Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Godwin Woo"'
Autor:
Godwin Woo, Michael Hsing, Ayse Derya Cavga, Artem Cherkasov, Michael Fernandez, Nathan A. Lack
Publikováno v:
Bioinformatics. 36:813-818
Motivation Recent advances in the areas of bioinformatics and chemogenomics are poised to accelerate the discovery of small molecule regulators of cell development. Combining large genomics and molecular data sources with powerful deep learning techn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d290fb26dd174d9f1cf2587e5ffd7b8c
https://doi.org/10.1093/bioinformatics/btz645
https://doi.org/10.1093/bioinformatics/btz645
Autor:
Paul S. Rennie, Takeshi Yamazaki, Fuqiang Ban, Michael Fernandez, Michael Hsing, Eric Leblanc, Artem Cherkasov, Godwin Woo, William J. Welch
Publikováno v:
Journal of Chemical Information and Modeling. 58:1533-1543
The majority of computational methods for predicting toxicity of chemicals are typically based on "nonmechanistic" cheminformatics solutions, relying on an arsenal of QSAR descriptors, often vaguely associated with chemical structures, and typically
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66511e17e7f2b8efcf1d63a020f4b6c5
https://doi.org/10.1021/acs.jcim.8b00338
https://doi.org/10.1021/acs.jcim.8b00338
Autor:
Fuqiang Ban, Valery V. Fokin, Michael Fernandez, Godwin Woo, Carl Perez, Alexander Tropsha, Oleksandr Isaev, Artem Cherkasov
Publikováno v:
Journal of chemical information and modeling. 59(4)
In recent years, the field of quantitative structure-activity/property relationship (QSAR/QSPR) modeling has developed into a stable technology capable of reliably predicting new bioactive molecules. With the availability of inexpensive commercial so
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d923f0201860b51093d3828f3440fc33
https://pubmed.ncbi.nlm.nih.gov/30767528
https://pubmed.ncbi.nlm.nih.gov/30767528
Autor:
Fernandez, Michael, Ban, Fuqiang, Godwin Woo, Isaev, Oleksandr, Perez, Carl, Fokin, Valery, Tropsha, Alexander, Cherkasov, Artem
Publikováno v:
Journal of Chemical Information & Modeling; Apr2019, Vol. 59 Issue 4, p1306-1313, 8p