Jürgen Claesen
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Jürgen Claesen has a total of 107 co-authors. Here are the top co-authors by number of shared publications:
- Tomasz Burzykowski
International Drug Development Institute (IDDI)
13 shared publications Dirk Valkenborg
Uhasselt Data Science Institute (DSI) Agoralaan, Diepenbeek Belgium
9 shared publicationsTomasz Burzykowski
Data Science Institute, Hasselt University , Hasselt 3500
7 shared publicationsPiotr Dittwald
Institute of Informatics , University of Warsaw , 00-927 Warsaw , Poland
5 shared publications- Anna Gambin
Institute of Informatics, University of Warsaw, Stefana Banacha 2, Warsaw 02-097, Poland
3 shared publications - Dirk Valkenborg
Data Science Institute, Hasselt University, Hasselt, Belgium
3 shared publications
Latest Publications
- Open Access
- 26 December 2024
- Published by Oxford University Press (OUP) in Bioinformatics Advances
- Vol. 5 (1) , vbaf126
A hierarchical negative-binomial model for analysis of correlated sequencing data: practical implementations
Summary: High-throughput techniques for biological and (bio)medical sciences often result in read counts used in downstream analysis. Nowadays, complex experimental designs in combination with these high-throughput methods are regularly applied and lead to correlated count-data measured from matched samples or taken from the same subject under multiple treatment conditions. Additionally, as is common with biological data, the variance is often larger than the mean, leading to over dispersed count data. Hierarchical models have been proposed to analyze over dispersed, correlated data from paired, longitudinal, or clustered experiments. We consider a hierarchical negative-binomial model with normally distributed random effects to account for the within- and between-sample correlation. We focus on different software implementations to allow the use of the model in practice.
- 26 December 2024
- Published by Oxford University Press (OUP) in Bioinformatics Advances
- Vol. 5 (1) , vbaf126
Open AccessA hierarchical negative-binomial model for analysis of correlated sequencing data: practical implementations
Summary: High-throughput techniques for biological and (bio)medical sciences often result in read counts used in downstream analysis. Nowadays, complex experimental designs in combination with these high-throughput methods are regularly applied and lead to correlated count-data measured from matched samples or taken from the same subject under multiple treatment conditions. Additionally, as is common with biological data, the variance is often larger than the mean, leading to over dispersed count data. Hierarchical models have been proposed to analyze over dispersed, correlated data from paired, longitudinal, or clustered experiments. We consider a hierarchical negative-binomial model with normally distributed random effects to account for the within- and between-sample correlation. We focus on different software implementations to allow the use of the model in practice.
- Open Access
- 31 October 2024
- Published by American Chemical Society (ACS) in Chemical Reviews
- Vol. 124 (21) , 12242-12263
Computational Tools for Hydrogen–Deuterium Exchange Mass Spectrometry Data Analysis
Hydrogen-deuterium exchange (HDX) has become a pivotal method for investigating the structural and dynamic properties of proteins. The versatility and sensitivity of mass spectrometry (MS) made the technique the ideal companion for HDX, and today HDX-MS is addressing a growing number of applications in both academic research and industrial settings. The prolific generation of experimental data has spurred the concurrent development of numerous computational tools, designed to automate parts of the workflow while employing different strategies to achieve common objectives. Various computational methods are available to perform automated peptide searches and identification; different statistical tests have been implemented to quantify differences in the exchange pattern between two or more experimental conditions; alternative strategies have been developed to deconvolve and analyze peptides showing multimodal behavior; and different algorithms have been proposed to computationally increase the resolution of HDX-MS data, with the ultimate aim to provide information at the level of the single residue. This review delves into a comprehensive examination of the merits and drawbacks associated with the diverse strategies implemented by software tools for the analysis of HDX-MS data.
