Columbia University Physical Sciences in Oncology Center

I have been working closely with Raul Rabadan, an associate professor at Columbia University, on launching an exciting new research center sponsored by the National Cancer Institute’s Physical Sciences in Oncology program. He and a multidisciplinary team of investigators at Columbia and other institutions will be using advanced mathematical approaches to analyze data generated with new single-cell experimental methods, with the goal of providing more effective ways of understanding how cancerous tumors evolve. I wrote and designed the center’s website, and wrote this article announcing the project. Check them out! The center will be doing some truly fascinating work.


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Research Highlights Brochure

















Here are some quick shots of a brochure I recently assembled for the Columbia University Department of Systems Biology. It compiles writing I did for them in 2014, including coverage of key papers and interviews with two faculty members. In addition to the writing, I also did the layout in InDesign. I’m very happy to have all of this in print form, as it captures some truly fascinating work coming out of Columbia. To read the articles online, go to systems

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Semi-Rational Genome Engineering

I recently had a chance to interview Harris Wang, a young researcher at Columbia University who is doing some very exciting work in synthetic biology. He recently published a new method called (MO)-MAGE, which makes it possible to deliver large numbers of targeted mutations in E. coli simultaneously. The implications are quite fascinating, both in terms of the conceptual frame shift the technology implies and its potential practical applications. In an interview I recently posted to the Department of Systems Biology’s website he explains:

The biggest problem with random mutagenesis is that the likelihood of a finding a beneficial mutation is astronomically low. (MO)-MAGE is not random, but it’s not a completely rational approach to engineering either. I like to think of it as a semi-rational approach whose beauty is that by allowing you to make many genetic variants very quickly, it opens up experimental opportunities that we’ve never really had before.

For example, computational analysis or the scientific literature might lead you to hypothesize that 5 genes are relevant in a specific biochemical process you are trying to optimize. But those genes exist within a complex molecular system and so identifying the ideal levels for all of these components in combination using traditional approaches poses a very difficult problem. By using (MO)-MAGE, however, you can quickly produce lots of genetic variants that you can just experimentally isolate and characterize. This allows you to tune the expression of all of the genes in an iterative way.

If you think about the traditional engineering pipeline that goes from design to building to testing, using this kind of semi-rational approach removes a historical bottleneck. Previously you might have been able to propose a variety of possible designs to optimize a specific biochemical activity, but it was never practical to build them all. (MO)-MAGE saves you from needing to put all your eggs in one basket with one design; it gives you a method to experimentally try hundreds of thousands or even millions of mutations and see what looks interesting.

In the interview Dr. Wang explains how (MO)-MAGE works, and what it could mean for both basic biological research and commercial applications of synthetic biology. Read the full interview here.

Mapping Human B Cell Development Using Single-Cell Technologies

Last week I reported on a very interesting paper published researchers at Columbia University and Stanford University. Here’s the opening. Follow the link below to read the full article.

In a new paper published in the journal Cell, a team of researchers led by Dana Pe’er at Columbia University and Garry Nolan at Stanford University describes a powerful new method for mapping cellular development at the single cell level. By combining emerging technologies for studying single cells with a new, advanced computational algorithm, they have designed a novel approach for mapping development and created the most comprehensive map ever made of human B cell development. Their approach will greatly improve researchers’ ability to investigate development in cells of all types, make it possible to identify rare aberrations in development that lead to disease, and ultimately help to guide the next generation of research in regenerative medicine.

Pointing out why being able to generate these maps is an important advance, Dr. Pe’er, an associate professor in the Columbia University Department of Systems Biology and Department of Biological Sciences, explains, “There are so many diseases that result from malfunctions in the molecular programs that control the development of our cell repertoire and so many rare, yet important, regulatory cell types that we have yet to discover. We can only truly understand what goes wrong in these diseases if we have a complete map of the progression in normal development. Such maps will also act as a compass for regenerative medicine, because it’s very difficult to grow something if you don’t know how it develops in nature. For the first time, our method makes it possible to build a high-resolution map, at the single cell level, that can guide these kinds of research.”

Read the full article here.

Helices & Chains

I was playing around with a sine function today in Processing and while trying to do something else stumbled across this formulation. The function tells each of the rings to move back and forth horizontally at its own pace, with a gradient from slowest to fastest from top to bottom. As the rings dance around each other groups periodically slip into phase, forming chains of different configurations.

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Screenprinting 101











Last weekend I took a two-day class titled “Screenprinting 101” at the Printmaking Center of New Jersey. It was taught by Dave DiMarchi, a Montclair, NJ, based printer and bookmaker. Saturday focused on the basics of how screens are prepared, some techniques for drawing designs by hand, and the mechanics of pulling prints. On Sunday, Dave walked us through the process of using Adobe Illustrator to create color separations and turn them into stencils, transferring the stencils to screens, mixing inks, and then producing an edition.

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Fun with Sine Waves

I’ve been working on a set of Processing sketches that start from an oscillating sine wave. This is created by making a bezier whose anchor points are at either sides of your window, and setting two control points that oscillate up and down in opposite directions. When you stack multiple iterations of the same function, you can create a nice wave effect:


Things start to get even more interesting when you set the window not to refresh with every frame, and turn the alpha (opacity) of your line to a very low percentage. As the frames accumulate without being erased, they generate interference patterns that are most visible where the lines move and intersect most frequently. The wave that is actually telling the pixels to change color is constantly moving, but an apparently static image slowly emerges like a developing photograph, producing some very lovely shapes, which almost feel three dimensional because of the shading effects that result. It reminds me of the famous Chladni plates, which when bowed, vibrate in ways that almost magically concentrate randomly scattered particles on their surfaces into coherent patterns.

The following image shows the interference pattern that results from the waves seen in the animation above. For this one I reversed the colors so that the lines are black and the background is white, which seemed to produce a more interesting effect.


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An Interview with Saeed Tavazoie

I recently had a chance to speak with Saeed Tavazoie, a professor of systems biology at Columbia University, about his work. He gave a very cogent overview of his perspective on the future of biological research, and some really fascinating projects that his lab has been working on. Here is a short snippet, but I’d suggest checking out my full edited interview with him here.

The new technologies that we and others are developing not only generate a scaffold of knowledge about regulatory interactions that other scientists can use, but eventually become important tools for making progress in many other areas. In the past, technologies like microarrays, RNA-Seq, and CHiP-Seq totally changed the way people do science. Today, new technologies that are coming out of systems biology are pushing conceptual revolutions in biology because they enable you to make observations you couldn’t make before. It’s not just that you start thinking out of the box, new technologies actually throw you out of the box and you can’t avoid thinking about things in new ways.

Go to the interview.