A5029659969- Computational Drug Discovery Methods
- Drug-Induced Hepatotoxicity and Protection
- Pharmacogenetics and Drug Metabolism
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- SARS-CoV-2 and COVID-19 Research
- Cell Image Analysis Techniques
- Single-cell and spatial transcriptomics
- Atherosclerosis and Cardiovascular Diseases
- Cell Adhesion Molecules Research
- Protease and Inhibitor Mechanisms
- Microbial Metabolic Engineering and Bioproduction
- Extracellular vesicles in disease
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- vaccines and immunoinformatics approaches
- Gene expression and cancer classification
- MicroRNA in disease regulation
- Viral Infectious Diseases and Gene Expression in Insects
University of Cambridge
2020-2023
GlaxoSmithKline (United Kingdom)
2022
University Hospital Heidelberg
2019
Heidelberg University
2019
RWTH Aachen University
2019
Joint Research Centre
2019
Abstract While gene expression profiling is commonly used to gain an overview of cellular processes, the identification upstream processes that drive changes remains a challenge. To address this issue, we introduce CARNIVAL, causal network contextualization tool which derives architectures from footprints. CARNIVAL (CAusal Reasoning pipeline for Network using Integer VALue programming) integrates different sources prior knowledge including signed and directed protein–protein interactions,...
Data-driven computational analysis and simulation identified drug repurposing opportunities for COVID-19.
Abstract Background Drug-induced liver injury (DILI) is a major safety concern characterized by complex and diverse pathogenesis. In order to identify DILI early in drug development, better understanding of the models with predictivity are urgently needed. One approach this regard silico which aim at predicting risk based on compound structure. However, these do not yet show sufficient predictive performance or interpretability be useful for decision making themselves, former partially...
Drug-induced liver injury (DILI) is a class of adverse drug reactions (ADR) that causes problems in both clinical and research settings. It the most frequent cause acute failure majority Western countries major attrition novel candidates. Manual trawling literature main route deriving information on DILI from studies. This makes it an inefficient process prone to human error. Therefore, automatized AI model capable retrieving DILI-related articles huge ocean could be invaluable for discovery...
Abstract While gene expression profiling is commonly used to gain an overview of cellular processes, the identification upstream processes that drive changes remains a challenge. To address this issue, we introduce CARNIVAL, causal network building tool which derives architectures from footprints. CARNIVAL (CAusal Reasoning pipeline for Network using Integer VALue programming) integrates different sources prior knowledge, including signed and directed protein-protein interactions,...
Adverse event pathogenesis is often a complex process which compromises multiple events ranging from the molecular to phenotypic level. In toxicology, Outcome Pathways (AOPs) aim formalize this as temporal sequences of events, in relationships should be supported by causal evidence according tailored Bradford-Hill criteria. One criteria whether are consistently observed certain order and, work, we study time concordance using concept “first activation” data-driven means generate hypotheses...
Understanding the Mechanism of Action (MoA) a compound is an often challenging but equally crucial aspect drug discovery that can help improve both its efficacy and safety. Computational methods to aid MoA elucidation usually either aim predict direct targets, or attempt understand modulated downstream pathways signalling proteins. Such require extensive coding experience results are optimised for further computational processing, making them difficult wet-lab scientists perform, interpret...
Drug-Induced Liver Injury (DILI), despite its low occurrence rate, can cause severe side effects or even lead to death. Thus, it is one of the leading causes for terminating development new, and restricting use already-circulating, drugs. Moreover, multifactorial nature, combined with a clinical presentation that often mimics other liver diseases, complicate identification DILI-related (or "positive") literature, which remains main medium sourcing results from practice experimental studies....
SUMMARY The global outbreak of SARS-CoV-2 necessitates the rapid development new therapies against COVID-19 infection. Here, we present identification 200 approved drugs, appropriate for repurposing COVID-19. We constructed a SARS-CoV-2-induced protein (SIP) network, based on disease signatures defined by multi-omic datasets(Bojkova et al., 2020; Gordon 2020), and cross-examined these pathways drugs. This analysis identified drugs predicted to target pathways, 40 which are already in...
Abstract Background: Drug-induced liver injury (DILI) is a major safety concern characterized by complex and diverse pathogenesis. In order to identify DILI early in drug development, better understanding of the models with predictivity are urgently needed. One approach this regard silico which aim at predicting risk based on compound structure. However, these do yet show sufficient predictive performance or interpretability be useful for decision making themselves, former partially stemming...
ABSTRACT Drug-Induced Liver Injury (DILI) is a class of Adverse Drug Reactions (ADR) which causes problems in both clinical and research settings. It the most frequent cause acute liver failure majority western countries major attrition novel drug candidates. Manual trawling literature for main route deriving information on DILI from studies. This makes it an inefficient process prone to human error. Therefore, automatized AI model capable retrieving DILI-related papers huge ocean could be...
Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease, which affects around three million people worldwide and characterized by impaired regeneration from recurrent injury to the alveolar epithelium resulting in progressive scarring. In this work, we target cell transition differentiation of AT2 cells into mature AT1 inhibited IPF contributes epithelium. We hypothesize that inducing promotes can ameliorate disease. To end, intermediate population signature using multiple recently...
ABSTRACT Drug-Induced Liver Injury (DILI), despite its low occurrence rate, can cause severe side effects or even lead to death. Thus, it is one of the leading causes for terminating development new, and restricting use already-circulating, drugs. Moreover, multifactorial nature, combined with a clinical presentation that often mimics other liver diseases, complicate identification DILI-related literature, which remains main medium sourcing results from practice experimental studies. In this...
Abstract Background Understanding the mechanism of action (MoA) a compound is an often challenging but equally crucial aspect drug discovery that can help improve both its efficacy and safety. Computational methods to aid MoA elucidation usually either aim predict direct targets, or attempt understand modulated downstream pathways signalling proteins. Such require extensive coding experience results are optimised for further computational processing, making them difficult wet-lab scientists...
Abstract Drug-induced vascular injury (DIVI) observed in non-clinical species often leads to significant delays or termination of compounds drug development due the lack translatable biomarkers and unknown relevance humans. This study focused on identification potential biomarker candidates drug-induced injury, more specifically mesenteric medial arterial necrosis (MAN), rats. To do so, an adapted bioinformatic filtering pipeline was applied previously generated gene expression data obtained...
Abstract Adverse event pathogenesis is often a complex process which compromises multiple events ranging from the molecular to phenotypic level. In toxicology, Outcome Pathways (AOPs) aim formalize this as temporal sequences of events, in relationships should be supported by causal evidence according tailored Bradford-Hill criteria. One criteria whether are consistently observed certain order and, work, we study time concordance using concept “first activation” data-driven means generate...