- 31 October 2024
- Published by American Chemical Society (ACS) in Chemical Reviews
- Vol. 124 (21) , 12242-12263
Open AccessComputational Tools for Hydrogen–Deuterium Exchange Mass Spectrometry Data Analysis
Hydrogen-deuterium exchange (HDX) has become a pivotal method for investigating the structural and dynamic properties of proteins. The versatility and sensitivity of mass spectrometry (MS) made the technique the ideal companion for HDX, and today HDX-MS is addressing a growing number of applications in both academic research and industrial settings. The prolific generation of experimental data has spurred the concurrent development of numerous computational tools, designed to automate parts of the workflow while employing different strategies to achieve common objectives. Various computational methods are available to perform automated peptide searches and identification; different statistical tests have been implemented to quantify differences in the exchange pattern between two or more experimental conditions; alternative strategies have been developed to deconvolve and analyze peptides showing multimodal behavior; and different algorithms have been proposed to computationally increase the resolution of HDX-MS data, with the ultimate aim to provide information at the level of the single residue. This review delves into a comprehensive examination of the merits and drawbacks associated with the diverse strategies implemented by software tools for the analysis of HDX-MS data.
- Open Access
- 25 June 2024
- Published by Microbiology Society in Microbiology
- Vol. 170 (6) , 001469
Benchmarking short-, long- and hybrid-read assemblers for metagenome sequencing of complex microbial communities
Metagenome community analyses, driven by the continued development in sequencing technology, is rapidly providing insights in many aspects of microbiology and becoming a cornerstone tool. Illumina, Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) are the leading technologies, each with their own advantages and drawbacks. Illumina provides accurate reads at a low cost, but their length is too short to close bacterial genomes. Long reads overcome this limitation, but these technologies produce reads with lower accuracy (ONT) or with lower throughput (PacBio high-fidelity reads). In a critical first analysis step, reads are assembled to reconstruct genomes or individual genes within the community. However, to date, the performance of existing assemblers has never been challenged with a complex mock metagenome. Here, we evaluate the performance of current assemblers that use short, long or both read types on a complex mock metagenome consisting of 227 bacterial strains with varying degrees of relatedness. We show that many of the current assemblers are not suited to handle such a complex metagenome. In addition, hybrid assemblies do not fulfil their potential. We conclude that ONT reads assembled with CANU and Illumina reads assembled with SPAdes offer the best value for reconstructing genomes and individual genes of complex metagenomes, respectively.
- 25 June 2024
- Published by Microbiology Society in Microbiology
- Vol. 170 (6) , 001469
Open AccessBenchmarking short-, long- and hybrid-read assemblers for metagenome sequencing of complex microbial communities
Metagenome community analyses, driven by the continued development in sequencing technology, is rapidly providing insights in many aspects of microbiology and becoming a cornerstone tool. Illumina, Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) are the leading technologies, each with their own advantages and drawbacks. Illumina provides accurate reads at a low cost, but their length is too short to close bacterial genomes. Long reads overcome this limitation, but these technologies produce reads with lower accuracy (ONT) or with lower throughput (PacBio high-fidelity reads). In a critical first analysis step, reads are assembled to reconstruct genomes or individual genes within the community. However, to date, the performance of existing assemblers has never been challenged with a complex mock metagenome. Here, we evaluate the performance of current assemblers that use short, long or both read types on a complex mock metagenome consisting of 227 bacterial strains with varying degrees of relatedness. We show that many of the current assemblers are not suited to handle such a complex metagenome. In addition, hybrid assemblies do not fulfil their potential. We conclude that ONT reads assembled with CANU and Illumina reads assembled with SPAdes offer the best value for reconstructing genomes and individual genes of complex metagenomes, respectively.
