September 10, 2021 article Open access Uncertainty quantification for chromatography model parameters by Bayesian inference using sequential Monte Carlo method Process Safety and Environmental Protection DOI: 10.1016/j.cherd.2021.09.003 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 2 stored of 39 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access PeakPerformance - A tool for Bayesian inference-based fitting of LC-MS/MS peaks 2024 The Journal of Open Source Software article Biochemistry, Genetics and Molecular Biology Metabolomics and Mass Spectrometry Studies Open access 1 citations Advanced error modeling and Bayesian uncertainty quantification in mechanistic liquid chromatography modeling 2023 Journal of Chromatography A article Chemistry Analytical Chemistry and Chromatography 14 citations 2 results References 0