 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q8QGX4 from www.uniprot.org...
The NucPred score for your sequence is 0.95 (see score help below)
1 MAGGVQECLQELHGCLQPGDAMRGYGLLRGLGEACLTCLAGGALALHVSL 50
51 VFAPERGLLAFVCRSLGVEEFRECREEALKFLCVFLERIGERAHPYACSL 100
101 KQTCISVYTKERAAKCKIPALELLIKLLQSLRRSCLMEEMKVGEIFNKFY 150
151 GELAVRSKISDTVLEKIYELLGVLGEVHPADMINNSEKLFRAYLGELKTQ 200
201 MTSATRVPKLPIVAGCLRGLTALMYNFTKSVDEDAQTSKEIFDFAVKAIR 250
251 PQVDQKRYAVHLAGLQLFSWHAAQFGTLLLDSYVMLFETMCRWCGHTNQE 300
301 LKKAGHNALDSFLKQMSLMVAKDAELHKSKLKFFMEQFYGIIRRMDSSNK 350
351 ELSIAIRGYGLFAAPCKAMHPADVDAMYIELLQRCKQMYLTEAETIDDHL 400
401 YQLPSFLQSIASVIFHLDTIPEVYTPVLEHLVVLQINSFPRYSEKMQLVC 450
451 CRSIIKVFLALSIKGPVLWNFISTVVHQGLIRVFSKPMKFSKDVFGKETS 500
501 GSEEFPESGEVDTARWKVPTYKDYLYLFRSLLSCDTMKESIFEEENFLTG 550
551 NSPLQSLNRLLYDELIKSILKIIEKLDLTVQKLNVHEQDENETDSAFIGP 600
601 TSDPASNLQPKKPTDFIAFINLVEFCRDILPDKHVEYFQPWVYSFGYELI 650
651 IHSTRLPLISGFYKLLSVTMKIAKKIKYFEGVGPKSLRKATEDPEKSSCF 700
701 ALFAKFGKEVTAKMKQYKDELLASCLNFLLSLPHDIVMLDIKAYIPALQN 750
751 AFKLGLSCTPMADLGLDALEDWSAHIPRHIMQPYYKDVLPLLDGYLKNSA 800
801 TTVEPQNNWEVRKLSRAAQKGFNKIVIQRLRKAKTSSLDDNPSLEAVRTR 850
851 VARLLGSLGGQINHNLITATSAEEMMKKCVSWDTKNHLSFAVPFADMKPV 900
901 IYLDVFLPRVTDLALSASDRQTKIAACELLHSIVAYMLGKASQMPERQQG 950
951 PPPMHQLYKRIFPVLLRLACDVDQVTRQLYEPLVMQLIHWFTNNKKFESQ 1000
1001 DTVTFLEAILSGIVDPVDSTLRDFCGQCVREFLKWSIKQTTPKQQEKSPA 1050
1051 NTKSLFKRLYSLALHPSAFKRLGAALAFNSIYREFREENSLVEQFVFEAL 1100
1101 VVFLESLALTHTDEKSLGTTQQCCDAINHLKRIIKHKAPALNKEGKRRVP 1150
1151 RGFPATKSVCLQDVVMWLLVQCGRPQTECRHKAMELFYEFVPLLPGNNSP 1200
1201 SSWLADVLKKRDVSFLINKFEGGGSDAKSPSGILSQPTLRDMQEPFSLLT 1250
1251 VMRWMDMFLAALDCYNTFFELRMIKPHEILGVNERSSFLEAVDFFLETIA 1300
1301 LHDIHAAEQCFDCRSRGNIFSPQEREVYNYSKCTIIVRIMEFVTMILEIC 1350
1351 QQDFWKLLEKELLNANFIELLVMTVCDPSHIGFNTADVQVMKNLPDISVR 1400
1401 LLKALMKSPYKEYLQLCLKKRITPQSFEDLCSVDLFNSDARFDQVRFSAV 1450
1451 LSACKQLQKSGLLHSVLHSQDERPHPSIGSKLLSVVYKSIAPGSERSSLP 1500
1501 AVDISSKRLADRLLQLAFAIDDQCEELVSLLLNTVVLSVPLSKASERNFV 1550
1551 DFSHGQYFYSLFSDTINQQLLKNLDVIVIHLMESSVSNPQMVGSILNGML 1600
1601 DQSFRERTIRKQQGVKLVTAVLRNWKRLDSWWAKDSSPESKMAVLTLLAK 1650
1651 VLQIDSSVSFNTSHEAFTAVFDTYTSLLTDQNLGLNLKGHAVIILPFFTN 1700
1701 LSGEKLHDLKNALDQLVAFNFPMSSDEFPKGTLKHNNYVDCTKKFLDALE 1750
1751 LSQSPMLLQLMTEVLCRDHRHSMEDLFQASFKRISRRSSTDKQVVLLDTV 1800
1801 HKMFQNEDLLSNIVRQAFVDRSLLTLMSHCSLDALREFFCKIIVQAMDTL 1850
1851 NSRFTKSNECVFDTQITKKMGYYKMLEVMYIRLSKDDVHSKDSKINQAYR 1900
1901 GSVSVEGNELTKALIKLCYDAFTENMAGENQLLEKRRQYHCAAYNCAIAV 1950
1951 ISCVFTESKFYQGFLFTEKSEKNLLIFENLIDLKRQYVFPVEIEVPLERK 2000
2001 KRYIAIRKEAREAWNDGQDEPKYLASASYMMDSSLSEEMSQFDFSTGVQG 2050
