Shirin C C Saverimuttu
A5017186263- Biomedical Text Mining and Ontologies
- Bioinformatics and Genomic Networks
- Alzheimer's disease research and treatments
- Genomics and Phylogenetic Studies
- Genetic Associations and Epidemiology
- Cardiovascular Function and Risk Factors
- Genetic and phenotypic traits in livestock
- Research Data Management Practices
- Computational Drug Discovery Methods
- Peroxisome Proliferator-Activated Receptors
- Neuroinflammation and Neurodegeneration Mechanisms
- Race, Genetics, and Society
- Pulmonary Hypertension Research and Treatments
- Scientific Computing and Data Management
University College London
2020-2025
European Bioinformatics Institute
2021-2024
SIB Swiss Institute of Bioinformatics
2023
Stanford University
2023
Phoenix Bioinformatics
2023
University at Buffalo, State University of New York
2023
University of Southern California
2023
University of Padua
2023
Abstract The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding functions of genes and gene products. Here, we report advances consortium over past two years. new GO-CAM annotation framework was notably improved, formalized model with a computational schema to check validate rapidly increasing repository 2838 GO-CAMs. In addition, describe impacts several collaborations refine GO 10% increase in number annotations,...
Abstract Polygenic scores (PGS) have transformed human genetic research and multiple potential clinical applications, including risk stratification for disease prevention prediction of treatment response. Here, we present a series recent enhancements to the PGS Catalog ( www.PGSCatalog.org ), largest findable, accessible, interoperable, reusable (FAIR) repository PGS. These include expansions in data content ancestral diversity as well addition new features. We further Calculator pgsc_calc ,...
Abstract A comprehensive, computable representation of the functional repertoire all macromolecules encoded within human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating structured body information about gene functions, which now includes experimental findings reported in more than 175,000 publications genes experimentally tractable model organisms 1,2 . Here, we describe results large,...
Gene Ontology (GO) is a major bioinformatic resource used for analysis of large biomedical datasets, example from genome-wide association studies, applied universally across biological fields, including Alzheimer's disease (AD) research.We aim to demonstrate the applicability GO interpretation AD datasets improve understanding underlying molecular mechanisms, involvement inflammatory pathways and dysregulated microRNAs (miRs).We have undertaken systematic full article annotation approach...
Abstract The role of the blood–brain barrier (BBB) in Alzheimer’s and other neurodegenerative diseases is still subject many studies. However, those studies using high-throughput methods have been compromised by lack Gene Ontology (GO) annotations describing proteins normal function BBB. GO Consortium provides a gold-standard bioinformatics resource used for analysis interpretation large biomedical data sets. also research communities and, therefore, must meet variety demands on breadth...
Abstract Gene Ontology (GO) is a tool which provides gene functional annotations, an essential resource for knowledge discovery and the analysis of biological datasets. Although considerable research has quantified similarity between products physiological processes, there need to identify these may contribute pathophysiological states in humans. Previous studies have identified role PPARG multiple signalling pathways, particularly those TGFB1 BMP2, pulmonary artery smooth muscle cells their...