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Academic research community (GECIP)

Academics, clinicians, and students worldwide can join our research community, the Genomics England Clinical Interpretations Partnership (GECIP, for short).

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Research projects by domain

Select from the domains and explore our active research projects.

Research projects for Quantitative methods, machine learning and functional genomics

Testing the “post-Mendelian” model developed by GEN-COVID network

Validation of interpretable artificial intelligence algorithms for genetic diagnostics

Matching the disease-associated genomics data to the coding regions of microproteins, a new frontier of human proteome.

Genome-wide analysis of tandem repeat expansion in neurological disorders

Machine Learning Enabled Patient Insights in Haematological Cancers and Breast Cancers

Investigating effect of non-coding and regulatory variants in rare disease cases in 100,000 Genomes Project

Assessing the genetic contribution to disease heterogeneity in selected neurological diseases.

Meta-analysis of de novo variants in genes associated with early-onset neurodevelopmental and psychiatric disorders

Effects of endogamy versus consanguinity on risk of rare disorders

Machine Learning Enabled Patient Insights in Neurological Diseases

Identification of Host Genes and Variants influencing susceptibility to COVID-19 using a Proprietary Machine Learning Knowledge Base

PRS analysis of early-onset and familial forms of macular degeneration

Genetic predisposition in COVID-19 patients

The role of branchpoint variants in splice disruption and rare disease

Integrated approaches to identify functional genetic variants predisposing to severe outcomes of COVID-19 infection - Understanding how COVID-19 genetic risk relates to non-COVID sepsis

Using Xenopus to functionally validate variants of uncertain significance

Integrated approaches to identify functional genetic variants predisposing to severe outcomes of COVID-19 infection

Translational genomic: Optimising novel gene discovery for 100,000 rare disease patients

Characterising the deleteriousness of non-coding variants and their role in rare human disease

ARIADNE- a machine learning model to accelerate variant interpretation

Quantitative methods, machine learning and functional genomics research plan

Full details of the research proposed by this domain

Quantitative methods, machine learning and functional genomics detailed research plan
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