 | Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden. |
NucPred
Fetching Q9VGW1 from www.uniprot.org...
The NucPred score for your sequence is 0.99 (see score help below)
1 MASTSSSQPEKNRSHVPLCRLGTEPVSRTGAAEEPSGQRECYYYAPATSP 50
51 HHHHHHHHQHHHHHRLKQHHRHHHHHHRLQHHHHHHQQQHNHQNQQMQHH 100
101 WPSRLGPIGPWLGAMTAYRLLTISLLIGILCPHHVQGADPKFDPTTRMRL 150
151 VLVPADAQVNSVIYRLRATDEEFDYPLTFEFVGDASASTVKVESLPCTKY 200
201 NSVCQANIVLQRRLEPGRYYDFQVSVKDTKGGMTTQLCSITATNFTTPHD 250
251 LIFPHKPGIIMIPEDAKRGTELDYVIARKNPLFQKPVYLELWGSPLFAIR 300
301 QKIVSSETTEGTVFLLGPLDFEKQAMYHLTILANDAYAEPGQDSRNIAGM 350
351 EIVVIVQDVQDQPPVFTSAPPVTKLPPGILPGDKILQVHAEDGDKGNPRE 400
401 VRYGLVSENNPFTSFFDINETSGEIFLMRPLEDIAFITHVGDPVLLTVIA 450
451 EEVKVGRDEPPALASTVQLAFFLPDRTNSPPYFENDHYVSRVDENAPQGT 500
501 ALTFVDPYVPRVYDDDTGKNGVFSLTLLNNNGTFEISPNVAERSAGFLIR 550
551 VRDNSMLDYEQQQSVQFQILAQELGPATNLSALVNVTVYINDVNDNAPVF 600
601 EQPAYSVELPENMTAGTKVVQVLATDPDSGLGGKVRYTAILGYLNTSLNL 650
651 DAETGLITVSTNKHGFDREVMPEYHLYVEARDMDGEGNRAQVPLIIKLID 700
701 VNDETPIFDKDLYEFILTHDLMGFTTTAVIHAEDKDATAPNNEVRYEIIN 750
751 GNYDNQFVLDKVTGELTVREKIHLRSKKNAKTRRRRQAGSDDEDTDIFIL 800
801 TARAYDLGVPVRFSTTTIRVYPPESRKRSVKFVVPGHNPDKAKTEETLSA 850
851 LSGGKVYIHNIRPLSPDEPGAKDIPAGNPGIKERSVVTATVIYDSSSVVD 900
901 ISEIQQRLSHHNNSYAIMPQDTSSTDTQYKAENKVLFWLLILLATLVALT 950
951 ILILLLCCICSWCPLYGAATKRIVNISRTEDDVHLVHREMANGKQTKSVQ 1000
1001 VAEWMGRRDAWSAEKPPDTRTKPTRWEFHDGREQLDEDVGRGQDIGEGDR 1050
1051 RHIQSAEEQQRRVRIKHNRTAKDDLHLNFHNSRTNLINDRDVYMEDVIEN 1100
1101 RDLAGDREHITRTRVNRQEYARRKQYDSEVRHIDDDSMRRHEIDRGSDID 1150
1151 FNTAHNSLKSKRELFIKDGNVEILQLMTRDKTRDGLNLDDDNIYVNVPLK 1200
1201 PAGNLSHPQLLMVDNTGKEILMRRFIEEQPDGKQIIREHYQIVPGATYIQ 1250
1251 SMPNEVQQGSTLKGDTFPLGKSGPNSIVYSQLEPEVKVIHTQPVQAGEGV 1300
1301 SLDQQMQPAVSNQSLTHELEHSLKQQNALLRQILMEKEKLENAYTQHEVA 1350
1351 LETQSLPGQSMAIGTQTDCDAGTQTEGFDGVLDPEISLAKPSRRRARSEN 1400
1401 DESMSEDGYEYVRFNPPNSPEGVYWIKRRRTKKRPRQPRKRIVMVEEVKR 1450
1451 KIRTPIKEEEEVQERKKRVPPKKPLRETKTSILRKQLSDESRKDQSRNGE 1500
1501 SQTGNRHRSESDSHNRDMFMEITDSMDELASPGSHSIRKIQVEKYYKHSD 1550
1551 GDFDEDDTEYSIDSDGDEIVIRTNYPSRAQENERYRRQERTYAEPENPVD 1600
1601 RKRPARKSSPTDSQPEAMPRLSRRDSSKRGSRKQTSSEPPHNRVSISKYE 1650
1651 STVTENGRKLMSTSTEIVGSKRSLTDRSYQSETELAGLEHEERNVPKYME 1700
1701 WYYNKKKSSVSGRTSTESSKSQPSSKKKVGAAEKRVSKTRITAQPKDVEE 1750
1751 YDETGGRYKPEPAPRKSPPKGSRLLKEDRALNKQHKPKIETDTNHPLLQH 1800
1801 SEHRFERENALEVPAAPTKLPHYMYPETPPHAAAGGKESKSGRESKTSKE 1850
1851 AKPKPSPIRENEVKVSNSKIYVEHRGTGHPTQKQLNASTLEDDHDSGIAM 1900
1901 NSLLNSLGRRNPIAEKKSVFSIAYDDVSRVKKINSGGESPQYS 1943
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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