Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Sally R. Ellingson"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract Artesunate is a derivative of artemisinin, an active compound isolated from Artemisia annua which has been used in Traditional Chinese Medicine and to treat malaria worldwide. Artemisinin derivatives have exhibited anti-cancer activity again
Externí odkaz:
https://doaj.org/article/e9a6711898344495994d6b1afa88de98
Autor:
Luksana Chaiswing, Fangfang Xu, Yanming Zhao, Jon Thorson, Chi Wang, Daheng He, Jinpeng Lu, Sally R. Ellingson, Weixiong Zhong, Kristy Meyer, Wei Luo, William St. Clair, Daret St. Clair
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 12, p 6409 (2022)
Aberrant levels of reactive oxygen species (ROS) are potential mechanisms that contribute to both cancer therapy efficacy and the side effects of cancer treatment. Upregulation of the non-canonical redox-sensitive NF-kB family member, RelB, confers r
Externí odkaz:
https://doaj.org/article/abac73aadc3044368af0760957df8019
Autor:
Sally R. Ellingson, David W. Fardo
Publikováno v:
F1000Research, Vol 5 (2016)
This paper provides details on the necessary steps to assess and control data in genome wide association studies (GWAS) using genotype information on a large number of genetic markers for large number of individuals. Due to varied study designs and g
Externí odkaz:
https://doaj.org/article/91a788929dc44d279af1273c56d84b2e
Artesunate is a derivative of artemisinin, an active compound isolated from Artemisia annua which has been used in Traditional Chinese Medicine and to treat malaria worldwide. Artemisinin derivatives have exhibited anti-cancer activity against both s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e17073853d7ed0ba174aaca0bdc2098e
https://doi.org/10.21203/rs.3.rs-2281276/v1
https://doi.org/10.21203/rs.3.rs-2281276/v1
Publikováno v:
F1000Research. 12:387
Artificial Intelligence (AI) and machine learning are the current forefront of computer science and technology. AI and related sub-disciplines, including machine learning, are essential technologies which have enabled the widespread use of smart tech
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::51245389187bc6bf834bc56a5e0c5161
https://doi.org/10.12688/f1000research.133019.1
https://doi.org/10.12688/f1000research.133019.1
Publikováno v:
BCB
The development of new ethical drugs is expensive in terms of both time and resources. A single drug can take up to a decade to bring to market, with costs soaring to over a billion dollars [1]. Drug repositioning has thus become an attractive altern
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c0fd659b66a2c2adb933c1457a14a0e
https://doi.org/10.1145/3459930.3469505
https://doi.org/10.1145/3459930.3469505
Autor:
Kristen S. Hill, Sally R. Ellingson, Jill M. Kolesar, Rina Plattner, Erin E Schuler, Anthony McDowell, J. Robert McCorkle
Publikováno v:
Cancers, Vol 13, Iss 1885, p 1885 (2021)
Cancers; Volume 13; Issue 8; Pages: 1885
Cancers
Cancers; Volume 13; Issue 8; Pages: 1885
Cancers
Simple Summary The antimalarial drug artesunate also has anticancer activity. Based on what is known about how artesunate works in malaria, we hypothesized that the kelch-like ECH-associated protein 1 (KEAP1)/nuclear factor erythroid 2-related factor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::74b82637867cd345fd304e7050cebf52
https://www.mdpi.com/2072-6694/13/8/1885
https://www.mdpi.com/2072-6694/13/8/1885
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030504199
ICCS (3)
ICCS (3)
In this paper, we investigate potential biases in datasets used to make drug binding predictions using machine learning. We investigate a recently published metric called the Asymmetric Validation Embedding (AVE) bias which is used to quantify this b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::82cecae61ada0af778f84ba8065c2c7c
