 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q6VNB8 from www.uniprot.org...
The NucPred score for your sequence is 0.84 (see score help below)
1 MNMVKRIMGRPRQEECSPQDNALGLMHLRRLFTELCHPPRHMTQKEQEEK 50
51 LYMMLPVFNRVFGNAPPNTMTEKFSDLLQFTTQVSRLMVTEIRRRASNKS 100
101 TEAASRAIVQFLEINQSEEASRGWMLLTTINLLASSGQKTVDCMTTMSVP 150
151 STLVKCLYLFFDLPHVPEAGGGAQNELPLAERRGLLQKAFVQILVKLCSF 200
201 VSPAEELAQKDDLQLLFSAITSWCPPYNLPWRKSAGEVLMTISRHGLSVN 250
251 VVKYIHEKECLSTCVQNMQQSDDLSPLEIVEMFAGLSCFLKDSSDVSQTL 300
301 LDDFRIWQGYNFLCDLLLRLEQGKEAECRDALKDLVSLVTSLTTYGVSEL 350
351 KPAGVTTGAPFLLPGFAVPQPAGKGHSVRNIQAFAVLQNAFLKAKTNFLA 400
401 QIILDAITNIYMADNANYFILESQHTLSQFAEKISKLPEVQNKYFEMLEF 450
451 VVFSLNYIPCKELISVSILLKSSSSYHCSIIAMKTLLKFTRHDYIFKDVF 500
501 REVGLLEVMVNLLHKYAALLKDPAQALNEQGDSRNNSSVEDQKHLALLVM 550
551 EALTVLLQGSNTNAGIFREFGGARCAHNIVKYPQCRQHALMTIQQLVLSP 600
601 NGEDDMGTLLGLMHSAPPTELQLKTDILRALLSVLRESHRSRTVFRKVGG 650
651 FVYITSLLVAMERSLSSPPKNGWEKVSQSQVLELLHTVFCTLTAALRYEP 700
701 ANSHFFKTEIQYEKLADAVRFLGCFSDLRKISAVNVFPSNTQPFQRLLEE 750
751 GAVSVDSVSPTLRHCSKLFIYLYKVATDSFDSHAEQIPPCLTSESSLPSP 800
801 WGTPALSRKRHAFHCVSTPPVYPAKNVTDLKLQVTSSPLQSSDAVIIHPG 850
851 AMLAMLDLLASVGSVTQPEHALDLQLAVANILQSLVHTERNQQVMCEAGL 900
901 HARLLQRCGAALADEDHSLHPPLQRMFERLASQALEPMVLREFLRLASPL 950
951 NCGAWDKKLLKQYRVHKPSSLSFEPEMRSSVITSLEGLGSDNVFSSHEDN 1000
1001 HYRISKSLVKSAEGSTVPLTRVKCLVSMTTPHDIRLHGSSVTPAFVEFDT 1050
1051 SLEGFGCLFLPSLAPHNAPTNNTVTTGLTDGAVVSGMGSGERFFPPPSGL 1100
1101 SYSCWFCIEHFSSPPNNHPVRLLTVVRRANSSEQHYVCLAIVLSAKDRSL 1150
1151 IVSTKEELLQNYVDDFSEESSFYEILPCCARFRCGELVVEGQWHHLALLM 1200
1201 SRGMLKNSTAALYLDGQLVSTVKLHYVHSTPGGSGSANPPVLSTVYAYVG 1250
1251 TPPAQRQIASLVWRLGPTHFLEEVLPPSSVTTIYELGPNYVGSFQAVCVP 1300
1301 CKDAKSEGVTPSPVSLVAEEKVSFGLYALSVSSLTVARIRKVYNKLDSKA 1350
1351 IAKQLGISSHENATPVKLVHNAAGHLNGPARTIGAALIGYLGVRTFVPKP 1400
1401 VATTLQYIGGAAAILGLVAMASDVEGLYAAVKALVCVVKSNPLASKEMER 1450
1451 IKGYQLLAMLLKKKRSLLNSHILHLTFSLVGTVDSGHETSIIPNSTAFQD 1500
1501 LLCDFEVWLHAPYELHLSLFEHFIELLTESSEASKNAKLMREFQLIPKLL 1550
1551 LTLRDMSLSQPTIAAISNVLSFLLQGFPNSNDLLRFGQFISSTLPTFAVC 1600
1601 EKFVVMEINNEEKPDPGAEEEFGGLVSANLILLRNRLLDILLKLVYTSKE 1650
1651 KTNINLQACEELVRTLGFDWIMMFMEEHLHPTTVTAAMRILVVLLSNQSI 1700
1701 LIKFKEGLSGGGWLEQTDSVLTNKIGTVLGFNVGRSAGGRSTVREINRDA 1750
