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    Centenary Institute > Research > Bioinformatics

Bioinformatics

Bioinformatics is a research discipline that combines mathematics, statistics with computer algorithms to look for patterns in biological data and help answer biological questions.

The word ‘bioinformatics’ was first used in 1968 and its definition was first given in 1978. Bioinformatics is required for the efficient analysis of large amounts of data and today is most frequently used to process data from next generation sequencing experiments.

There are two main components of bioinformatics, the development of software tools and algorithms and the analysis and interpretation of data using these tools and algorithms.

Recently, it has been driven by the acceleration of data available in all areas of biology. Typical data that are analysed with bioinformatics methods include DNA sequencing and RNA sequencing data, proteomics data and molecule structure data. Modern bioinformatics algorithms seek to integrate cellular high-throughput data (a.k.a. omics data) of various levels (genome, epigenome, transcriptome, and proteome) to look for patterns and for obtaining a comprehensive and accurate snapshot of the state and identify of a cell.

In the Computational BioMedicine lab, we develop integrative workflows combining various computational disciplines with experimentation to address questions around non-coding RNAs, post-transcriptional gene regulation and cancer biology.

In the Computational BioMedicine lab, we develop integrative workflows combining various computational disciplines with experimentation to address questions around non-coding RNAs, post-transcriptional gene regulation and cancer biology.

Using machine learning, mathematical modelling, and molecular dynamics simulations we investigate mechanisms of post-transcriptional gene regulation.

We develop multi-omics data analysis pipelines to investigate patterns of alternative splicing and other forms of gene regulation in normal biology and in various cancers.

Dr Ulf Schmitz, Head of the Computational BioMedicine Laboratory leads this research.

Our ability to read DNA sequence has far exceeded our ability to identify the genetic variants that cause inherited diseases. To address this shortcoming, the Bioinformatics and Human Genetics Group develop new computer-based approaches and laboratory-based methods to identify and characterise disease-causing genetic variants, with a current focus on inherited heart diseases and sudden cardiac death in young people.

We are working to further improve the genetic testing yield and to understand the genetic mechanisms that lead to heart failure. As a result, we are investigating potential new therapeutic approaches to slow or to prevent the development of inherited heart diseases using patient-specific cellular models of disease.

Dr Richard Bagnall, Head of the Bioinformatics and Molecular Genetics Laboratory leads this research.

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In the Computational BioMedicine lab, we develop integrative workflows combining various computational disciplines with experimentation to address questions around non-coding RNAs, post-transcriptional gene regulation and cancer biology.

Using machine learning, mathematical modelling, and molecular dynamics simulations we investigate mechanisms of post-transcriptional gene regulation.

We develop multi-omics data analysis pipelines to investigate patterns of alternative splicing and other forms of gene regulation in normal biology and in various cancers.

Dr Ulf Schmitz, Head of the Computational BioMedicine Laboratory leads this research.

Our ability to read DNA sequence has far exceeded our ability to identify the genetic variants that cause inherited diseases. To address this shortcoming, the Bioinformatics and Human Genetics Group develop new computer-based approaches and laboratory-based methods to identify and characterise disease-causing genetic variants, with a current focus on inherited heart diseases and sudden cardiac death in young people.

We are working to further improve the genetic testing yield and to understand the genetic mechanisms that lead to heart failure. As a result, we are investigating potential new therapeutic approaches to slow or to prevent the development of inherited heart diseases using patient-specific cellular models of disease.

Dr Richard Bagnall, Head of the Bioinformatics and Molecular Genetics Laboratory leads this research.

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