A5010974805- Biomedical Text Mining and Ontologies
- Semantic Web and Ontologies
- Bioinformatics and Genomic Networks
- Genomics and Rare Diseases
- Tryptophan and brain disorders
- Schizophrenia research and treatment
- Asymmetric Hydrogenation and Catalysis
- Bipolar Disorder and Treatment
- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
- Health, Environment, Cognitive Aging
- Cell Image Analysis Techniques
- Dementia and Cognitive Impairment Research
- Gene expression and cancer classification
- Computational Drug Discovery Methods
- Cancer Genomics and Diagnostics
- Machine Learning in Healthcare
- Algorithms and Data Compression
Bonn Aachen International Center for Information Technology
2020-2024
University of Bonn
2020-2024
Fraunhofer Institute for Algorithms and Scientific Computing
2020-2024
Abstract Motivation The COVID-19 pandemic has prompted an impressive, worldwide response by the academic community. In order to support text mining approaches as well data description, linking and harmonization in context of COVID-19, we have developed ontology representing major novel coronavirus (SARS-CoV-2) entities. a strong scope on chemical entities suited for drug repurposing, this is target ongoing therapeutic development. Results comprises 2270 classes concepts 38 987 axioms (2622...
Abstract Motivation The importance of clinical data in understanding the pathophysiology complex disorders has prompted launch multiple initiatives designed to generate patient-level from various modalities. While these studies can reveal important findings relevant disease, each study captures different yet complementary aspects and modalities which, when combined, a more comprehensive picture disease etiology. However, achieving this requires global integration across studies, which proves...
Schizophrenia and bipolar disorder are characterized by highly similar neuropsychological signatures, implying shared neurobiological mechanisms between these two disorders. These disorders also have comorbidities, such as type 2 diabetes mellitus (T2DM). To date, an understanding of the that mediate link remains incomplete. In this work, we identify investigate patterns across multiple schizophrenia, T2DM gene expression datasets through strategies. Firstly, dysregulation at gene-level...
Abstract Motivation Epilepsy is a multifaceted complex disorder that requires precise understanding of the classification, diagnosis, treatment and disease mechanism governing it. Although scattered resources are available on epilepsy, comprehensive structured knowledge missing. In contemplation to promote multidisciplinary exchange facilitate advancement in clinical management, especially pre-clinical research, disease-specific ontology necessary. The presented designed enable better...
Although hundreds of datasets have been published since the beginning coronavirus pandemic, there is a lack centralized resources where these are listed and harmonized to facilitate their applicability uptake by predictive modeling approaches. Firstly, such resource provides information about data owners researchers who searching develop models. Secondly, harmonization supports simultaneously taking advantage several similar datasets. This, in turn, does not only ease imperative external...
Abstract Motivation: Epilepsy is a multi-faceted complex disorder that requires precise understanding of the classification, diagnosis, treatment, and disease mechanism governing it. Although scattered resources are available on epilepsy, comprehensive structured knowledge missing. In contemplation to promote multidisciplinary exchange facilitate advancement in clinical management, especially pre-clinical research, disease-specific ontology necessary. The presented designed enable better...
Abstract Schizophrenia and bipolar disorder are characterized by highly similar neuropsychological signatures, implying shared neurobiological mechanisms between these two disorders. These disorders also have comorbidities with other indications, such as type 2 diabetes mellitus (T2DM). To date, an understanding of the that mediate link remains incomplete. In this work, we identify investigate patterns across multiple schizophrenia, T2DM gene expression datasets through strategies. Firstly,...
As one of the leading causes for dementia in population, it is imperative that we discern exactly why Alzheimer's disease (AD) has a strong molecular association with beta-amyloid and tau. Although clear understanding about etiology pathogenesis AD remains unsolved, scientists worldwide have dedicated significant efforts to discovering interactions linked pathological characteristics potential treatments. Knowledge representations, such as domain ontologies encompassing our current AD, could...
Abstract The COVID-19 data catalogue is a repository that provides landscape view of studies and datasets as putative source to enable researchers develop personalized predictive risk models. currently contains over 400 their relevant information collected from wide range global sources such initiatives, clinical trial repositories, publications repositories. Further, the curated content stored in this complemented by web application, providing visualizations these studies, including...
Motivation: The importance of clinical data in understanding the pathophysiology complex disorders has prompted launch multiple initiatives designed to generate patient-level from various modalities. While these studies can reveal important findings relevant disease, each study captures different yet complementary aspects and modalities which, when combined, a more comprehensive picture disease aetiology. However, achieving this requires global integration across studies, which proves be...