Bioinformatics Core
University Of Cincinnati, Cincinnati OH
Investigators
Linked publications & trials
Abstract
Comprehensive readouts of cellular states produced by genome-scale experimental platforms, such as Next-Generation Sequencing (NGS) and various microarray/BeadArray platforms, have become indispensible in studying effects and interactions of genetic, epigenetic and environmental factors. Management, analysis and interpretation of genomics data generated by these platforms, and omics data in general, require advanced computational platforms and analytical approaches. The increasing scale and complexity of genome-wide assays dramatically raise the need for systems biology integration and interpretation of such data, as well as the overall importance of bioinformatics in biomedical research. Advanced bioinformatics methods are also being increasingly used to elucidate functional consequences of mutations, model biomolecular interactions, such as those between toxicants and their targets, or create general mathematical models of complex biological systems. The methods and algorithms used in these analyses are underpinned by mathematical and statistical models of growing complexity. The breath of bioinformatics methods used in modern Environmental Health research necessitates involvement of experts in different areas of bioinformatics. Finding the right expertise sometimes requires going beyond boundaries of individual Environmental Health Sciences (EHS) Core Centers and individual institutions. The computational tools used in bioinformatics are built on mathematical, statistical and algorithmic foundations that are often inaccessible to biomedical researchers, creating a pressing need for assistance in all stages of generating, managing and analyzing genomic data sets. The Bioinformatics Core (BC) provides unique services that have in the past been extensively used by CEG investigators. It is reasonable to expect that CEG investigators will increasingly rely on BC in navigating ever changing landscape of massive datasets, quickly evolving technologies, and multitude of algorithms and computational platforms for data analysis. In addition to using existing state-of-the-art methods, BC members will develop innovative methods for analysis of genomics data and resources for leveraging the public domain genomics data. Through the network of internal and external Bioinformatics consultants, BC will facilitate the access to resources and expertise otherwise not accessible to CEG investigators. BC will also play an important integrative role for the CEG and beyond by centralizing management and facilitating access to genomics data handled by BC.
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