“With respect to components of academia, I firmly believe that these are difficult to separate,” she says. “The best way to deeply understand scientific concepts is to get your hands dirty— actually perform an experiment, write a program, or solve a math problem — or to teach the concepts to someone else. In the best-case scenarios, you do both.”

Her ability to apply this philosophy recently earned Dowell the National Science Foundation’s most prestigious award for junior faculty, the Faculty Early Career Development (CAREER) grant. Providing five years of support totaling more than $650,000, the grant recognizes emerging investigators who excel at combining teaching and research in ways that directly impact their institutions and the broader community. Dowell is one of only ten scientists nationwide in the field of molecular and cellular bioscience who have received the award so far this year.

The CAREER program requires scientists to complete specific aims in both teaching and research.  Successful candidates have designed projects in which their research feeds into their teaching goals and vice versa, creating a long-term cycle that advances both aims. Projects are also expected to meet institutional needs, such as providing students with mentored external development opportunities or promoting interdisciplinary research.

Dowell prefers the term “” in her lab’s approach, a term coined by her graduate mentor, Dr. Sean Eddy. Given her and her students’ concentrations in computer science, statistics, molecular biology and genetics, she defines the concept as “following problem wherever it leads you.”

“I have a hard time when people ask me how I integrate such diverse fields,” she says. “It isn't about integrating fields, areas or components, but rather ignoring those kinds of boundaries.”

The CAREER project embraces this philosophy by providing two unique educational activities for students while furthering the Dowell lab’s continuing research on the molecular impact of aneuploidy. Down syndrome is a well-known example of aneuploidy, which occurs when a person has more copies of a chromosome than normal.

Using computational models of biological processes and experiments on yeast cells, the Dowell lab will explore how regulators—genes that affect the function and form of other genes— affect the early processes of genetic expression, called transcription.

Dowell describes her research in musical terms. If the human genome is the score for a symphony, transcription is like the music heard from that score. In genetics, a regulator gene performs the work of the musical conductor, controlling qualities such as tempo and volume.  

While regulators in the human genome number about 1,800, having too many of these conductors in a particular cell can throw off the music. Aneuploidy is an example in which the dose of regulators has altered expression of genes, causing deleterious affects for people with Down syndrome.

“We understand that transcription is affected by aneuploidy, but we don’t know how it works at the molecular level,” Dowell says.

The educational component of project contains two unique objectives that encourage students to engage in external opportunities that contribute to their education and community. The first objective is to establish a permanent iGEM team at CU. iGEM, or international Genetically Engineered Machine, is the world’s foremost synthetic biology competition for undergraduates. Last year’s CU team won the gold medal at the North American competition for their “DIY Biology” project to create a set of low-cost tools for performing synthetic biology.

The second objective is to better engage scientists in understanding Responsible Conduct of Research (RCR) by creating an interactive game. RCR encompasses professional norms and ethical principles scientists must use in the performance of their work. 

“The game will not only train scientists in an engaging and interactive manner but also will enable studies into how peer pressure influences ethical behavior.” Dowell wrote in her CAREER grant application. “In the end, the long term impact of creating honest, intelligent and creative scientists is incalculable.”

More information on antedisciplinary research, iGEM and aneuploidy can be found on the 

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I decided to join the MCDB department and Dr. Leslie Leinwand’s lab. I have been working on understanding the actin-myosin cross-bridge cycle kinetic model. In general, I want to understand why different myosin isoforms and mutants have different reaction rates and how they play a role in myopathy (muscle disease). Myosin, one of the main contractile proteins in muscle cells can show differences in its reaction rates depending on the muscle, the isoform and the developmental stage. Mutant forms of the protein result in muscle disease and understanding these reactions at the kinetic level can help design treatments for these myopathies. I feel very fortunate to be on this path with some great classmates and in a great lab working on a very interesting project with biotech potential.