- Open Access
- 18 May 2024
- Published by Elsevier in Computational Biology and Chemistry
- Vol. 111, 108094
A varying-coefficient model for the analysis of methylation sequencing data
- 18 May 2024
- Published by Elsevier in Computational Biology and Chemistry
- Vol. 111, 108094
Open AccessA varying-coefficient model for the analysis of methylation sequencing data
- Open Access
- 21 March 2024
- Published by MDPI AG in Current Issues in Molecular Biology
- Vol. 46 (3) , 2713-2740
Unveiling the Molecular Mechanism of Trastuzumab Resistance in SKBR3 and BT474 Cell Lines for HER2 Positive Breast Cancer
HER2-positive breast cancer is one of the most prevalent forms of cancer among women worldwide. Generally, the molecular characteristics of this breast cancer include activation of human epidermal growth factor receptor-2 (HER2) and hormone receptor activation. HER2-positive is associated with a higher death rate, which led to the development of a monoclonal antibody called trastuzumab, specifically targeting HER2. The success rate of HER2-positive breast cancer treatment has been increased; however, drug resistance remains a challenge. This fact motivated us to explore the underlying molecular mechanisms of trastuzumab resistance. For this purpose, a two-fold approach was taken by considering well-known breast cancer cell lines SKBR3 and BT474. In the first fold, trastuzumab treatment doses were optimized separately for both cell lines. This was done based on the proliferation rate of cells in response to a wide variety of medication dosages. Thereafter, each cell line was cultivated with a steady dosage of herceptin for several months. During this period, six time points were selected for further in vitro analysis, ranging from the untreated cell line at the beginning to a fully resistant cell line at the end of the experiment. In the second fold, nucleic acids were extracted for further high throughput-based microarray experiments of gene and microRNA expression. Such expression data were further analyzed in order to infer the molecular mechanisms involved in the underlying development of trastuzumab resistance. In the list of differentially expressed genes and miRNAs, multiple genes (e.g., BIRC5, E2F1, TFRC, and USP1) and miRNAs (e.g., hsa miR 574 3p, hsa miR 4530, and hsa miR 197 3p) responsible for trastuzumab resistance were found. Downstream analysis showed that TFRC, E2F1, and USP1 were also targeted by hsa-miR-8485. Moreover, it indicated that miR-4701-5p was highly expressed as compared to TFRC in the SKBR3 cell line. These results unveil key genes and miRNAs as molecular regulators for trastuzumab resistance.
- 21 March 2024
- Published by MDPI AG in Current Issues in Molecular Biology
- Vol. 46 (3) , 2713-2740
Open AccessUnveiling the Molecular Mechanism of Trastuzumab Resistance in SKBR3 and BT474 Cell Lines for HER2 Positive Breast Cancer
HER2-positive breast cancer is one of the most prevalent forms of cancer among women worldwide. Generally, the molecular characteristics of this breast cancer include activation of human epidermal growth factor receptor-2 (HER2) and hormone receptor activation. HER2-positive is associated with a higher death rate, which led to the development of a monoclonal antibody called trastuzumab, specifically targeting HER2. The success rate of HER2-positive breast cancer treatment has been increased; however, drug resistance remains a challenge. This fact motivated us to explore the underlying molecular mechanisms of trastuzumab resistance. For this purpose, a two-fold approach was taken by considering well-known breast cancer cell lines SKBR3 and BT474. In the first fold, trastuzumab treatment doses were optimized separately for both cell lines. This was done based on the proliferation rate of cells in response to a wide variety of medication dosages. Thereafter, each cell line was cultivated with a steady dosage of herceptin for several months. During this period, six time points were selected for further in vitro analysis, ranging from the untreated cell line at the beginning to a fully resistant cell line at the end of the experiment. In the second fold, nucleic acids were extracted for further high throughput-based microarray experiments of gene and microRNA expression. Such expression data were further analyzed in order to infer the molecular mechanisms involved in the underlying development of trastuzumab resistance. In the list of differentially expressed genes and miRNAs, multiple genes (e.g., BIRC5, E2F1, TFRC, and USP1) and miRNAs (e.g., hsa miR 574 3p, hsa miR 4530, and hsa miR 197 3p) responsible for trastuzumab resistance were found. Downstream analysis showed that TFRC, E2F1, and USP1 were also targeted by hsa-miR-8485. Moreover, it indicated that miR-4701-5p was highly expressed as compared to TFRC in the SKBR3 cell line. These results unveil key genes and miRNAs as molecular regulators for trastuzumab resistance.
