Zobrazeno 1 - 10
of 34
pro vyhledávání: '"William Mangione"'
Publikováno v:
Frontiers in Pharmacology, Vol 14 (2023)
The two most common reasons for attrition in therapeutic clinical trials are efficacy and safety. We integrated heterogeneous data to create a human interactome network to comprehensively describe drug behavior in biological systems, with the goal of
Externí odkaz:
https://doaj.org/article/b02b200680cb41068d86deb5fdacbb82
Publikováno v:
Frontiers in Pharmacology, Vol 13 (2022)
The worldwide outbreak of SARS-CoV-2 in early 2020 caused numerous deaths and unprecedented measures to control its spread. We employed our Computational Analysis of Novel Drug Opportunities (CANDO) multiscale therapeutic discovery, repurposing, and
Externí odkaz:
https://doaj.org/article/51ed7f8055474300811527e0478070de
Autor:
Liana Bruggemann, Zackary Falls, William Mangione, Stanley A. Schwartz, Sebastiano Battaglia, Ravikumar Aalinkeel, Supriya D. Mahajan, Ram Samudrala
Publikováno v:
International Journal of Molecular Sciences, Vol 24, Iss 2, p 997 (2023)
Pharmacogenomics is a rapidly growing field with the goal of providing personalized care to every patient. Previously, we developed the Computational Analysis of Novel Drug Opportunities (CANDO) platform for multiscale therapeutic discovery to screen
Externí odkaz:
https://doaj.org/article/6ff710e6963a4b23b0482be9c8c3119a
Publikováno v:
BMC Research Notes, Vol 12, Iss 1, Pp 1-6 (2019)
Abstract Objective Ascertain the optimal interaction scoring criteria for the Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun drug repurposing to improve benchmarking performance, thereby enabling more accurate predict
Externí odkaz:
https://doaj.org/article/581cf70ccb2c4136ab61dbd24085871e
Autor:
Manoj J. Mammen, Chengjian Tu, Matthew C. Morris, Spencer Richman, William Mangione, Zackary Falls, Jun Qu, Gordon Broderick, Sanjay Sethi, Ram Samudrala
Publikováno v:
Pharmaceuticals, Vol 15, Iss 5, p 566 (2022)
Bronchoalveolar lavage of the epithelial lining fluid (BALF) can sample the profound changes in the airway lumen milieu prevalent in chronic obstructive pulmonary disease (COPD). We compared the BALF proteome of ex-smokers with moderate COPD who are
Externí odkaz:
https://doaj.org/article/e936a32dbaad4c84a331129c244743e7
Autor:
Lama Moukheiber, William Mangione, Mira Moukheiber, Saeed Maleki, Zackary Falls, Mingchen Gao, Ram Samudrala
Publikováno v:
Molecules, Vol 27, Iss 9, p 3021 (2022)
Humans are exposed to numerous compounds daily, some of which have adverse effects on health. Computational approaches for modeling toxicological data in conjunction with machine learning algorithms have gained popularity over the last few years. Mac
Externí odkaz:
https://doaj.org/article/4e35f93a57a240c680c57caa8d25fc94
Publikováno v:
Journal of Clinical and Translational Science, Vol 6, Pp 65-65 (2022)
OBJECTIVES/GOALS: Our goal is to develop a cost-effective approach for precision medicine treatment by providing computational predictions for new uses of currently available FDA approved, and experimental drugs for NSCLC. METHODS/STUDY POPULATION: C
Externí odkaz:
https://doaj.org/article/1f7e8f3db8344ca0b9c08574abfcce6c
Publikováno v:
Pharmaceuticals, Vol 14, Iss 12, p 1277 (2021)
Computational approaches have accelerated novel therapeutic discovery in recent decades. The Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun multitarget therapeutic discovery, repurposing, and design aims to improve th
Externí odkaz:
https://doaj.org/article/8357c091016d49d0b69aecc92385b37b
The worldwide outbreak of SARS-CoV-2 in early 2020 caused numer- ous deaths and unprecedented measures to control its spread. We employed our Computational Analysis of Novel Drug Opportunities (CANDO) multiscale therapeutic discovery, repurposing, an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f42fe373e178ad14013b00dd7a9ab87e
Humans are exposed to numerous compounds daily, some of which have adverse effects on health. Computational approaches for modeling toxicological data in conjunction with machine learning algorithms have gained popularity over the last few years. Mac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::600a3f80d2941e842b82efbaa012f326
https://doi.org/10.1101/2021.12.13.472455
https://doi.org/10.1101/2021.12.13.472455