MDI Biological Laboratory

Topic: Bioinformatics

This is Why: Full Circle Stories

Whether they began here as students, researchers or staff, many discover that the MDI Bio Lab’s sense of curiosity, collaboration and community stays with them. Matthew Cox, Markus Sujansky and Celeste Nobrega share what brought them back — and how working together in the Comparative Genomics and Data Science Core has brought their journeys full circle.

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A Q&A with Joel Graber, Ph.D., on the Comparative Genomics and Data Science Core

Basic scientific research is anything but—the modern science used to unravel the body’s biggest mysteries is increasingly complex. The brilliant minds working to answer the big questions of human aging need powerful tools, technology and expertise working alongside them. 

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MDI Bio Lab Data Team Taps the Cloud

Big data analysis is steadily moving away from local servers and into "the cloud". And the team in MDI Bio Lab’s Computational Genomics and Data Science Core is playing a role in the biomedical world’s transition.

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Data Science Team Explores New Protein Functions

Data Science Core Director Joel Graber, Ph.D., and several of his MDI Bio Lab Core team are co-authors of a new publication in Genetics that details previously undescribed molecular and genetic functions of a protein in yeast that is conserved in humans.

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Cloud Computing 101

Joel Graber, Ph.D., is a Senior Staff Scientist and Director of the Computational Biology and Bioinformatics Core, funded by a Center of Biomedical Research Excellence award from the National Institutes of Health 

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Bioinformatics: The Importance of Training the Trainer

In recent years bioinformatics – using computational power to help process the massive swathes of data produced by modern experiments – has become an indispensable tool for research scientists.

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MINOTA 2020 – a change of direction

Transcriptome-profiling is the primary means by which researchers characterize what is happening at the molecular level.  When a transcriptome profile is generated for a sample, it tells us which genes are active (being expressed) and at what amount.  Comparing profiles among samples allows us to identify genes, and importantly the biological processes that are varying...

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Part III: Meet the Computational Biology Core

(Read part one or part two of the series.)  For this entry into our ongoing discussion of the MDI Biological Laboratory Computational Biology Core, I want to take a step back and, rather than talk about the specifics of the science, instead talk about who we are, what we do, and why it is so...

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Bioinformatics Part II: What do my genome-scale measurements of gene expression mean?

Graphical representation of differential gene expression for a single gene.  The red triangles represent measurements of replicate treated samples, and the black diamonds represent matched control samples.  Differential expression of this gene is determined by a statistical analysis of the separation between expression levels in treated and control, compared to the variation within each group...

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