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Introduction
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October 2015 - February 2018
July 2015 - September 2015
August 2011 - June 2015
Publications
Publications (196)
Background/Introduction
Platelets exhibit considerable heterogeneity in RNA content, size, and thrombogenicity. Our preliminary investigation of the transcriptome of the RNA-rich reticulated platelets(RPs) in healthy donors revealed an enrichment of prothrombotic transcripts compared to mature platelets(MPs). Recently, we validated the prognostic r...
A key parameter in the experimental design of RNA-seq projects is the choice of sequencing depth. Considering a limited budget, one needs to find a tradeoff between the number of samples and the sensitivity of the analysis, particularly concerning lowly expressed genes. While previous studies have proposed a lower bound for the comprehensive analys...
Alternative splicing is crucial for increasing eukaryotic cell transcriptome and proteome diversity Changes in alternative splicing play a key role in cell differentiation and tissue development, and aberrations in this process have been associated with diseases Despite its importance, the exact mechanisms for regulating alternative splicing are po...
Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs) (1–3). Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatoria...
The amount of scientific literature available is overwhelming, especially in fast-evolving fields like drug repurposing. Researchers face a significant challenge: staying up-to-date is nearly impossible due to the sheer volume of publications, databases, and tools available. This situation creates an urgent need for more efficient ways to access an...
The traditional nomenclature of enteroendocrine cells (EECs), established in 1977, applied the “one cell - one hormone” dogma, which distinguishes subpopulations based on the secretion of a specific hormone. These hormone-specific subpopulations included S cells for secretin (SCT), K cells for glucose-dependent insulinotropic polypeptide (GIP), N c...
In silico cell-type deconvolution from bulk transcriptomics data is a powerful technique to gain insights into the cellular composition of complex tissues. While first-generation methods used precomputed expression signatures covering limited cell types and tissues, second-generation tools use single-cell RNA sequencing data to build custom signatu...
Thromboembolic events are common in patients with essential thrombocythemia (ET). However, the pathophysiological mechanisms underlying the increased thrombotic risk remain to be determined. Here, we perform the first phenotypical characterization of platelet expression using single-cell mass cytometry in six ET patients and six age- and sex-matche...
In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex ins...
Artificial Intelligence (AI) and Machine Learning (ML) techniques play an increasingly crucial role in the field of drug repurposing.As the number of computational tools grows, it is essential to not only understand and carefully select the method itself, but also consider the input data used for building predictive models.
This review aims to take...
Identifying protein–protein interactions (PPIs) is crucial for deciphering biological pathways. Numerous prediction methods have been developed as cheap alternatives to biological experiments, reporting surprisingly high accuracy estimates. We systematically investigated how much reproducible deep learning models depend on data leakage, sequence si...
Diseases can be caused by molecular perturbations that induce specific changes in regulatory interactions and their coordinated expression, also referred to as network rewiring. However, the detection of complex changes in regulatory connections remains a challenging task and would benefit from the development of novel nonparametric approaches. We...
Transcriptome deconvolution has emerged as a reliable technique to estimate cell-type abundances from bulk RNA sequencing data. Unlike their human equivalents, methods to quantify the cellular composition of complex tissues from murine transcriptomics are sparse and sometimes not easy to use. We extended the immunedeconv R package to facilitate the...
Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we propose that RNA-seq should be considered a diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on...
Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate thi...
Background
Endoscopic healing (EH) is the major long-term treatment target for inflammatory bowel diseases (IBD) in adults and paediatric patients. However, EH may not represent disease clearance. Hence, risk of relapse remains high and treatment discontinuation after reaching EH often results in disease exacerbation. We aimed to identify persisten...
RNA sequencing offers unique insights into transcriptome diversity, and a plethora of tools have been developed to analyze alternative splicing. One important task is to detect changes in the relative transcript abundance in differential transcript usage (DTU) analysis. The choice of the right analysis tool is non-trivial and depends on experimenta...
Artificial intelligence (AI) and machine learning (ML) techniques play an increasingly crucial role in the field of drug repurposing. As the number of computational tools grows, it is essential to not only understand and carefully select the method itself, but also consider the input data used for building predictive models. This review aims to tak...
