accelerating clinical and translational research challenges in bioinformatics r.w. doerge...
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ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH
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Challenges in BioinformaticsR.W. Doerge
Department of StatisticsDepartment Agronomy
Purdue University
Methylation profilingMethylation
profiling
A second code of instruction
DNA modifications
ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH
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What is bioinformatics?
•Bioinformatics is the application of computer technology to the management of biological information
• Computers are used to gather, store, analyze and integrate biological and genetic information which can then be applied to gene-based drug discovery and development
•The science of Bioinformatics, is the melding of molecular biology with computer science
•Universities, government institutions and pharmaceutical firms have formed bioinformatics groups to unraveling the mass of information
Reflections
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• Technologies evolve…• More and more data
Cell 157, March 27, 2014
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Bioinformatics uses many areas of computer science, statistics, mathematics and engineering to “process” biological data…
Not just “any” data, … the right data…
and, a lot of it…
Looking Forward…
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• Data storage• one human genome (DNA): 200 gigabytes• five human genomes: 1 terabyte
• Data access
• Data analysis
Looking Forward…
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A. Principal Component Analysis reduces multidimensional (single cell) data by identifying linear combinations of genes that are responsible for cell-to-cell variability
B. measurement of mRNA distributions allows determination of kinetic parameters controlling expression of individual genes
(top) Slow transitions between the ‘‘on’’ and ‘‘off’’ state of a promoter can give rise to bimodality
(bottom) Fast transitions lead to unimodal copy number distributions
• Genes (left) controlled by the same upstream regulator are expected to be positively or negatively correlated across single cells
• Clusters (right) of co-regulated genes identified via pairwise correlations
Cell 157, March 27, 2014
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• Personalized medicine• Personalized food
• Mechanisms underlying heterogeneous gene expression• transcription factor binding• methylation• histone modifications• single cell nucleosome occupancy • spatial orientation of single cells in tissue
Looking Forward…
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AHEAD, Nature 2008
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• an epigenome exits• per cell?• it is dynamic
• epigenomic changes control gene expression
• epigenomic marks are heritable
Opportunities
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• Pre-processing of emerging high throughput data
• Dependence in high-dimensional data• high dimensional discrete counts
• Integration of multi-omics data
• Modeling dynamics of mixtures• populations of cells, variants, metagenomics
• Big data approaches for addressing 'omics'
Opportunities
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• 10-70 trillion cells in the human body• genome per cell• epigenome per cell (type)?
• variation: between individuals, tissues, cells, across time• epigenome is dynamic• interactions between the “environment”, the epigenome, and
genome…
• Think of the opportunities
Opportunities
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