Age K. Smilde

27.2k total citations · 9 hit papers
313 papers, 20.7k citations indexed

About

Age K. Smilde is a scholar working on Analytical Chemistry, Molecular Biology and Spectroscopy. According to data from OpenAlex, Age K. Smilde has authored 313 papers receiving a total of 20.7k indexed citations (citations by other indexed papers that have themselves been cited), including 140 papers in Analytical Chemistry, 127 papers in Molecular Biology and 63 papers in Spectroscopy. Recurrent topics in Age K. Smilde's work include Spectroscopy and Chemometric Analyses (133 papers), Metabolomics and Mass Spectrometry Studies (93 papers) and Fault Detection and Control Systems (50 papers). Age K. Smilde is often cited by papers focused on Spectroscopy and Chemometric Analyses (133 papers), Metabolomics and Mass Spectrometry Studies (93 papers) and Fault Detection and Control Systems (50 papers). Age K. Smilde collaborates with scholars based in Netherlands, Denmark and Belgium. Age K. Smilde's co-authors include Johan A. Westerhuis, Rasmus Bro, Huub C. J. Hoefsloot, Mariët J. van der Werf, Robert A. van den Berg, Sabina Bijlsma, Edoardo Saccenti, Bruce R. Kowalski, Romá Tauler and Ewoud J. J. van Velzen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Bioinformatics and PLoS ONE.

In The Last Decade

Age K. Smilde

305 papers receiving 20.2k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Principal component analysis

2014 2.2k citations Age K. Smilde et al. profile →
Centering, scaling, and transformations: improving the biological information content of metabolomics data

2006 1.8k citations Robert A. van den Berg, Huub C. J. Hoefsloot et al. profile →
Assessment of PLSDA cross validation

2008 1.1k citations Johan A. Westerhuis, Huub C. J. Hoefsloot et al. profile →
Selectivity, local rank, three‐way data analysis and ambiguity in multivariate curve resolution

1995 792 citations Age K. Smilde et al. Journal of Chemometrics profile →
Large-Scale Human Metabolomics Studies: A Strategy for Data (Pre-) Processing and Validation

2005 720 citations Elwin Verheij, Age K. Smilde et al. profile →
Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies

2011 663 citations Age K. Smilde, Johan A. Westerhuis et al. profile →
Multi‐Way Analysis with Applications in the Chemical Sciences

2004 586 citations Age K. Smilde, Paul Geladi et al. UvA-DARE (University of Amsterdam) profile →
ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data

2005 505 citations Age K. Smilde, Huub C. J. Hoefsloot et al. profile →
Reflections on univariate and multivariate analysis of metabolomics data

2013 460 citations Huub C. J. Hoefsloot, Age K. Smilde et al. profile →

Peers

Countries citing papers authored by Age K. Smilde

Since Specialization

Citations

This map shows the geographic impact of Age K. Smilde's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Age K. Smilde with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Age K. Smilde more than expected).

Fields of papers citing papers by Age K. Smilde

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Age K. Smilde. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Age K. Smilde. The network helps show where Age K. Smilde may publish in the future.

