Machine learning methods for endocrine disrupting potential identification based on single-cell data-Reference-Cited by-同舟云学术

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Machine learning methods for endocrine disrupting potential identification based on single-cell data

Published:2023-11 Issue: Volume:281 Page:119086
ISSN:0009-2509
Container-title:Chemical Engineering Science
language:en
Short-container-title:Chemical Engineering Science

Author:

Aghayev Zahir,Szafran Adam T.,Tran Anh,Ganesh Hari S.,Stossi Fabio,Zhou Lan,Mancini Michael A.,Pistikopoulos Efstratios N.,Beykal Burcu

Funder

National Institutes of Health

Cancer Prevention and Research Institute of Texas

University of Connecticut

Publisher

Elsevier BV

Subject

Applied Mathematics,Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Reference53 articles.

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3. Avraamidou, S., Beykal, B., Pistikopoulos, I.P. and Pistikopoulos, E.N., 2018. A hierarchical food-energy-water nexus (FEW-N) decision-making approach for land use optimization. In Computer Aided Chemical Engineering (Vol. 44, pp. 1885-1890). Elsevier.

4. Global optimization of grey-box computational systems using surrogate functions and application to highly constrained oil-field operations;Beykal;Comput. Chem. Eng.,2018

5. Optimal design of energy systems using constrained grey-box multi-objective optimization;Beykal;Comput. Chem. Eng.,2018

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