Exclusive enteral nutrition (EEN) is the first-line therapy for pediatric Crohn s disease (CD), but protective mechanisms remain unknown. We established a prospective pediatric cohort (n = 1271 fecal samples) to characterize the function of fecal microbiota and metabolite changes of treatment-naive CD patients in response to EEN. Integrated multi-o...
Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs). Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial expl...
Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate thi...
Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we argue that RNA-seq should be considered a routine diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readou...
Microbiota assembly in the infant gut is influenced by time and duration of dietary exposure to breast-milk, infant formula and solid foods. In this randomized controlled intervention study, longitudinal sampling of infant stools (n=998) showed similar development of fecal bacterial communities between formula– and breast-fed infants during the fir...
The nomenclature of enteroendocrine cells (EECs), established in 1977, applies the ”one cell - one hormone” dogma, which distinguishes subpopulations based on the secretion of a specific hormone. These hormone-specific subpopulations include S cells for secretin, K cells for glucose-dependent insulinotropic polypeptide, N cells producing neurotensi...
Transcription factors (TFs) are essential players in orchestrating the regulatory landscape in cells. Still, their exact modes of action and dependencies on other regulatory aspects remain elusive. Since TFs act cell type‐specific and each TF has its own characteristics, untangling their regulatory interactions from an experimental point of view is...
MicroRNAs (miRNAs) are small non-coding RNA molecules that bind to target sites in different gene regions and regulate post-transcriptional gene expression. Approximately 95% of human multi-exon genes can be spliced alternatively, which enables the production of functionally diverse transcripts and proteins from a single gene. Through alternative s...
A key problem in systems biology is the discovery of regulatory mechanisms that drive phenotypic behaviour of complex biological systems in the form of multi-level networks. Modern multi-omics profiling techniques probe these fundamental regulatory networks but are often hampered by experimental restrictions leading to missing data or partially mea...
Background:
Machine learning and artificial intelligence have shown promising results in many areas and are driven by the increasing amount of available data. However, these data are often distributed across different institutions and cannot be easily shared owing to strict privacy regulations. Federated learning (FL) allows the training of distri...
Motivation
Circular RNAs (circRNAs) are long noncoding RNAs (lncRNAs) often associated with diseases and considered potential biomarkers for diagnosis and treatment. Among other functions, circRNAs have been shown to act as microRNA (miRNA) sponges, preventing the role of miRNAs that repress their targets. However, there is no pipeline to systemati...
Alternative splicing is a major contributor to transcriptome and proteome diversity in health and disease. A plethora of tools have been developed for studying alternative splicing in RNA-seq data. Previous benchmarks focused on isoform quantification and mapping. They neglected event detection tools, which arguably provide the most detailed insigh...
We present ROBUST-Web which implements our recently presented ROBUST disease module mining algorithm in a user-friendly web application. ROBUST-Web features seamless downstream disease module exploration via integrated gene set enrichment analysis, tissue expression annotation, and visualization of drug-protein and disease-gene links. Moreover, ROB...
In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex ins...
In recent decades, the development of new drugs has become increasingly expensive and inefficient, and the molecular mechanisms of most pharmaceuticals remain poorly understood. In response, computational systems and network medicine tools have emerged to identify potential drug repurposing candidates. However, these tools often require complex ins...
Motivation:
Cancer is one of the leading causes of death worldwide. Despite significant improvements in prevention and treatment, mortality remains high for many cancer types. Hence, innovative methods that use molecular data to stratify patients and identify biomarkers are needed. Promising biomarkers can also be inferred from competing endogenou...
MicroRNAs (miRNAs) are small non-coding RNA molecules that bind to target sites in different gene regions and regulate post-transcriptional gene expression. Approximately 95% of human multi-exon genes can be spliced alternatively, which enables the production of functionally diverse transcripts and proteins from a single gene. Through alternative s...
Protein-protein interaction (PPI) networks have been found to be power-law-distributed, ie, in observed PPI networks, the fraction of nodes with degree k often follows a power-law (PL) distribution k -α . The emergence of this property is typically explained by evolutionary or functional considerations. However, the experimental procedures used to...
Motivation: Circular RNAs (circRNAs) are long non-coding RNAs (lncRNAs) often associated with diseases and considered potential biomarkers for diagnosis and treatment. Among other functions, circRNAs have been shown to act as microRNA (miRNA) sponges, preventing the role of miRNAs that repress their targets. However, there is no pipeline to systema...
