Assembling the 3-D Genome: A Puzzle with Many Solutions

Using computational approaches to assemble plausible 3-D structures

As a result of experimental techniques developed about a decade ago, researchers now have data that can be used to reconstruct how the genome is arranged inside the nucleus. This 3-D structure likely plays a role in determining cellular function by affecting cells’ ability to access, read and interpret genetic information.


Stem Cell (Re)Programming: Computing New Recipes

Leveraging big data, modeling, and computational biology to create new protocols

Most scientists seeking to turn back adult cells’ developmental clocks rely on go-to recipes that—when followed just right—will yield stem cells. A dash of one reprogramming factor, a sprinkle of another, and let the mixture stew. Likewise, when researchers want stem cells to remain stem cells or, alternatively, when they want them coaxed down a particular developmental pathway, they have cocktails they turn to. Most of these recipes were concocted using trial and error over the past few years, and then they’ve been passed between labs.

Cancer's Heterogeneity

Modeling tumors' diversity

Cancer might spring from a single cell gone awry, but tumors are not monolithic collections of clones. Far from it: They contain many different types of cancer cells, all with their own mutations, proliferation rates, metastatic capacities, and drug responses.


Welcome to the New Biomedical Computation Review

For nearly ten years, this magazine has been published by Simbios (under principal investigator [PI] Russ Altman) as part of the National Institutes of Health’s National Center for Biomedical Computing (NCBC) program. With the end of that program last summer, the magazine faced an uncertain future. But it has gained new life with the support of the Mobilize Center (under PI Scott Delp) as part of BD2K.


Drilling for Insight: NIH Funding for Biocomputing

A support vector machine approach to cataloguing NIH expenditures

Philip Bourne’s recent appointment as Associate Director for Data Science at the National Institutes of Health (NIH) signals the growing importance of bioinformatics and biomedical computing in achieving the NIH mission. Yet the NIH Institutes and Centers don’t have reliable information about how much they spend on computational science. For fiscal year 2011, for example, NITRD (the Networking and Information Technology Research and Development program), reported that the NIH invested $551 million in computational science.

2012 Update on the National Centers for Biomedical Computing

The Principal Investigators weigh in

Ever since the National Institutes of Health (NIH) began funding the National Centers for Biomedical Computing (NCBCs) just over seven years ago, these powerhouses have been plugging away, building the nation’s computational research infrastructure.  Now a collection of articles about the Centers has been published in the March 2012 issue of the Journal of the American Medical Informatics Association (JAMIA).

Capturing Mitosis Genes in Action

During the one-hour drama that is human cell division, many genes enter and exit the stage. Until now, researchers did not know the identities of many of these actors, nor understand their various roles. Now, using a combination of high-throughput screening methods, time-resolved movies and a supervised machine-learning algorithm, researchers have identified 572 genes that are involved in mitosis in human cells. The raw data and images are available to the research community at


Proteins in Knots? NOT!

Knot-detecting algorithm discovers that proteins are rarely knotted

When you accidentally twist a shoelace, garden hose, or necklace, it can get annoyingly tangled into intractable knots. On the microscopic level, biopolymers—string-like molecules such as DNA—also form knots, with one mysterious exception: knotted proteins are rare. Physicists have now used computational methods to quantify just how rare in the May 2006 issue of PLoS Computational Biology.


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