Declines in the cost of generating genomic data have made DNA sequencing, RNA-seq, and high-throughput screening an increasingly important part of biomedical research. This has created a new challenge of finding the most efficient and effective ways to analyze data and leverage their ability to generate insights into the function of biological systems.

The Columbia Genome Center includes faculty and experienced data analysts who specialize in developing computational methods for extracting insights from next-generation sequencing and high-throughput screening data. We utilize techniques from computer science, statistics, and information theory to infer the relationships and dynamics among genes and to develop predictive models that identify factors within cell regulatory networks that are important in generating specific phenotypes. In the context of translational research, these key factors could ultimately be targets for treatment. Our tools for performing these analyses include an array of algorithms and software that were developed by investigators in the Columbia University Department of Systems Biology and have found widespread usage in the systems biology community.

Columbia Genome Center staff specialize in analyzing high-throughput experimental data.

Although advanced bioinformatics approaches are not essential for all next-generation sequencing and high-throughput screening projects, opportunities exist at the Columbia Genome Center for investigators whose work would benefit from these approaches. Our bioinformatics specialists can assist both in study design and in downstream data analysis.

Performing these types of analysis can often require extensive computing power. As a part of the Department of Systems Biology, the Columbia Genome Center utilizes Columbia’s high-performance computing facility to conduct bioinformatics projects that study large datasets. This platform is one of the world’s largest computing environments dedicated to molecular and systems biology.

Please contact us to learn more about our bioinformatics capabilities.