 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching P04052 from www.uniprot.org...
The NucPred score for your sequence is 0.89 (see score help below)
1 MSTPTDSKAPLRQVKRVQFGILSPDEIRRMSVTEGGVQFAETMEGGRPKL 50
51 GGLMDPRQGVIDRTSRCQTCAGNMTECPGHFGHIDLAKPVFHIGFITKTI 100
101 KILRCVCFYCSKMLVSPHNPKIKEIVMKSRGQPRKRLAYVYDLCKGKTIC 150
151 EGGEDMDLTKENQQPDPNKKPGHGGCGHYQPSIRRTGLDLTAEWKHQNED 200
201 SQEKKIVVSAERVWEILKHITDEECFILGMDPKYARPDWMIVTVLPVPPL 250
251 AVRPAVVMFGAAKNQDDLTHKLSDIIKANNELRKNEASGAAAHVIQENIK 300
301 MLQFHVATLVDNDMPGMPRAMQKSGKPLKAIKARLKGKEGRIRGNLMGKR 350
351 VDFSARTVITPDPNLRIDQVGVPRSIAQNLTFPELVTPFNIDRMQELVRR 400
401 GNSQYPGAKYIVRDNGERIDLRFHPKSSDLHLQCGYKVERHLRDDDLVIF 450
451 NRQPTLHKMSMMGHRVKVLPWSTFRMNLSCTSPYNADFDGDEMNLHVPQS 500
501 METRAEVENIHITPRQIITPQANKPVMGIVQDTLTAVRKMTKRDVFITRE 550
551 QVMNLLMFLPTWDAKMPQPCILKPRPLWTGKQIFSLIIPGNVNMIRTHST 600
601 HPDEEDEGPYKWISPGDTKVMVEHGELIMGILCKKSLGTSAGSLLHICFL 650
651 ELGHDIAGRFYGNIQTVINNWLLFEGHSIGIGDTIADPQTYNEIQQAIKK 700
701 AKDDVINVIQKAHNMELEPTPGNTLRQTFENKVNRILNDARDKTGGSAKK 750
751 SLTEYNNLKAMVVSGSKGSNINISQVIACVGQQNVEGKRIPYGFRKRTLP 800
801 HFIKDDYGPESRGFVENSYLAGLTPSEFYFHAMGGREGLIDTAVKTAETG 850
851 YIQRRLIKAMESVMVNYDGTVRNSVGQLIQLRYGEDGLCGELVEFQNMPT 900
901 VKLSNKSFEKRFKFDWSNERLMKKVFTDDVIKEMTDSSEAIQELEAEWDR 950
951 LVSDRDSLRQIFPNGESKVVLPCNLQRMIWNVQKIFHINKRLPTDLSPIR 1000
1001 VIKGVKTLLERCVIVTGNDRISKQANENATLLFQCLIRSTLCTKYVSEEF 1050
1051 RLSTEAFEWLVGEIETRFQQAQANPGEMVGALAAQSLGEPATQMTLNTFH 1100
1101 FAGVSSKNVTLGVPRLKEIINISKKPKAPSLTVFLTGGAARDAEKAKNVL 1150
1151 CRLEHTTLRKVTANTAIYYDPDPQRTVISEDQEFVNVYYEMPDFDPTRIS 1200
1201 PWLLRIELDRKRMTDKKLTMEQIAEKINVGFGEDLNCIFNDDNADKLVLR 1250
1251 IRIMNNEENKFQDEDEAVDKMEDDMFLRCIEANMLSDMTLQGIEAIGKVY 1300
1301 MHLPQTDSKKRIVITETGEFKAIGEWLLETDGTSMMKVLSERDVDPIRTS 1350
1351 SNDICEIFQVLGIEAVRKSVEKEMNAVLQFYGLYVNYRHLALLCDVMTAK 1400
1401 GHLMAITRHGINRQDTGALMRCSFEETVDVLMDAAAHAETDPMRGVSENI 1450
1451 IMGQLPKMGTGCFDLLLDAEKCRFGIEIPNTLGNSMLGGAAMFIGGGSTP 1500
1501 SMTPPMTPWANCNTPRYFSPPGHVSAMTPGGPSFSPSAASDASGMSPSWS 1550
1551 PAHPGSSPSSPGPSMSPYFPASPSVSPSYSPTSPNYTASSPGGASPNYSP 1600
1601 SSPNYSPTSPLYASPRYASTTPNFNPQSTGYSPSSSGYSPTSPVYSPTVQ 1650
1651 FQSSPSFAGSGSNIYSPGNAYSPSSSNYSPNSPSYSPTSPSYSPSSPSYS 1700
1701 PTSPCYSPTSPSYSPTSPNYTPVTPSYSPTSPNYSASPQYSPASPAYSQT 1750
1751 GVKYSPTSPTYSPPSPSYDGSPGSPQYTPGSPQYSPASPKYSPTSPLYSP 1800
1801 SSPQHSPSNQYSPTGSTYSATSPRYSPNMSIYSPSSTKYSPTSPTYTPTA 1850
1851 RNYSPTSPMYSPTAPSHYSPTSPAYSPSSPTFEESED 1887
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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