Bioinformatics and Machine Learning community
Description
Bioinformatics and machine learning are at the core of genomic research. They provide the algorithms and computational tools needed to investigate omics (e.g. genomics, proteomics, metabolomics) and clinical data, often at scale, to find meaningful associations and patterns. These include finding genotype–phenotype correlations, biomarker identification, gene function predictions, and pathogenicity scores, as well as mapping and annotating genomic features, such as enhancers, promoters, and splice sites. Research in this community will focus on the development, refinement, validation and application of bioinformatics approaches to interrogate data in the NGRL and maximise the ability for clinically relevant discovery. It will facilitate the open exchange and sharing of computational ideas and methods, including powerful machine learning approaches. It will also ensure best practices in clinical interpretation analysis, work with disease groups to provide access to world-leading statistical and computational data analysis expertise; and provide training and support a world-leading workforce in support of genomic-based healthcare.
If you have any questions or enquiries regarding this community, please contact the community lead using the link below (it will open in your email application).