Co-authorship network of co-authors of Age K. Smilde

This figure shows the co-authorship network connecting the top 25 collaborators of Age K. Smilde. A scholar is included among the top collaborators of Age K. Smilde based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Age K. Smilde. Age K. Smilde is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	parafac4microbiome: exploratory analysis of longitudinal microbiome data using parallel factor analysis 2025 ·mSystems ·(unknown), Johan A. Westerhuis, Anna Heintz‐Buschart, Age K. Smilde	0
2	A Data-Driven Approach to Link GC-MS and LC-MS with Sensory Attributes of Chicken Bouillon with Added Yeast-Derived Flavor Products in a Combined Prediction Model 2025 ·Metabolites ·(unknown), Carmen Díez-Simón, (unknown), Anne-Charlotte Dubbelman, Amy C. Harms, Johan A. Westerhuis, Doris M. Jacobs, (unknown), Margriet M. W. B. Hendriks, (unknown), Marco van den Berg, (unknown), Roland Mumm, Age K. Smilde, Robert D. Hall, Thomas Hankemeier	1
3	Multi-way modelling of oral microbial dynamics and host-microbiome interactions during induced gingivitis 2024 ·npj Biofilms and Microbiomes ·(unknown), Bernd W. Brandt, Bart J. F. Keijser, Monique H. van der Veen, C.M.C. Volgenant, Egija Zaura, Age K. Smilde, Johan A. Westerhuis, Anna Heintz‐Buschart	3
4	Selection of principal variables through a modified Gram–Schmidt process with and without supervision 2023 ·Journal of Chemometrics ·(unknown), Kristian Hovde Liland, Tormod Næs, Age K. Smilde, Ulf Geir Indahl	2
5	Flavor Profiling Using Comprehensive Mass Spectrometry Analysis of Metabolites in Tomato Soups 2022 ·Metabolites ·(unknown), (unknown), Carmen Díez-Simón, Naama Karu, Anne-Charlotte Dubbelman, Amy C. Harms, Johan A. Westerhuis, Doris M. Jacobs, (unknown), Margriet M. W. B. Hendriks, (unknown), Marco van den Berg, (unknown), Roland Mumm, Robert D. Hall, Age K. Smilde, Thomas Hankemeier	2
6	Choosing proper normalization is essential for discovery of sparse glycan biomarkers 2020 ·Molecular Omics ·Hae‐Won Uh, Lucija Klarić, Ivo Ugrina, Gordan Lauc, Age K. Smilde, Jeanine J. Houwing‐Duistermaat	15
7	Transcriptional profiles of adjuvanted hepatitis B vaccines display variable interindividual homogeneity but a shared core signature 2020 ·Science Translational Medicine ·Laurane De Mot, Viviane Bechtold, Vanesa Bol, Andrea Callegaro, Margherita Coccia, Ahmed Essaghir, (unknown), Fernando Ulloa‐Montoya, Emilio Siena, Age K. Smilde, Robert A. van den Berg, Arnaud M. Didierlaurent, Wivine Burny, Robbert van der Most	33
8	Choosing proper normalization is essential for discovery of sparse glycan biomarkers 2020 ·OMICS A Journal of Integrative Biology ·Hae‐Won Uh, Lucija Klarić, Ivo Ugrina, Gordan Lauc, Age K. Smilde, Jeanine J. Houwing‐Duistermaat	2
9	iTOP: inferring the topology of omics data 2018 ·Bioinformatics ·Nanne Aben, Johan A. Westerhuis, (unknown), Henk A. L. Kiers, Magali Michaut, Age K. Smilde, Lodewyk F.A. Wessels	12
10	MetDFBA: incorporating time-resolved metabolomics measurements into dynamic flux balance analysis 2014 ·Molecular BioSystems ·(unknown), Diana M. Hendrickx, Huub C. J. Hoefsloot, Margriet M. W. B. Hendriks, A. Wahl, Bas Teusink, Age K. Smilde, Antoine H. C. van Kampen	28
11	Inferring differences in the distribution of reaction rates across conditions 2012 ·Molecular BioSystems ·Diana M. Hendrickx, Huub C. J. Hoefsloot, Margriet M. W. B. Hendriks, Daniël J. Vis, André B. Canelas, Bas Teusink, Age K. Smilde	0
12	DISCO-SCA and Properly Applied GSVD as Swinging Methods to Find Common and Distinctive Processes 2012 ·PLoS ONE ·Katrijn Van Deun, Iven Van Mechelen, Lieven Thorrez, Martijn Schouteden, Bart De Moor, Mariët J. van der Werf, Lieven De Lathauwer, Age K. Smilde, Henk A. L. Kiers	32
13	Reverse engineering of metabolic networks, a critical assessment 2010 ·Molecular BioSystems ·Diana M. Hendrickx, Margriet M. W. B. Hendriks, Paul H.C. Eilers, Age K. Smilde, Huub C. J. Hoefsloot	21
14	A Classification Model for the Leiden Proteomics Competition 2008 ·Statistical Applications in Genetics and Molecular Biology ·Huub C. J. Hoefsloot, Suzanne Smit, Age K. Smilde	17
15	Manufacturing Vaccines: An Illustration of Using PAT Tools for Controlling the Cultivation of Bordetella pertussis 2007 ·Quality Engineering ·Eric N.M. van Sprang, Mathieu Streefland, Henk‐Jan Ramaker, Leo A. van der Pol, E. C. Beuvery, Age K. Smilde	7
16	Increased dietary cholesterol-induced atherosclerosis is associated with liver inflammation: Identification of novel regulatory pathways and transcriptional regulators involved in switch from metabolic adaptation to inflammatory state. 2007 ·Genome biology ·Robert Kleemann, Lars Verschuren, Marjan J. van Erk, Yuri Nikolsky, Nicole H.P. Cnubben, Elwin Verheij, Age K. Smilde, (unknown)	1
17	Theoretical framework for real time release of pharmaceutical products. 2006 ·UvA-DARE (University of Amsterdam) ·Erik Skibsted, Johan A. Westerhuis, Age K. Smilde, Dirk T. Witte	1
18	Process analytical chemistry in the distillation industry using near-infrared spectroscopy 1997 ·Pure Amsterdam UMC ·Frans van den Berg, (unknown), Age K. Smilde	17
19	General introduction of robustness. 1996 ·UvA-DARE (University of Amsterdam) ·Age K. Smilde	1
20	THE FUTURE OF CHEMOMETRICS 1995 ·Journal of Chemometrics ·Paul Geladi, Age K. Smilde	2

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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