ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH www.indianactsi.org Challenges in Bioinformatics R.W. Doerge Department of Statistics Department Agronomy.

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Presentation transcript:

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH Challenges in Bioinformatics R.W. Doerge Department of Statistics Department Agronomy Purdue University

Methylation profiling A second code of instruction DNA modifications

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH 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

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH Technologies evolve… More and more data Cell 157, March 27, 2014

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH 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…

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH Data storage one human genome (DNA): 200 gigabytes five human genomes: 1 terabyte Data access Data analysis Looking Forward…

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH 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 C.Genes (left) controlled by the same upstream regulator are expected to be positively or negatively correlated across single cells D.Clusters (right) of co-regulated genes identified via pairwise correlations Cell 157, March 27, 2014

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH 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…

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH AHEAD, Nature 2008

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH an epigenome exits per cell? it is dynamic epigenomic changes control gene expression epigenomic marks are heritable Opportunities

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH 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

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH 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

ACCELERATING CLINICAL AND TRANSLATIONAL RESEARCH