A5060985142- Bioinformatics and Genomic Networks
- Biomedical Text Mining and Ontologies
- Computational Drug Discovery Methods
- Alzheimer's disease research and treatments
- Semantic Web and Ontologies
- Functional Brain Connectivity Studies
- Dementia and Cognitive Impairment Research
- Neurological Disorders and Treatments
- Genetics, Bioinformatics, and Biomedical Research
- Cholinesterase and Neurodegenerative Diseases
- Scientific Computing and Data Management
- Gene expression and cancer classification
- Acute Ischemic Stroke Management
- Machine Learning in Bioinformatics
- Genomics and Rare Diseases
- Axon Guidance and Neuronal Signaling
- Consumer Attitudes and Food Labeling
- Sarcoma Diagnosis and Treatment
- Neurological diseases and metabolism
- Electronic Health Records Systems
- Nerve injury and regeneration
- Protein Degradation and Inhibitors
- Microbial Metabolic Engineering and Bioproduction
- Nutrition, Genetics, and Disease
- Bioeconomy and Sustainability Development
Sarcoma Oncology Center
2023
Centre National de la Recherche Scientifique
2022
Laboratoire d’Imagerie Biomédicale
2022
Inserm
2022
Alzheimer Precision Medicine
2022
Arbed (Luxembourg)
2021
European Society of Radiology
2017-2019
European Society for Blood and Marrow Transplantation
2018
Fraunhofer Institute for Algorithms and Scientific Computing
2009-2017
University of Bonn
2011-2016
Biomedical ontologies offer the capability to structure and represent domain-specific knowledge semantically. Disease-specific can facilitate exchange across multiple disciplines, ontology-driven mining approaches generate great value for modeling disease mechanisms. However, in case of neurodegenerative diseases such as Alzheimer's disease, there is a lack formal representation relevant domain.Alzheimer's ontology (ADO) constructed accordance building life cycle. The Protégé OWL editor was...
Stroke is a leading cause of death and disability worldwide. According to the Iranian Ministry Medical Health Education, out 100,000 stroke incidents in country, 25,000 lead death. Thus, identifying risk factors can help healthcare providers establish prevention strategies. This study was conducted investigate prevalence their distribution based on subtypes Sayad Shirazi Hospital, Gorgan, Northeastern Iran. A retrospective hospital-based at Hospital only referral university hospital for...
Abstract Introduction The longitudinal trajectories of functional brain dynamics and the impact genetic risk factors in individuals at for Alzheimer's disease are poorly understood. Methods In a large‐scale monocentric cohort 224 amyloid stratified disease, default mode network (DMN) resting state connectivity (FC) was investigated between two serial time points across 2 years. Results Widespread DMN FC changes were shown frontal posterior areas, as well right hippocampus. There no...
The discovery and development of new treatments for Alzheimer's disease (AD) requires a profound mechanistic understanding the disease. Here, we propose model-driven approach supporting systematic identification putative mechanisms.We have created model AD corresponding normal physiology neurons using biological expression language to systematically causal correlative relationships between biomolecules, pathways, clinical readouts. Through model-model comparison identify "chains...
With the significant advancement of high-throughput technologies and diagnostic techniques throughout past decades, molecular underpinnings many disorders have been identified. However, translation patient-specific mechanisms into tailored clinical applications remains a challenging task, which requires integration multi-dimensional data patient-centric models. This task becomes even more when dealing with complex diseases such as neurodegenerative disorders. Integrative disease modeling is...
Speculative statements communicating experimental findings are frequently found in scientific articles, and their purpose is to provide an impetus for further investigations into the given topic. Automated recognition of speculative text has gained interest recent years as systematic analysis such could transform thoughts testable hypotheses. We describe here a pattern matching approach detection that uses dictionary patterns classify sentences hypothetical. To demonstrate practical utility...
Abstract Background For selection and evaluation of potential biomarkers, inclusion already published information is utmost importance. In spite significant advancements in text- data-mining techniques, the vast knowledge space biomarkers biomedical text has remained unexplored. Existing named entity recognition approaches are not sufficiently selective for retrieval biomarker from literature. The purpose this study was to identify textual features that enhance effectiveness different...