My story in �鶹ӰԺ didn’t actually start in August 2011, but in the summer of 2005 and I attribute that summer as one of the main reasons I am in this fortunate situation. I participated in the SMART (Summer Multicultural Access to Research Training) program during that year and immediately fell in love with the �鶹ӰԺ lifestyle and was very intrigued by the research environment.

The SMART program has been going on for 24 years and its main goal is to bring minority undergraduate students from underrepresented institutions to one of the high-end CU-�鶹ӰԺ labs to do research for the summer. That summer was very meaningful for me and it was a huge factor in my decision to continue graduate studies in �鶹ӰԺ. I remained friends with Dr. Mark Hernandez and Barbara Kraus throughout the years and we were all pretty excited when I decided to join the BioFrontiers Institute.

One idea that I had of a way I could repay them for their efforts was to become a student mentor for the program. I would join some colleagues and fellow grad students in helping the intern class for this year in any way we could. But my idea was taken a few steps further, when Leslie trusted me to also mentor the student who joined the Leinwand lab for the summer.

Initially, I was confused. I had just joined the lab, what do I have to teach to a person who is probably 3-4 years younger than me and who is also joining the lab with me? Thankfully, Leslie assured me that one of the postdocs (Steve Langer) would be the one doing most of the teaching and I would help out. Then Dr. Langer told me he would be taking some much-deserved vacation time during the student’s first week, so again… confusion.

As it turned out, I actually had a lot to teach during the first two weeks. I taught the student some tissue culturing, some Q-PCR, some protein purification and some theory behind my new reason for living: myosin kinetics. Then Steve and the recently graduated John Deacon (Leinwand Lab, defended in July) helped me out for the rest of the summer.

I also had a chance to interact with the other students when I gave a workshop on how to write a research proposal. The proposal is just one of the many requirements that the SMART program has for the interns. Watching the students work on their respective proposals in the beginning of the summer was very fun because it reminded me of my proposal in 2005 and how I struggled with it.

Then, I and a fellow mentor, Joan Marcano (Batey Lab) gave a Science and Society workshop where we described to the students some ethical issues in research through a Nature article on Cohort studies. It resulted in some discussion on the future of “big data” and the responsibility of having this information. We also took some time during this workshop to talk to the students about the BioFrontiers Institute. There were also some fun times like when the group went on a rafting trip and when we went to Hartford, Connecticut for a symposium at which over 20 programs similar to the SMART program brought their groups of students to present their research for the summer.

In the end, I believe this was a very productive summer, meaningful just like the one in 2005. I joined a lab that I like, work on a project with many facets and issues, and I got a chance to give back to the people who are responsible for me being in my current situation. I was able to help train a very SMART student which was very rewarding considering he is interested in cardiac failure research. Working in a team-fashion with John (biochemist) and Steve (virologist) while training a biomedical engineering student, was just as interdisciplinary of an effort as the first year of IQ biology. I look forward to future challenges such as this one.

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He is interested in applying machine learning and computational statistics to challenges in biology, genomics and engineering. He is also the first student to graduate from BioFrontier’s Ph.D. certificate program in Interdisciplinary Quantitative Biology, or IQ Biology.

“The IQ Biology program encouraged me to continue to straddle the boundary between computation and biology,” said Dan “It exposed me to a new group of scientists and strengthened my foundations in the life sciences.”

Dan defended his thesis work in April 2012, which also earned him the Outstanding Dissertation Award from CU-�鶹ӰԺ’s College of Engineering and Applied Science. During his graduate studies, he spent much of his time in the lab of BioFrontiers faculty member Rob Knight, researching the microbiome.

Dan's advice for incoming graduate students is simple and effective: Learn programming and learn how to write code. Don't be afraid to branch out and explore other disciplines during lab rotations. You might be surprised how these connections make you better at what you do. For an impressive list of Dan's publications, visit . 

The microbiome is the enormous collection of bacterial species that coexist in and on living organisms, including humans, and contribute substantially to our health and disease. The bacteria can be identified indirectly through their DNA genomes, but these experiments generate a vast amount of information. Making sense of all that information required Dan’s computer science expertise.

