A5054291245- Bioinformatics and Genomic Networks
- Computational Drug Discovery Methods
- Microbial Metabolic Engineering and Bioproduction
- Gene Regulatory Network Analysis
- SARS-CoV-2 and COVID-19 Research
- Genetics, Bioinformatics, and Biomedical Research
- vaccines and immunoinformatics approaches
- Biomedical Text Mining and Ontologies
- Cancer Genomics and Diagnostics
- Gene expression and cancer classification
- Genomics and Chromatin Dynamics
- Biochemical Acid Research Studies
- Protein Tyrosine Phosphatases
- Renin-Angiotensin System Studies
- Cancer-related molecular mechanisms research
- Neutrophil, Myeloperoxidase and Oxidative Mechanisms
- Genetic Associations and Epidemiology
- Cell Image Analysis Techniques
- Eicosanoids and Hypertension Pharmacology
- Ovarian cancer diagnosis and treatment
- Cholinesterase and Neurodegenerative Diseases
- Scientific Computing and Data Management
- RNA Research and Splicing
- Single-cell and spatial transcriptomics
- Cancer Cells and Metastasis
Technical University of Munich
2020-2024
Universität Hamburg
2021-2024
Hamburg Institut (Germany)
2024
Odense University Hospital
2024
University of Southern Denmark
2024
Saarland University
2017
Coronavirus Disease-2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. It was first identified in Wuhan, China, and has since spread causing a global pandemic. Various studies have been performed to understand molecular mechanisms of viral infection for predicting drug repurposing candidates. However, such information across many publications it very time-consuming access, integrate, explore, exploit. We developed CoVex, interactive online platform SARS-CoV-1 host...
Responding quickly to unknown pathogens is crucial stop uncontrolled spread of diseases that lead epidemics, such as the novel coronavirus, and keep protective measures at a level causes little social economic harm possible. This can be achieved through computational approaches significantly speed up drug discovery. A powerful approach restrict search existing drugs repurposing, which vastly accelerate usually long approval process. In this Review, we examine representative set currently...
Abstract In recent decades, the development of new drugs has become increasingly expensive and inefficient, molecular mechanisms most pharmaceuticals remain poorly understood. response, computational systems network medicine tools have emerged to identify potential drug repurposing candidates. However, these often require complex installation lack intuitive visual mining capabilities. To tackle challenges, we introduce Drugst.One, a platform that assists specialized in becoming...
Abstract Traditional drug discovery faces a severe efficacy crisis. Repurposing of registered drugs provides an alternative with lower costs and faster development timelines. However, the data necessary for identification disease modules, i.e. pathways sub-networks describing mechanisms complex diseases which contain potential targets, are scattered across independent databases. Moreover, existing studies limited to predictions specific or non-translational algorithmic approaches. There is...
Hypertension is the most important cause of death and disability in elderly. In 9 out 10 cases, molecular cause, however, unknown. One mechanistic hypothesis involves impaired endothelium-dependent vasodilation through reactive oxygen species (ROS) formation. Indeed, ROS forming NADPH oxidase ( Nox ) genes associate with hypertension, yet target validation has been negative. We re-investigate this association by network analysis identify NOX5, not present rodents, as a sole neighbor to human...
Abstract A long-term objective of network medicine is to replace our current, mainly phenotype-based disease definitions by subtypes health conditions corresponding distinct pathomechanisms. For this, molecular and data are modeled as networks mined for However, many such studies rely on large-scale association where diseases annotated using the very field aims overcome. This raises question which extent biases mechanistically inadequate annotations introduce in distort results use...
Abstract Motivation Disease module mining methods (DMMMs) extract subgraphs that constitute candidate disease mechanisms from molecular interaction networks such as protein–protein (PPI) networks. Irrespective of the employed models, DMMMs typically include non-robust steps in their workflows, i.e. computed subnetworks vary when running multiple times on equivalent input. This lack robustness has a negative effect trustworthiness obtained and is hence detrimental for widespread adoption...
SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The causes infectious disease COVID-19. biology coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly have only recently developed as rapid reaction to need fast detection, understanding, and treatment To control ongoing COVID-19 pandemic, it utmost importance get insight into evolution pathogenesis virus. In this review, we cover workflows...
In recent decades, the development of new drugs has become increasingly expensive and inefficient, molecular mechanisms most pharmaceuticals remain poorly understood. response, computational systems network medicine tools have emerged to identify potential drug repurposing candidates. However, these often require complex installation lack intuitive visual mining capabilities. To tackle challenges, we introduce Drugst.One, a platform that assists specialized in becoming user-friendly,...
<p class="first" id="d4450922e187">Traditional drug discovery faces a severe efficacy crisis. Repurposing of registered drugs provides an alternative with lower costs, reduced risk, and faster clinical application. The underlying mechanisms complex diseases are best described by disease modules. These modules represent disease-relevant pathways contain potential targets which can be identified in silico network-based methods. data necessary for the identification repurposing scattered across...
Circulating tumor DNA (ctDNA) is a biomarker that could potentially improve the survival rate of ovarian cancer (OC), e.g., by monitoring treatment response and early relapse detection. However, an optimal method for ctDNA analysis in OC remains to be established. We developed tumor-informed single-nucleotide variant detection using whole-genome sequencing. Tumor plasma samples obtained at time diagnosis from 10 patients with were included. The tested involved applying basic filters...
Gene-regulatory networks are an abstract way of capturing the regulatory connectivity between transcription factors, microRNAs, and target genes in biological cells. Here, we address problem identifying enriched co-regulatory three-node motifs that found significantly more often real network than randomized networks. First, compare two randomization strategies, either only conserve degree distribution nodes' in- out-links, or also distributions different edge types. Then, issue how...
<p class="first" id="d4450009e168">Stroke is currently the third cause of death and first disability in industrialized countries. However, translational stroke research has yielded only one thrombolytic no neuroprotective therapy over last decades. In fact, single-drug targets were hitherto pursued leading to patient benefit thus obstructing innovation most profound manner. Contrary, we now know that complex diseases are defined by multitarget modules dysregulated genes causing different...
<p class="first" dir="auto" id="d16332132e261">NeDRex (Network-based Drug Repurposing Explorer) <a data-untrusted="" href="https://paperpile.com/c/jWTgWE/ucal+NBJv" id="d16332132e263" target="xrefwindow">(Sadegh et al. 2021, 2022)</a> is a network-based computational tool used for drug repurposing. The NeDRex database houses rich collection of data on Protein-Protein and Drug-Protein (target) interactions integrates diverse sources. outcome comprehensive knowledge graph, enabling researchers...
<p class="first" dir="auto" id="d16332132e261">NeDRex (Network-based Drug Repurposing Explorer) <a data-untrusted="" href="https://paperpile.com/c/jWTgWE/ucal+NBJv" id="d16332132e263" target="xrefwindow">(Sadegh et al. 2021, 2022)</a> is a network-based computational tool used for drug repurposing. The NeDRex database houses rich collection of data on Protein-Protein and Drug-Protein (target) interactions integrates diverse sources. outcome comprehensive knowledge graph, enabling researchers...
<p class="first" id="d4450006e139">We hardly understand any disease mechanistically and low precision drug interventions are the norm in clinics [1,2]. Current definitions also organ- symptom-based which runs risk that different mechanisms cause a similar symptom subsumed under one umbrella term. They thus converted into common complex entity, is impossible to untangle based on current diagnostic tools, leading long-lasting classification of chronic diseases either symptoms or body location....
<p class="first" id="d25990928e214">In a pandemic, such as the one caused by coronavirus in 2020, fast action is required to provide insights into disease mechanisms and find potential drug targets slow progress of lower mortality. We developed CoVex, an interactive online platform for exploration SARS-CoV-2 host interactome identification candidates. CoVex integrates virus-human protein interactions, human protein-protein drug-target allows visual data. The guided network-based systems...
<p class="first" id="d4449035e148">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 tools have either develop a suitable network representation their results omit this feature. This in large variety custom solutions different quality visualization network-enhanced drug repurposing prediction. We developed Drugst.One,...