- Open Access
- 15 June 2023
- Published by Wiley in Journal of Pediatric Gastroenterology and Nutrition
- Vol. 77 (3) , 373-380
Safety of Accelerated Infliximab Infusions in Children With Inflammatory Bowel Disease: A Retrospective Cohort Study
Objectives: Accelerated infliximab (IFX) infusions have shown to be safe in adults with inflammatory bowel disease (IBD), but data on its safety in pediatric IBD is limited. This study aimed to assess the incidence and timing of infusion reactions (IR) in children with IBD who received accelerated (1‐h) versus standard (2‐h) IFX infusions.Methods: This retrospective cohort study included IBD patients 4–18 years of age and initiated IFX between January 2006 and November 2021 at Amsterdam University Medical Centre, location Academic Medical Centre (AMC) and VU Medical Centre (VUmc). The AMC protocol was adjusted in July 2019 from standard to accelerated infusions with 1‐h intrahospital post‐infusion observation period, whereas in VUmc only standard infusions were administered without an observation period. After merging the departments in 2022, all VUmc patients were allocated to the accelerated infusions (AMC) protocol. Primary outcome was the incidence of acute IR among maintenance accelerated versus standard infusions.Results: Totally, 297 (150 VUmc, 147 AMC) patients (221 Crohn disease; 65 ulcerative colitis; 11 IBD‐unclassified) with cumulative n = 8381 IFX infusions were included. No statistically significant difference in the per‐infusion incidence of IR was observed between maintenance standard infusions (26/4383, 0.6% of infusions) and accelerated infusions (9/3117, 0.3%) (P = 0.33). Twenty‐six of 35 IR (74%) occurred during the infusion, while 9 occurred post‐infusion (26%). Only 3 of 9 IR developed in the intrahospital observation period following the switch to accelerated infusions. All post‐infusion IR were mild, requiring no intervention or only oral medication.Conclusions: Accelerated IFX infusion without a post‐infusion observation period for children with IBD seems a safe approach.
- 15 June 2023
- Published by Wiley in Journal of Pediatric Gastroenterology and Nutrition
- Vol. 77 (3) , 373-380
Open AccessSafety of Accelerated Infliximab Infusions in Children With Inflammatory Bowel Disease: A Retrospective Cohort Study
Objectives: Accelerated infliximab (IFX) infusions have shown to be safe in adults with inflammatory bowel disease (IBD), but data on its safety in pediatric IBD is limited. This study aimed to assess the incidence and timing of infusion reactions (IR) in children with IBD who received accelerated (1‐h) versus standard (2‐h) IFX infusions.Methods: This retrospective cohort study included IBD patients 4–18 years of age and initiated IFX between January 2006 and November 2021 at Amsterdam University Medical Centre, location Academic Medical Centre (AMC) and VU Medical Centre (VUmc). The AMC protocol was adjusted in July 2019 from standard to accelerated infusions with 1‐h intrahospital post‐infusion observation period, whereas in VUmc only standard infusions were administered without an observation period. After merging the departments in 2022, all VUmc patients were allocated to the accelerated infusions (AMC) protocol. Primary outcome was the incidence of acute IR among maintenance accelerated versus standard infusions.Results: Totally, 297 (150 VUmc, 147 AMC) patients (221 Crohn disease; 65 ulcerative colitis; 11 IBD‐unclassified) with cumulative n = 8381 IFX infusions were included. No statistically significant difference in the per‐infusion incidence of IR was observed between maintenance standard infusions (26/4383, 0.6% of infusions) and accelerated infusions (9/3117, 0.3%) (P = 0.33). Twenty‐six of 35 IR (74%) occurred during the infusion, while 9 occurred post‐infusion (26%). Only 3 of 9 IR developed in the intrahospital observation period following the switch to accelerated infusions. All post‐infusion IR were mild, requiring no intervention or only oral medication.Conclusions: Accelerated IFX infusion without a post‐infusion observation period for children with IBD seems a safe approach.
