A5087599896- Bioinformatics and Genomic Networks
- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Microbial Metabolic Engineering and Bioproduction
- Biomedical Text Mining and Ontologies
- Advanced Proteomics Techniques and Applications
- Digital Radiography and Breast Imaging
- Gene expression and cancer classification
- Computational Drug Discovery Methods
- Cutaneous Melanoma Detection and Management
- Digital Imaging for Blood Diseases
- Semantic Web and Ontologies
- Cell Image Analysis Techniques
- Service-Oriented Architecture and Web Services
- EEG and Brain-Computer Interfaces
- Electronic Health Records Systems
- Advanced Scientific and Engineering Studies
- Intravenous Infusion Technology and Safety
- Radiology practices and education
- Brain Tumor Detection and Classification
- Neural Networks and Applications
- Gene Regulatory Network Analysis
- Information Systems and Technology Applications
- Single-cell and spatial transcriptomics
- Peer-to-Peer Network Technologies
AstraZeneca (United Kingdom)
2023
European Bioinformatics Institute
2015-2021
Wellcome Trust
2019
Open Targets
2016
Brunel University of London
2009-2015
Technological Educational Institute of Athens
2009-2015
University of West London
2012-2014
Reactome (http://www.reactome.org) is a manually curated open-source open-data resource of human pathways and reactions. The current version 46 describes 7088 proteins (34% the predicted proteome), participating in 6744 reactions based on data extracted from 15 107 research publications with PubMed links. Web site analysis tool set have been completely redesigned to increase speed, flexibility user friendliness. model has extended support annotation disease processes due infectious agents mutation.
The Reactome Knowledgebase (https://reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism, and other cellular processes as an ordered network transformations-an extended version a classic metabolic map, in single consistent data model. functions both archive biological tool for discovering unexpected functional relationships such gene expression profiles or somatic mutation catalogues from tumor cells. To support the continued brisk growth...
Abstract The Reactome Knowledgebase (https://reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network transformations in a single consistent data model, extended version classic metabolic map. functions both archive biological tool for discovering functional relationships such gene expression profiles or somatic mutation catalogs from tumor cells. To extend our ability to annotate human disease...
The Reactome Knowledgebase (https://reactome.org), an Elixir core resource, provides manually curated molecular details across a broad range of physiological and pathological biological processes in humans, including both hereditary acquired disease processes. are annotated as ordered network transformations single consistent data model. thus functions digital archive human tool for discovering functional relationships such gene expression profiles or somatic mutation catalogs from tumor...
Reactome aims to provide bioinformatics tools for visualisation, interpretation and analysis of pathway knowledge support basic research, genome analysis, modelling, systems biology education. Pathway methods have a broad range applications in physiological biomedical research; one the main problems, from performance point view, is constantly increasing size data samples. Here, we present new high-performance in-memory implementation well-established over-representation method. To achieve...
We have designed and developed a data integration visualization platform that provides evidence about the association of known potential drug targets with diseases. The is to support identification prioritization biological for follow-up. Each target linked disease using integrated genome-wide from broad range sources. either target-centric workflow identify diseases may be associated specific target, or disease-centric disease. Users can easily transition between these target- workflows....
Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One its main priorities to provide easy efficient access high quality data. At present, biological pathway databases typically store their contents in relational databases. This limits efficiency because there are performance issues associated with queries traversing highly interconnected The same data graph database can be queried more efficiently. Here we present the rationale...
Pathway analyses are key methods to analyze 'omics experiments. Nevertheless, integrating data from different technologies and species still requires considerable bioinformatics knowledge.Here we present the novel ReactomeGSA resource for comparative pathway of multi-omics datasets. can be used through Reactome's existing web interface R Bioconductor package with explicit support scRNA-seq data. Data is automatically mapped a common space. Public ExpressionAtlas Single Cell directly...
Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. For web-based pathway visualization, uses custom diagram viewer that has been evolved over the past years. Here, we present comprehensive enhancements in usability performance based on extensive testing sessions technology developments, aiming to optimize towards needs community.The version 3 achieves consistently better performance, loading rendering 97% diagrams less than 1 s....
Reactome is a free, open-source, open-data, curated and peer-reviewed knowledge base of biomolecular pathways. Pathways are arranged in hierarchical structure that largely corresponds to the GO biological process hierarchy, allowing user navigate from high level concepts like immune system detailed pathway diagrams showing events membrane transport or phosphorylation. Here, we present new developments visualization facilitate navigation through hierarchy enable efficient reuse visualizations...
As the demand for effective and reliable telecare systems increases rapidly over last years, novel ideas applied on existing consumer products enables development of innovative solutions that could enhance user's wellbeing. In this research, we are going to demonstrate potential a system users monitor their own heart beat rate in real time use specialised software personal health coaching. paper will explain how extract information from user using camera commercially available mobile phone...
Reactome is a manually curated, open-source, open-data knowledge base of biomolecular pathways. has always provided clear credit attribution for authors, curators and reviewers through fine-grained annotation all three roles at the reaction pathway level. These data are visible in web interface various download formats. To enhance visibility work reviewers, to provide additional opportunities community engagement, we have implemented key changes Reactome: contributor names now fully...
Abstract Pathway analyses are key methods to analyse ‘omics experiments. Nevertheless, integrating data from different technologies and species still requires considerable bioinformatics knowledge. Here we present the novel ReactomeGSA resource for comparative pathway of multi-omics datasets. can be used through Reactome’s existing web interface R Bioconductor package with explicit support scRNA-seq data. Data is automatically mapped a common space. Public ExpressionAtlas Single Cell...
We developed a wireless personal digital assistant (PDA)-based teleradiology terminal which allowed secure connection to the hospital's Picture Archiving and Communication System (PACS) through DICOM protocol. Ten members of medical staff completed questionnaire about its mobility, usability, stability, performance diagnostic efficiency in real health-care environment. There was high degree satisfaction with system's mobility (mean score 4.1, SD 1.0, on five-point scale), usability 4.2,...
The purpose of this study was to design a decision support system for assisting the diagnosis melanoma in dermatoscopy images. Clinical material comprised images 44 dysplastic (clark's nevi) and malignant lesions, obtained from dermatology database Dermnet. Initially, were processed hair removal background correction using Dull Razor algorithm. Processed segmented isolate moles surrounding background, combination level sets an automated thresholding approach. Morphological (area, size,...
Brain tumours are considered one of the most lethal and difficult to treat forms cancer, with unknown aetiology lack any realistic screening. In this study, we examine, whether combination descriptive criteria, used by expert histopathologists in assessing histologic tissue samples, quantitative image analysis features may improve diagnostic accuracy brain tumour grading. Data comprised 61 cases cancers (astrocytomas, oligodendrogliomas, meningiomas) collected from archives University...
Genetic Algorithm (GA) is a popular optimization technique that can detect the global optimum of multivariable function containing several local optima. GA has been widely used in field biomedical informatics, especially context designing decision support systems classify signals or images into classes interest. The aim this paper to present methodology, based on GA, for selection optimal subset features be efficient classification Event Related Potentials (ERPs), which are recorded during...
Malignant melanoma represents the most dangerous type of skin cancer. In this study we present an ensemble classification scheme, employing mutual information, cross-correlation and clustering based on proximity image features methods, for early stage assessment melanomas plain photography images. The proposed scheme performs two main operations. First, it retrieves similar, to unknown case, samples from available database with verified benign moles malignant cases. Second, provides...
The aim of this study was to design a pattern recognition system for assisting the diagnosis breast lesions, using image information from Ultrasound (US) and Digital Mammography (DM) imaging modalities. State-of-art computer technology employed based on commercial Graphics Processing Unit (GPU) cards parallel programming. An experienced radiologist outlined lesions both US DM images 59 patients employing custom designed software application. Textural features were extracted each lesion used...