A machine learning approach to define antimalarial drug action from heterogeneous cell-based screens-Reference-Cited by-同舟云学术

A machine learning approach to define antimalarial drug action from heterogeneous cell-based screens

Published:2020-09-25 Issue:39 Volume:6 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Ashdown George W.¹^ORCID,Dimon Michelle²,Fan Minjie²^ORCID,Sánchez-Román Terán Fernando¹^ORCID,Witmer Kathrin¹^ORCID,Gaboriau David C. A.³^ORCID,Armstrong Zan²^ORCID,Ando D. Michael²^ORCID,Baum Jake¹^ORCID

Affiliation:

1. Department of Life Sciences, Imperial College London, London, UK.

2. Google Research, Applied Science Team.

3. Facility for Imaging by Light Microscopy, Imperial College London, London, UK.

Abstract

Machine learning is applied to high-throughput microscopy images of malaria parasites to define antimalarial drug mode of action.

Funder

Bill and Melinda Gates Foundation

Wellcome

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference33 articles.

1. Opportunities and challenges in phenotypic drug discovery: an industry perspective

2. Open-source discovery of chemical leads for next-generation chemoprotective antimalarials

3. WHO World Malaria Report (Geneva 2019).

4. Evolution and expansion of multidrug-resistant malaria in southeast Asia: a genomic epidemiology study

5. Malaria medicines: a glass half full?

Cited by 39 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An adaptable, fit-for-purpose screening approach with high-throughput capability to determine speed of action and stage specificity of anti-malarial compounds;Antimicrobial Agents and Chemotherapy;2024-09-12

2. The Role of Artificial Intelligence in Healthcare: Enhancing Coronary Computed Tomography Angiography for Coronary Artery Disease Management;Cureus;2024-06-02

3. Leveraging computational tools to combat malaria: assessment and development of new therapeutics;Journal of Cheminformatics;2024-05-02

4. Next Generation Chemiluminescent Probes for Antimalarial Drug Discovery;ACS Infectious Diseases;2024-04-01

5. Application of Machine Learning for Detection and Prediction of Malaria: A Review;2024 3rd International Conference for Innovation in Technology (INOCON);2024-03-01