Dan recently accepted a tenure-track faulty position as an assistant professor of Computer Science at the University of Minnesota, Twin Cities Campus. Before he heads to the City of Lakes, Dan is making a year long stop at The Broad Institute of MIT and Harvard in Cambridge, Mass. to extend his research by doing post-doctoral work. His focus will be a mix of microbiome analysis, and a study of gut microbiota and the human immune response.

“It is unusual for a graduate student to jump right into a tenure-track faculty position, but Dan is unusually talented, and his accomplishments in both computer science and genomics served him well on the job market,” said Tom Cech, Director of the BioFrontiers Institute. “He sets a high standard for students in the IQ Biology program, and we wish him the very best.”

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“I was lucky that I had a graduate advisor who understood that I had 11 Olympic workouts a week,” she says of her graduate experience. “But, being at MIT was a fire hose of fabulous things to think about.”

Bradley acts as an advisor on the Biofrontiers Institute’s graduate program because cross-discipline work is something she is passionate about. Computer science now plays a huge role in managing the massive data sets in the biosciences.

“Computers, by default, are cross-disciplinary. They are used everywhere in scientific discovery. We solve equations with computers because we can’t solve them with pencil and paper,” she says. “And it is because I am open to working across disciplines that I tend to be the home in the department for the student projects nobody else will supervise.”

Rhonda Hoenigman is pursuing a Ph.D., and with Bradley’s encouragement and advice, she has created a computer algorithm that aids in the design of efficient landscapes: those that offer the best growth, with the most shade, using the least amount of water. This “agent-based” algorithm allows the plants to move themselves in a virtual world, and find the places they would grow the best. Hoenigman has a vision for the algorithm to help building planners save water while cooling structures with shade—a necessity for water-starved areas like the American Southwest.

Caleb Phillips, another student who works with Bradley, also created a new algorithm that addresses sustainability: one that can show us how to redistribute food waste.  Phillips’ algorithm takes into account how much food is being thrown away across a given region, like �鶹ӰԺ County, and also calculates the cost of rescuing it and redistributing it to organizations in need across that region.

Most food rescue organizations use a warehouse model, which usually prevents them from handling fresh produce and other perishables. In addition, transportation costs are higher when trucks are needed to deliver food from a central warehouse.

With the help of this algorithm, the organization that Phillips founded, , takes surplus foods from stores and restaurants, and delivers them immediately to organizations that will use them. The kicker: �鶹ӰԺ Food Rescue picks up and delivers food using bikes and trailers, keeping costs at their lowest.

“�鶹ӰԺ 70 or 80 pounds a day is a normal delivery, but we rescued 950 pounds the day after Thanksgiving,” says Phillips, who has to notch his belt a little tighter because of all the bike deliveries he now makes. On days where food donations are too heavy, or the snow is too deep, Phillips’ organization has access to trucks via �鶹ӰԺ’s CarShare program. “There is definitely enough food in �鶹ӰԺ County to feed everyone,” he says.

“It’s not about us faculty, it’s about them, the students,” Bradley says. “That’s what grad school is about.” And it must be that old Olympic discipline she has that allows her to mentor incredible students, while still producing amazing work of her own.

Bradley studies chaos theory and computer performance dynamics. In her work, dropping the last decimal place off of a number that has six places after the decimal may seem insignificant—not even enough to worry about in a huge data set. But those insignificant numbers can have huge impacts across a large collection of data or across a long period of time. This theory is also known as the “Butterfly Effect,” referring to the flapping of an insect’s wing that could cause enough atmospheric change, over time, to create a devastating hurricane. Bradley is using this theory to work toward learning to predict and manage how computers and data interact.

You don’t have to look too hard to see that there is another “Butterfly Effect” going on in Bradley’s world. If chaos theory is predicting how a small change can equal a large effect, you only need to look as far as Bradley’s students to see how her interactions are exactly that: the butterfly’s wing creating a hurricane of change.

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