Despite the unprecedented and increasing amount of data, relatively little progress has been made in molecular characterization mechanisms underlying Parkinson's disease. In area research, there is a pressing need to integrate various pieces information into meaningful context presumed disease mechanism(s). Disease ontologies provide novel means for organizing, integrating, standardizing knowledge domains specific compact, formalized computer-readable form serve as reference exchange or...
Abstract Motivation: There have been many successful experimental and bioinformatics efforts to elucidate transcription factor (TF)-target networks in several organisms. For organisms, these annotations are complemented by miRNA-target of good quality. Attempts that use combination with gene expression data draw conclusions on TF or miRNA activity are, however, still relatively sparse. Results: In this study, we propose Bayesian inference regulation transcriptional (BIRTA) as a novel...
Neurodegenerative diseases including Alzheimer’s disease are complex to tackle because of the complexity brain, both in structure and function. Such is reflected by involvement various brain regions multiple pathways etiology neurodegenerative that render single drug target approaches ineffective. Particularly area neurodegeneration, attention has been drawn repurposing existing drugs with proven efficacy safety profiles. However, there a lack systematic analysis chemical space predict...
Ontologies and terminologies are used for interoperability of knowledge data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects the domain as whole such methodological concepts or calibrations instruments. However, none existing covers diagnostic features measured by technologies context neurodegenerative diseases. Therefore, Neuro-Imaging Feature Terminology (NIFT) was developed to organize brain association with diseases...
Molecular signaling pathways have been long used to demonstrate interactions among upstream causal molecules and downstream biological effects. They show the signal flow between cell compartments, majority of which are represented as cartoons. These often drawn manually by scanning through literature, is time-consuming, static, non-interoperable. Moreover, these devoid context (condition tissue) biased toward certain disease conditions. Mining scientific literature creates new possibilities...
A number of compelling candidate Alzheimer's biomarkers remain buried within the literature. Indeed, there should be a systematic effort towards gathering this information through approaches that mine publicly available data and substantiate supporting evidence disease modeling methods. In presented work, we demonstrate an integrative gray zone mining approach can used as way to tackle challenge successfully.The methodology in work combines semantic retrieval experimental context-specific...
Protein interaction networks are widely used in computational biology as a graphical means of representing higher-level systemic functions computable form. Although, many algorithms exist that seamlessly collect and measure protein information network models, they often do not provide novel mechanistic insights using quantitative criteria. Measuring content knowledge representation models about disease mechanisms becomes crucial particularly when exploring new target candidates well-defined...
Abstract Background In the past years, significant progress has been made to develop and use experimental settings for extensive data collection on tobacco smoke exposure exposure-associated diseases. Due growing number of such data, there is a need domain-specific standard ontologies facilitate integration data. Results The CSEO (version 1.0) composed 20091 concepts. ontology in its current form able capture wide range cigarette concepts within knowledge domain science with reasonable...
Abstract Motivation: Biomedical ontologies have proved to be valuable tools for data analysis and interoperability. Protein–ligand interactions are key players in drug discovery development; however, existing public that describe the knowledge space of biomolecular do not cover all aspects relevant pharmaceutical modelling simulation. Results: The protein–ligand interaction ontology (PLIO) was developed around three main concepts, namely target, ligand interaction, enriched by adding...
Ontology-based annotation of evidence, using disease-specific ontologies, can accelerate analysis and interpretation the knowledge domain diseases. Although many domain-specific disease ontologies have been developed so far, in area cardiovascular diseases, there is a lack ontological representation stroke. The stroke ontology (STO) was created on basis development life cycle built Protégé editor web language format. evaluated terms structural functional features, expert evaluation,...
Large biomedical simulation initiatives, such as the Virtual Physiological Human (VPH), are substantially dependent on controlled vocabularies to facilitate exchange of information, data and models. Hindering these initiatives is a lack comprehensive ontology that covers essential concepts domain. We propose first version newly constructed ontology, HuPSON, basis for shared semantics interoperability simulations, models, algorithms other resources in this The based Basic Formal Ontology,...