1751 CHFPGFLVLQSFLPKHTNVPALYFLLMALFLQQPVSELPENLQVSVPVTS 1800
1801 SRCKQGCQFDLDSIWTFIFGVPASSGTVVSSIHNVCTESAFLLLGMLRSM 1850
1851 LNSPWQSEEEGSWLREYPVTLMQFFRYLYHNVPDLASMWLSPDFLCALAA 1900
1901 TVFPFNIRPYSEMVTDLDDEVGSPAEEFKAFAADTGMNRSQSEYCNVGTK 1950
1951 TYLTNHPAKKFVFDFMRVLIIDNLCLTPASKQTPLIDLLLEASPERSTRT 2000
2001 QQKEFQTHVLDSVMDHLLAADVLLGEDASLPITSGGSYQVLVNNVFYFTQ 2050
2051 RVVDKLWQGMFNKESKLLIDFIIQLIAQSKRRSQGLSLDAVYHCLNRTIL 2100
2101 YQFSRAHKTVPQQVALLDSLRVLTVNRNLILGPGNHDQEFISCLAHCLIN 2150
2151 LHAGSVEGFGLEAEARMTTWHIMIPSDIEPDGGYSQDISEGRQLLIKAVN 2200
2201 RVWTELIHSKKQVLEELFKVSLPVNDRGHVDIALARPLIEEAGLKCWQNH 2250
2251 LAHEKKCISRGEALVPTTQSKLSRVSSGFGLSKLTGSRRNRKESGLHKHS 2300
2301 PSPQEISQWMFTHIAVVRDLVDTQYKEYQERQQNALKYVTEEWCQIECEL 2350
2351 LRERGLWGPPIGSHLDKWMLEMTEGPCRMRKKMVRNDMFYNHYPYVPETE 2400
2401 QEASVGKPARYRRAISYDSKEYYLRLASGNPAIVQDAIVESSEGEATQQE 2450
2451 PEHGEDTIAKVKGLVKPPLKRSRSAPDGGDEETQEQLQDQIAESGSIEEE 2500
2501 EKTDNATLLRLLEEGEKIQHMYRCARVQGLDTSEGLLLFGKEHFYVIDGF 2550
2551 TMTATREIRDIETLPPNMHEPIIPRGARQGPSQLKRTCSIFAYEDIKEVH 2600
2601 KRRYLLQPIAVEVFSGDGRNYLLAFQKGIRNKVYQRFLAVVPSLTDSSES 2650
2651 VSGQRPNTSVEQGSGLLSTLVGEKSVTQRWERGEISNFQYLMHLNTLAGR 2700
2701 SYNDLMQYPVFPWILSDYDSEEVDLTNPKTFRNLAKPMGAQTDERLAQYK 2750
2751 KRYKDWEDPNGETPAYHYGTHYSSAMIVASYLVRMEPFTQIFLRLQGGHF 2800
2801 DLADRMFHSVREAWYSASKHNMADVKELIPEFFYLPEFLFNSNNFDLGCK 2850
2851 QNGTKLGDVILPPWAKGDPREFIRVHREALECDYVSAHLHEWIDLIFGYK 2900
2901 QQGPAAVEAVNVFHHLFYEGQVDIYNINDPLKETATIGFINNFGQIPKQL 2950
2951 FKKPHPPKRVRSRLNGDNIGISVPPGATSDKIFFHHLDNLRPSLTPVKEL 3000
3001 KEPVGQIVCTDKGILAVEQNKVLIPPAWNKTFAWGYADLSCRLGTYESDK 3050
3051 AVTVYECLSEWGQILCAVCPNPKLVITGGTSTVVCVWEMGTSKEKAKPLT 3100
3101 LKQALLGHTDTVTCATASLAYHIIVSGSRDRTCIIWDLNKLSFLTQLRGH 3150
3151 RAPVSALCINELTGDIVSCAGTYIHVWSINGNPIVSVNTFTGRSQQIVCC 3200
3201 CMSEMNEWDTQNVIVTGHSDGVVRFWRMEFLQVPETPAPEPVEDLEMQEG 3250
3251 CPEAQIGQQAQDDDSSDSETEEPSVSQDPKDTSSQPSSTSHRPRAASCRA 3300
3301 TATWCTDSGSDDSRRWSDQLSLDEKDGFIFVNYSEGQTRAHLQGPLAHPH 3350
3351 PNPIEARSYSRLKPGYRWERQLVFRSKLTMHTAFDRKDNTHPAEVTALGV 3400
3401 SKDHSRILVGDSRGRVFSWSVSDQPGRSAADHWVKDEGGDSCSGCSVRFS 3450
3451 LTERRHHCRNCGQLFCQKCSRFQSEIKRLKISSPVRVCQNCYYSLQHERG 3500
3501 AEDGPRNC 3508
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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