTTQSKLSRVSSGFGLSKLTGSRRNRKESGLNKH 2300
2301 SLSTQEISQWMFTHIAVVRDLVDTQYKEYQERQQNALKYVTEEWCQIECE 2350
2351 LLRERGLWGPPIGSHLDKWMLEMTEGPCRMRKKMVRNDMFYNHYPYVPET 2400
2401 EQETNVASEIPSKQPETPDDIPQKKPARYRRAVSYDSKEYYMRLASGNPA 2450
2451 IVQDAIVESSEGEAAQQEPEHGEDTIAKVKGLVKPPLKRSRSAPDGGDEE 2500
2501 NQEQLQDQIAEGSSIEEEEKTDNATLLRLLEEGEKIQHMYRCARVQGLDT 2550
2551 SEGLLLFGKEHFYVIDGFTMTATREIRDIETLPPNMHEPIIPRGARQGPS 2600
2601 QLKRTCSIFAYEDIKEVHKRRYLLQPIAVEVFSGDGRNYLLAFQKGIRNK 2650
2651 VYQRFLAVVPSLTDSSESVSGQRPNTSVEQGSGLLSTLVGEKSVTQRWER 2700
2701 GEISNFQYLMHLNTLAGRSYNDLMQYPVFPWILADYDSEEVDLTNPKTFR 2750
2751 NLAKPMGAQTDERLAQYKKRYKDWEDPNGETPAYHYGTHYSSAMIVASYL 2800
2801 VRMEPFTQIFLRLQGGHFDLADRMFHSVREAWYSASKHNMADVKELIPEF 2850
2851 FYLPEFLFNSNNFDLGCKQNGTKLGDVILPPWAKGDPREFIRVHREALEC 2900
2901 DYVSAHLHEWIDLIFGYKQQGPAAVEAVNVFHHLFYEGQVDIYNINDPLK 2950
2951 ETATIGFINNFGQIPKQLFKKPHPPKRVRSRLNGDNAGISVLPGSTSDKI 3000
3001 FFHHLDNLRPSLTPVKELKEPVGQIVCTDKGILAVEQNKVLIPPTWNKTF 3050
3051 AWGYADLSCRLGTYESDKAMTVYECLSEWGQILCAICPNPKLVITGGTST 3100
3101 VVCVWEMGTSKEKAKTVTLKQALLGHTDTVTCATASLAYHIIVSGSRDRT 3150
3151 CIIWDLNKLSFLTQLRGHRAPVSALCINELTGDIVSCAGTYIHVWSINGN 3200
3201 PIVSVNTFTGRSQQIICCCMSEMNEWDTQNVIVTGHSDGVVRFWRMEFLQ 3250
3251 VPETPAPEPAEVLEMQEDCPEAQIGQEAQDEDSSDSEADEQSISQDPKDT 3300
3301 PSQPSSTSHRPRAASCRATAAWCTDSGSDDSRRWSDQLSLDEKDGFIFVN 3350
3351 YSEGQTRAHLQGPLSHPHPNPIEVRNYSRLKPGYRWERQLVFRSKLTMHT 3400
3401 AFDRKDNAHPAEVTALGISKDHSRILVGDSRGRVFSWSVSDQPGRSAADH 3450
3451 WVKDEGGDSCSGCSVRFSLTERRHHCRNCGQLFCQKCSRFQSEIKRLKIS 3500
3501 SPVRVCQNCYYNLQHERGSEDGPRNC 3526
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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