Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Luna De Ferrari"'
Publikováno v:
Evolutionary Bioinformatics, Vol 2015, Iss 11, Pp 267-274 (2015)
Externí odkaz:
https://doaj.org/article/d6b1f52243114ac6b40738a0709e6e48
Autor:
Stella Arakelyan, Nazir Lone, Atul Anand, Nataysia Mikula-Noble, Marcus J Lyall, Luna De Ferrari, Stewart W. Mercer, Bruce Guthrie
Publikováno v:
JBI Evidence Synthesis.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20ee6bc2943e9be644bad7d2157d5f9c
https://doi.org/10.11124/jbies-22-00406
https://doi.org/10.11124/jbies-22-00406
Publikováno v:
Journal of Chemical Information and Modeling
McDonagh, J L, Nath, N, De Ferrari, L, van Mourik, T & Mitchell, J B O 2014, ' Uniting cheminformatics and chemical theory to predict the intrinsic aqueous solubility of crystalline druglike molecules ', Journal of Chemical Information and Modeling, vol. 54, no. 3, pp. 844-56 . https://doi.org/10.1021/ci4005805
McDonagh, J L, Nath, N, De Ferrari, L, van Mourik, T & Mitchell, J B O 2014, ' Uniting cheminformatics and chemical theory to predict the intrinsic aqueous solubility of crystalline druglike molecules ', Journal of Chemical Information and Modeling, vol. 54, no. 3, pp. 844-56 . https://doi.org/10.1021/ci4005805
We present four models of solution free-energy prediction for druglike molecules utilizing cheminformatics descriptors and theoretically calculated thermodynamic values. We make predictions of solution free energy using physics-based theory alone and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34f95e1f88f5d7d03005d9f8d4a64384
https://hdl.handle.net/10023/4518
https://hdl.handle.net/10023/4518
Publikováno v:
BMC Bioinformatics, Vol 13, Iss 1, p 61 (2012)
BMC Bioinformatics
De Ferrari, L, Aitken, S, van Hemert, J & Goryanin, I 2012, ' EnzML : multi-label prediction of enzyme classes using InterPro signatures ', BMC Bioinformatics, vol. 13, pp. 61 . https://doi.org/10.1186/1471-2105-13-61
BMC Bioinformatics
De Ferrari, L, Aitken, S, van Hemert, J & Goryanin, I 2012, ' EnzML : multi-label prediction of enzyme classes using InterPro signatures ', BMC Bioinformatics, vol. 13, pp. 61 . https://doi.org/10.1186/1471-2105-13-61
LDF is funded by ONDEX DTG, BBSRC TPS Grant BB/F529038/1 of the Centre for Systems Biology at Edinburgh and the University of Newcastle. SA is supported by by a Wellcome Trust Value In People award and, together with IG, the Centre for Systems Biolog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27729f838a3b1427b4b3a4fe1e1c45ac
https://doi.org/10.1186/1471-2105-13-61
https://doi.org/10.1186/1471-2105-13-61
Publikováno v:
Int. Sym. Wikis
The aim of this work is to model quantitatively one of the main properties of wikis: how high quality knowledge can emerge from the individual work of independent volunteers. The approach chosen is to simulate knowledge collection and curation in wik
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a1ec70cd0e6783b62724f93c56093940
https://doi.org/10.1145/1822258.1822303
https://doi.org/10.1145/1822258.1822303
Autor:
Luna De Ferrari, Stuart Aitken
Publikováno v:
BMC Genomics, Vol 7, Iss 1, p 277 (2006)
De Ferrari, L & Aitken, S 2006, ' Mining housekeeping genes with a Naive Bayes classifier ', BMC Genomics, vol. 7, no. 277, pp. 277 . https://doi.org/10.1186/1471-2164-7-277
BMC Genomics
De Ferrari, L & Aitken, S 2006, ' Mining housekeeping genes with a Naive Bayes classifier ', BMC Genomics, vol. 7, no. 277, pp. 277 . https://doi.org/10.1186/1471-2164-7-277
BMC Genomics
The first author was supported by the Student Awards Agency for Scotland. The second author is supported by BBSRC grant BBS RC BB/D006473/1, and under the Advanced Knowledge Technologies (AKT) Interdisciplinary Research Collaboration (IRC), which is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e81013b44b5dd3c5ecc751d3dec62f0
http://www.biomedcentral.com/1471-2164/7/277
http://www.biomedcentral.com/1471-2164/7/277
Publikováno v:
Scopus-Elsevier
University of Edinburgh-PURE
University of Edinburgh-PURE
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a1a8b71ec73b2af66acfa8c244d822f9
http://www.scopus.com/inward/record.url?eid=2-s2.0-84923241101&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-84923241101&partnerID=MN8TOARS
Autor:
Luna De Ferrari, John B. O. Mitchell
Publikováno v:
BMC Bioinformatics
De Ferrari, L & Mitchell, J B O 2014, ' From sequence to enzyme mechanism using multi-label machine learning ', BMC Bioinformatics, vol. 15, pp. 150 . https://doi.org/10.1186/1471-2105-15-150
De Ferrari, L & Mitchell, J B O 2014, ' From sequence to enzyme mechanism using multi-label machine learning ', BMC Bioinformatics, vol. 15, pp. 150 . https://doi.org/10.1186/1471-2105-15-150
Background: In this work we predict enzyme function at the level of chemical mechanism, providing a finer granularity of annotation than traditional Enzyme Commission (EC) classes. Hence we can predict not only whether a putative enzyme in a newly se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9784f3c05d38a6071da829c36d8ecd3c