Identifying protein-protein interactions (PPIs) is crucial for deciphering biological pathways and their dysregulation. Numerous prediction methods have been developed as a cheap alternative to biological experiments, reporting phenomenal accuracy estimates. While most methods rely exclusively on sequence information, PPIs occur in 3D space. As pre...
Motivation:
During disease progression or organism development, alternative splicing may lead to isoform switches that demonstrate similar temporal patterns and reflect the alternative splicing co-regulation of such genes. Tools for dynamic process analysis usually neglect alternative splicing.
Results:
Here we propose Spycone, a splicing-aware...
Background:
Eukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic datasets c...
Molecular interaction networks lay the foundation for studying how biological functions are controlled by the complex interplay of genes and proteins. Investigating perturbed processes using biological networks has been instrumental in uncovering mechanisms that underlie complex disease phenotypes. Rapid advances in omics technologies have prompted...
Objectives:
COVID-19 disease can be exacerbated by Aspergillus superinfection (CAPA). However, the causes of CAPA are not yet fully understood. Recently, alterations in the gut microbiome have been associated with a more complicated and severe disease course in COVID-19 patients, most likely due to immunological mechanisms. The aim of this study w...
Alternative splicing is a regulatory mechanism in eukaryotic organisms that allows for production of different protein isoforms from the same gene. These isoforms differ in sequence and often in structure. Recently, it has been shown that they also differ in their capacity to interact with other proteins. However, in publicly available protein–prot...
Alzheimer's disease (AD) is a neurodegenerative disease whose molecular mechanisms are activated several years before cognitive symptoms appear. Genotype-based prediction of the phenotype is thus a key challenge for the early diagnosis of AD. Machine learning techniques that have been proposed to address this challenge do not consider known biologi...
Background
Eukaryotic gene expression is controlled by cis-regulatory elements (CREs) including promoters and enhancers which are bound by transcription factors (TFs). Differential expression of TFs and their putative binding sites on CREs cause tissue and developmental-specific transcriptional activity. Consolidating genomic data sets can offer fu...
Molecular signatures have been suggested as biomarkers to classify pancreatic ductal adenocarcinoma (PDAC) into two, three, four or five subtypes. Since the robustness of existing signatures is controversial, we performed a systematic evaluation of four established signatures for PDAC stratification across nine publicly available datasets. Clusteri...
Objectives
COVID-19 disease can be exacerbated by Aspergillus superinfection (CAPA). The causes of CAPA are not yet fully understood. Recently, alterations in the gut microbiome have been associated with a complicating course and increasing severity of COVID-19 disease, most likely via immunological mechanisms. Aim of this study was to investigate...
Diseases can be caused by molecular perturbations that induce specific changes in regulatory interactions and their coordinated expression, also referred to as network rewiring. However, the detection of complex changes in regulatory connections remains a challenging task and would benefit from the development of novel non-parametric approaches. We...
Motivation:
As complex tissues are typically composed of various cell types, deconvolution tools have been developed to computationally infer their cellular composition from bulk RNA sequencing (RNA-seq) data. To comprehensively assess deconvolution performance, gold-standard datasets are indispensable. Gold-standard, experimental techniques like...
BACKGROUND
Machine learning and artificial intelligence have shown promising results in many areas and are driven by the increasing amount of available data. However, these data are often distributed across different institutions and cannot be easily shared owing to strict privacy regulations. Federated learning (FL) allows the training of distribu...
Genomic profiling has shown that not all cancer patients who share similar macro- and microscopical features harbour the same underlying molecular mechanism. This suggests the urge for matching patients to mechanism-based cancer therapies, independent of their primary tumour location and histology (Bashraheel et al. 2020). Currently, precision onco...
Cytometry techniques are widely used to analyze cellular characteristics at single-cell resolution. This allows forstudying disease-specific mechanisms and potential drug targets, as well as pre-clinical therapy response indiseases such as atherosclerosis and breast cancer [1], [2].Many data analysis methods for cytometry data focus solely on ident...
Heterogeneous biological networks are an efficient way to represent interaction systems of biomedical entities such as disease modules or drug-protein interactomes. Online resources for multi-omics analyses and other biomedical tools have to either develop a suitable network representation for their results or to omit this feature. This results in...