- 8 March 2023
- Published by Wiley in Rapid Communications in Mass Spectrometry
- Vol. 37 (9) , e9480
Machine learning approach for the prediction of the number of sulphur atoms in peptides using the theoretical aggregated isotope distribution
Rationale: The observed isotope distribution is an important attribute for the identification of peptides and proteins in mass spectrometry–based proteomics. Sulphur atoms have a very distinctive elemental isotope definition, and therefore, the presence of sulphur atoms has a substantial effect on the isotope distribution of biomolecules. Hence, knowledge of the number of sulphur atoms can improve the identification of peptides and proteins. Methods: In this paper, we conducted a theoretical investigation on the isotope properties of sulphur‐containing peptides. We proposed a gradient boosting approach to predict the number of sulphur atoms based on the aggregated isotope distribution. We compared prediction accuracy and assessed the predictive power of the features using the mass and isotope abundance information from the first three, five and eight aggregated isotope peaks. Results: Mass features alone are not sufficient to accurately predict the number of sulphur atoms. However, we reach near‐perfect prediction when we include isotope abundance features. The abundance ratios of the eighth and the seventh, the fifth and the fourth, and the third and the second aggregated isotope peaks are the most important abundance features. The mass difference between the eighth, the fifth or the third aggregated isotope peaks and the monoisotopic peak are the most predictive mass features. Conclusions: Based on the validation analysis it can be concluded that the prediction of the number of sulphur atoms based on the isotope profile fails, because the isotope ratios are not measured accurately. These results indicate that it is valuable for future instrument developments to focus more on improving spectral accuracy to measure peak intensities of higher‐order isotope peaks more accurately.
- 8 March 2023
- Published by Wiley in Rapid Communications in Mass Spectrometry
- Vol. 37 (9) , e9480
Machine learning approach for the prediction of the number of sulphur atoms in peptides using the theoretical aggregated isotope distribution
Rationale: The observed isotope distribution is an important attribute for the identification of peptides and proteins in mass spectrometry–based proteomics. Sulphur atoms have a very distinctive elemental isotope definition, and therefore, the presence of sulphur atoms has a substantial effect on the isotope distribution of biomolecules. Hence, knowledge of the number of sulphur atoms can improve the identification of peptides and proteins. Methods: In this paper, we conducted a theoretical investigation on the isotope properties of sulphur‐containing peptides. We proposed a gradient boosting approach to predict the number of sulphur atoms based on the aggregated isotope distribution. We compared prediction accuracy and assessed the predictive power of the features using the mass and isotope abundance information from the first three, five and eight aggregated isotope peaks. Results: Mass features alone are not sufficient to accurately predict the number of sulphur atoms. However, we reach near‐perfect prediction when we include isotope abundance features. The abundance ratios of the eighth and the seventh, the fifth and the fourth, and the third and the second aggregated isotope peaks are the most important abundance features. The mass difference between the eighth, the fifth or the third aggregated isotope peaks and the monoisotopic peak are the most predictive mass features. Conclusions: Based on the validation analysis it can be concluded that the prediction of the number of sulphur atoms based on the isotope profile fails, because the isotope ratios are not measured accurately. These results indicate that it is valuable for future instrument developments to focus more on improving spectral accuracy to measure peak intensities of higher‐order isotope peaks more accurately.
- Open Access
The Effects of Combined Exposure to Simulated Microgravity, Ionizing Radiation, and Cortisol on the In Vitro Wound Healing Process
Human spaceflight is associated with several health-related issues as a result of long-term exposure to microgravity, ionizing radiation, and higher levels of psychological stress. Frequent reported skin problems in space include rashes, itches, and a delayed wound healing. Access to space is restricted by financial and logistical issues; as a consequence, experimental sample sizes are often small, which limits the generalization of the results. Earth-based simulation models can be used to investigate cellular responses as a result of exposure to certain spaceflight stressors. Here, we describe the development of an in vitro model of the simulated spaceflight environment, which we used to investigate the combined effect of simulated microgravity using the random positioning machine (RPM), ionizing radiation, and stress hormones on the wound-healing capacity of human dermal fibroblasts. Fibroblasts were exposed to cortisol, after which they were irradiated with different radiation qualities (including X-rays, protons, carbon ions, and iron ions) followed by exposure to simulated microgravity using a random positioning machine (RPM). Data related to the inflammatory, proliferation, and remodeling phase of wound healing has been collected. Results show that spaceflight stressors can interfere with the wound healing process at any phase. Moreover, several interactions between the different spaceflight stressors were found. This highlights the complexity that needs to be taken into account when studying the effect of spaceflight stressors on certain biological processes and for the aim of countermeasures development.
