By Alexander Titus, Colossal Biosciences
We have entered a remarkable new age in biology and biologics development. Like many other fields, biology is undergoing a technological revolution with an increasing focus on software-dependent and data-driven results. Integrating the biological and the computational creates a need for specialists working together in parallel. But how well-versed do you need to be in other departments? How important is it for biologists to understand computer science and for computational professionals to grasp biology?
Across government agencies, tech giants, and pharma innovators, it is clear that biologists and computer scientists play unique and equally important roles. Here we describe how communication between these two distinct pillars of knowledge forms the linchpin of transformative discovery.
Communicate Early And Often
Biologists and computer scientists play entirely different roles in scientific discovery, and keeping the distinction between these two disciplines is essential for specialization and effective economies of scale. However, as the lines between these two roles become increasingly blurry, they must partner together early on.
Increasingly, biological discovery is inherently intertwined with large and complex data sets. At the onset, biologists should bring on technical experts to assist in data processing, storage, and presentation. Conversely, computational biologists should feel comfortable leaning on their biological counterparts for context and knowledge. Allowing each of these experts to contribute their perspectives and needs will strengthen the project as a whole.
Context is everything. Biologists know the complex biological context of scientific questions and often need computational expertise to execute their vision. Computational biologists know the limits and caveats of computational approaches, which are essential for accurate biological interpretation. To harness the power of both experts, frequent communication is critical. As projects increasingly require an integrated approach, clear and consistent communication between the two partners is the guidepost that will lead a project to success.
What Effective Communication Looks Like
It’s rare to find someone who excels in biology and computer science, as these are both complex disciplines that require years to master. So, instead of holding out for “unicorns” that can do both, companies should invest in specialists — biologists for biology and computer scientists for computation – and then teach them how to work together.
Luckily, effective communication between these two groups is straightforward:
- Define goals together
- Set clear expectations for success
- Discuss progress regularly
- Brainstorm next steps
- Standardize communication
Defining goals together ensures that biologists and computer scientists speak the same language from the outset. For example, working on a CRISPR screen might have the ambiguous plan of “identify transcriptional changes after knockout of gene XYZ.” That seems straightforward in theory, but the team should define what success looks like together. The biologist should convey to the computer scientist which log-fold change cutoff in expression is biologically significant, why this might be different for transcription factors compared to effector proteins, and why the results are important. The computer scientist should explain the various approaches to normalize and align the data and each choice's pros, cons, and interpretation limitations. RNA-seq is a seemingly simple experiment with infinite complexities.
While setting clear expectations for success is essential in any discipline, it’s particularly critical in the sciences as success is often knowledge rather than a particular outcome. Returning to our RNA-seq knockout example, is success measured by the absolute number of genes with changed expression? Consistency between replicates? Identifying one key target to move forward with? These are critical questions on which the biological and computational teams need to be aligned.
Teams should hold meetings with three objectives that dovetail together for continuous progress: discuss results, interpret data, and brainstorm the next steps. We recommend at least biweekly meetings, but the more frequent the better. During these meetings, employees in both roles should be empowered to participate in decision-making and establish standardized communication protocols across an organization to ensure all multifaceted teams are engaged in regular productive communication.
While we continue to advocate for specialization, effective communication requires biologists and computer scientists to speak the same language. For that, biologists and coders need to do some homework. Here are our favorite resources to understand your teammates on the other side of the terminal:
Integrated Teams Ensure Success
Science needs more teams with biologists and computer scientists. How to ensure effective communication across these teams is not always clear. We’ve laid the groundwork for solid project-oriented communication with these teams to get you started. For a deeper dive, the ten simple rules for collaboration are another great resource.
To capitalize on specialization, biologists need to be able to focus on biology and computer scientists on computer science. Creating integrated teams with individual specialists ensures you get the best of each field rather than a half-baked representation of both. The key to success in these relationships is effective communication. Starting early, meeting regularly, aligning on goals, and standardizing communication workflows is the pathway to success.
About The Author:
Alexander Titus is vice president of strategy and is also on the scientific advisory board of Colossal Biosciences. His career spans senior roles with Google, the U.S. Department of Defense, and McKinsey. He holds a Ph.D. in quantitative biomedical sciences from Dartmouth College, a BS in biochemistry, and a BA in biology from the University of Puget Sound.