https://doi.org/10.1007/978-3-030-50420-5_44
https://doi.org/10.1007/978-3-030-50420-5_44
Autor:
Mathialakan Thavappiragasam, Gilchan Park, Kendall G. Byler, Leighton Coates, Laura Zanetti-Polzi, Jeffrey M. Larkin, Junqi Yin, John A. Gunnels, Omar Demerdash, Loukas Petridis, Ada Sedova, Carlos Soto, Aaron Scheinberg, Mai Zahran, Scott LeGrand, Jens Glaser, Jerome Baudry, Stephan Irle, Samuel Yen-Chi Chen, Andrey Kovalevsky, Isabella Daidone, Julie C. Mitchell, Arvind Ramanathan, Connor J. Cooper, Duncan Poole, V. Q. Vuong, Diogo Santos-Martins, David M. Rogers, Shinjae Yoo, Y. Shen, Oscar Hernandez, A. Tsaris, Swen Boehm, Debsindhu Bhowmik, Travis J Lawrence, Daniel W. Kneller, Shih-Hsien Liu, Jeremy C. Smith, Line Pouchard, Matthew B. Baker, Stefano Forli, Sally R. Ellingson, Anna Pavlova, Rupesh Agarwal, Micholas Dean Smith, Atanu Acharya, James C. Gumbart, Andreas F. Tillack, John D. Eblen, Josh V. Vermaas, Jerry M. Parks
Publikováno v:
Journal of chemical information and modeling 60 (2020): 5832–5852. doi:10.1021/acs.jcim.0c01010
info:cnr-pdr/source/autori:Acharya A.; Agarwal R.; Baker M.B.; Baudry J.; Bhowmik D.; Boehm S.; Byler K.G.; Chen S.Y.; Coates L.; Cooper C.J.; Demerdash O.; Daidone I.; Eblen J.D.; Ellingson S.; Forli S.; Glaser J.; Gumbart J.C.; Gunnels J.; Hernandez O.; Irle S.; Kneller D.W.; Kovalevsky A.; Larkin J.; Lawrence T.J.; Legrand S.; Liu S.-H.; Mitchell J.C.; Park G.; Parks J.M.; Pavlova A.; Petridis L.; Poole D.; Pouchard L.; Ramanathan A.; Rogers D.M.; Santos-Martins D.; Scheinberg A.; Sedova A.; Shen Y.; Smith J.C.; Smith M.D.; Soto C.; Tsaris A.; Thavappiragasam M.; Tillack A.F.; Vermaas J.V.; Vuong V.Q.; Yin J.; Yoo S.; Zahran M.; Zanetti-Polzi L./titolo:Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19/doi:10.1021%2Facs.jcim.0c01010/rivista:Journal of chemical information and modeling/anno:2020/pagina_da:5832/pagina_a:5852/intervallo_pagine:5832–5852/volume:60
Journal of Chemical Information and Modeling
ChemRxiv
article-version (number) 1
article-version (status) pre
info:cnr-pdr/source/autori:Acharya A.; Agarwal R.; Baker M.B.; Baudry J.; Bhowmik D.; Boehm S.; Byler K.G.; Chen S.Y.; Coates L.; Cooper C.J.; Demerdash O.; Daidone I.; Eblen J.D.; Ellingson S.; Forli S.; Glaser J.; Gumbart J.C.; Gunnels J.; Hernandez O.; Irle S.; Kneller D.W.; Kovalevsky A.; Larkin J.; Lawrence T.J.; Legrand S.; Liu S.-H.; Mitchell J.C.; Park G.; Parks J.M.; Pavlova A.; Petridis L.; Poole D.; Pouchard L.; Ramanathan A.; Rogers D.M.; Santos-Martins D.; Scheinberg A.; Sedova A.; Shen Y.; Smith J.C.; Smith M.D.; Soto C.; Tsaris A.; Thavappiragasam M.; Tillack A.F.; Vermaas J.V.; Vuong V.Q.; Yin J.; Yoo S.; Zahran M.; Zanetti-Polzi L./titolo:Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19/doi:10.1021%2Facs.jcim.0c01010/rivista:Journal of chemical information and modeling/anno:2020/pagina_da:5832/pagina_a:5852/intervallo_pagine:5832–5852/volume:60
Journal of Chemical Information and Modeling
ChemRxiv
article-version (number) 1
article-version (status) pre
We present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79326e7712c0be5402b46e8c6ef2b9fd
Publikováno v:
ICCS
In this work we have developed a multi-tiered computational platform to study protein-drug interactions. At the beginning of the workflow more efficient and less accurate methods are used to enable large libraries of proteins in many conformations an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b96dcdcdc1eb858d3e4733726f3df19b
https://doi.org/10.1016/j.procs.2017.05.268
https://doi.org/10.1016/j.procs.2017.05.268