Open AccessThe Effects of Combined Exposure to Simulated Microgravity, Ionizing Radiation, and Cortisol on the In Vitro Wound Healing Process
Human spaceflight is associated with several health-related issues as a result of long-term exposure to microgravity, ionizing radiation, and higher levels of psychological stress. Frequent reported skin problems in space include rashes, itches, and a delayed wound healing. Access to space is restricted by financial and logistical issues; as a consequence, experimental sample sizes are often small, which limits the generalization of the results. Earth-based simulation models can be used to investigate cellular responses as a result of exposure to certain spaceflight stressors. Here, we describe the development of an in vitro model of the simulated spaceflight environment, which we used to investigate the combined effect of simulated microgravity using the random positioning machine (RPM), ionizing radiation, and stress hormones on the wound-healing capacity of human dermal fibroblasts. Fibroblasts were exposed to cortisol, after which they were irradiated with different radiation qualities (including X-rays, protons, carbon ions, and iron ions) followed by exposure to simulated microgravity using a random positioning machine (RPM). Data related to the inflammatory, proliferation, and remodeling phase of wound healing has been collected. Results show that spaceflight stressors can interfere with the wound healing process at any phase. Moreover, several interactions between the different spaceflight stressors were found. This highlights the complexity that needs to be taken into account when studying the effect of spaceflight stressors on certain biological processes and for the aim of countermeasures development.
- 1 December 2021
- Published by Elsevier in Journal of Environmental Management
- Vol. 300, 113705
Effects of environmental parameters on Lemna minor growth: An integrated experimental and modelling approach
- 1 December 2021
- Published by Elsevier in Journal of Environmental Management
- Vol. 300, 113705
Effects of environmental parameters on Lemna minor growth: An integrated experimental and modelling approach
- 29 November 2021
- Published by American Chemical Society (ACS) in Analytical Chemistry
- Vol. 93 (49) , 16341-16349
Moderated Test Statistics to Detect Differential Deuteration in Hydrogen/Deuterium Exchange Mass Spectrometry Experiments
With differential hydrogen/deuterium exchange, differences in the structure and dynamics of protein states can be studied. Detecting statistically significant differentially deuterated peptides is crucial to draw meaningful conclusions about the distinct conformations and dynamics of the protein under study. Here, we introduced a linear model in combination with an empirical Bayes approach to detect differentially deuterated peptides. Using a linear model allows one to test for differences in deuteration between two (two-sample t-test) or more groups (F-statistic), while potentially controlling for the effects of other variables that are not of interest. The empirical Bayes approach improves the estimation of deuteration-level variances, especially in experiments with a low number of replicates. As a consequence, the two sample t-tests and the F-statistic become moderated, resulting in a lower number of false positive and false negative findings. Furthermore, we introduce a thresholded-moderated t-statistic to test if the observed deuteration differences are larger than a specified, biologically relevant difference. Finally, we underline the importance of having a sufficient number of replicates, and the effect of the number of replicates on the power of the statistical significance tests. The R-code for the proposed moderated test statistics is available upon request.
- 29 November 2021
- Published by American Chemical Society (ACS) in Analytical Chemistry
- Vol. 93 (49) , 16341-16349
Moderated Test Statistics to Detect Differential Deuteration in Hydrogen/Deuterium Exchange Mass Spectrometry Experiments
With differential hydrogen/deuterium exchange, differences in the structure and dynamics of protein states can be studied. Detecting statistically significant differentially deuterated peptides is crucial to draw meaningful conclusions about the distinct conformations and dynamics of the protein under study. Here, we introduced a linear model in combination with an empirical Bayes approach to detect differentially deuterated peptides. Using a linear model allows one to test for differences in deuteration between two (two-sample t-test) or more groups (F-statistic), while potentially controlling for the effects of other variables that are not of interest. The empirical Bayes approach improves the estimation of deuteration-level variances, especially in experiments with a low number of replicates. As a consequence, the two sample t-tests and the F-statistic become moderated, resulting in a lower number of false positive and false negative findings. Furthermore, we introduce a thresholded-moderated t-statistic to test if the observed deuteration differences are larger than a specified, biologically relevant difference. Finally, we underline the importance of having a sufficient number of replicates, and the effect of the number of replicates on the power of the statistical significance tests. The R-code for the proposed moderated test statistics is available upon request.