2051 FSYSSQDVTASSAHFRRKETSEYMVLNDEMELEMDELNQHECMAPLTTLI 2100
2101 KHMQRNQITPKVEEGVIPVDLPLWMKFLHSKLGNPSVPLNIRLFIAKLIV 2150
2151 NTEDVFRPYAKQWLGPMLQLVVSGDNGGEGIHYMVVEIAVTVLSWTSVTT 2200
2201 PKGNIKDEILANRLLEFLMKNAFHQKRAVFRHNLEIIKTVIECWKNCLSI 2250
2251 PYSLIFEKFSSGDPDTKDNSVGIQLLGIVLANNLPPFDLKCEIDRVRYFQ 2300
2301 ALVSNMGLLRYKEVYAAAAEVLGLALQYIAERQNILEDPVYDCVIKQLKR 2350
2351 HQNTQQDKFIICLNKVVKNFPPLADRFMNAVFFLIPKLHGVMKNYCLEVI 2400
2401 MCRAEEIPDLYLQLKSKDFIQIMKHRDDERQRVCLDIIYKMLSTLKPPEL 2450
2451 KELLPGVTGFISHPSVICRQRMYDILMWIYDNYSDPESQADGDSQEVLSL 2500
2501 AKEILLQGLIDENAELQLIVRNFWSDETRLPANILDRMLMLLNSLYSAKI 2550
2551 ETQYLSLITNFLLEMTSKSPDYSRKIFEHPLSECKFHDFVIDSSWRYRST 2600
2601 MLTPMFVETQASQSTNRNSSQERSLSISGSVGGRVRATQRQYEFTPTQNV 2650
2651 SGRSSFNWLTGNSIDTLAEYTVPSSSESLSSSMLLVNKRSEKFKQAAFKP 2700
2701 VGPDFGKKRLSLPGDKVDSKTKGIDERAEILRLRRRFLKDQEKVSLIYAR 2750
2751 KGVAEQKREKEMKSELKMKFDGQVTLYRSYRVGDLPDIQIEHCSLIAPLQ 2800
2801 GLAQKDPTFAKQLFSSLFGGIFCEVKKSKIPSEKKAIIQKLLKDFNHFLS 2850
2851 TSVSYFPPFIACIQEISYKHRELLELDSANVSTSCLASLQQPVGILLLEH 2900
2901 ALMALSPAEEPPSKRMRGRTELPPDVVKWLELAKLYRSLGDYDVLRGIFS 2950
2951 GKIGTKDITQQALLAEARSDYAEAAKCYDEALSKEDWEDGEPTEAEKDFW 3000
3001 ELASLECYDHLTEWKSLEYCATVNIDSGKPPDLNKTWSDPFYQETYLPYI 3050
3051 IRSKLKLLLNGENDQTLLTFIDEAMKTEQKKALIEMHYSQELSLLYILQD 3100
3101 DFDRAKYYIGNGIQIFMQSYSSIDTLLYQSRMSKLQSVQALTEIQDFINF 3150
3151 MTKTSNIASQAKSLKRLLRTWTSRYPDAKMDPMNIWDDIITNRCFFLDKL 3200
3201 QEKFLCDKANDSMEVDEESSVGDQMEVDQQDEDIHSMIRSCKFNMKLKMI 3250
3251 ESARKQNSFSIAKKLLKGLRREAKTREDWLVRWNYAYCRFVHSCSQSQSC 3300
3301 PERVLSVLKTISLLEDTKSDYLNKNIMAFRNQNLLLGTTYHIMANALSQD 3350
3351 PKCCEQIEEEKTGKILELSGESSESPEKILAGLNKRAFQCFSSAARKSEE 3400
3401 EVQSLSMEHVDVKGVIDAYMTLVGFCDQHLRKEEEGSLEINAADLQLFPA 3450
3451 IVVEKMIKALKLNSREARLRFPRLLQIIERYPAETLGLVTRELPSVPCWQ 3500
3501 FIGWISQMMALLDKDEAVAVQHTVEEIVDTYPQAIIYPFTISSESYCFKD 3550
3551 TAAGCRNKEFVASIKNKLDRGGVVQDFIHALEQLSNPVMLFKDWVADVRN 3600
3601 ELVKTQRNKIILKEMYEGMYKNLGDVKAPGLGWLRKRFVQAFGKDFDSHF 3650
3651 GKGGSKLLDMKISDFNEITTALLTKMNKTHKEPGNLKECSPWMSEFRAEF 3700
3701 LRNELEVPGQYDGKGKPLPEYHVKISGFDERIMVLESLRKPKRITIRGSD 3750
3751 EQEHPFLVKGGEDLRQDQRIEQLFDVMNIVLSRDAACSQRNMQLKTYQVI 3800
3801 PMTTRLGLIKWLENTCTLKEFLRNSMTEEEDANYNSLKGPRAAYSDWLSK 3850
3851 MGGKAQGLSRYNAMYKNASRTETVIAFKSRESSVPEDLLRRAFVKMSTSP 3900
3901 EAFLALRSHFVSSHALMCVSHWILGIGDRHLSNFMINKETGGMVGIDFGH 3950
3951 AFGSATQFLPVPELMPFRLTRQFVNLMMPVKEWGLIYSVMVHALRAYRAD 4000
4001 PDLLISTMDVFVKEPSLDWKNFEQRQLKKGGTWIKEINTAEVNWYPLQKV 4050
4051 SYVKRKLTGANPARITCDELRLGYEKLPFYNDFAAVARGSADHNIRAKEP 4100
4101 EDRLSEETQVRCLIDQATDPNLLGRVWEGWEPWM 4134
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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