Cancer Data Science Pulse

Hone Your Communication Skills: “Weird” Cancer and Data Science Terms to Know!

If there’s one thing both cancer researchers and data scientists have in common, it’s that we get creative when we name our tools and concepts. From “sonic hedgehogs” to “thunking,” we sure know how to turn a phrase.

While that makes our communications together interesting, it doesn’t always lead to successful collaborations. Let’s identify and define some of the terms and phrases that might come up when working on a trans-disciplinary, cancer data science team. Then, we’ll explore five tips for more effective communication when working on said team!

There are a lot of weird data science and cancer research terms. Leave a comment to share what your favorites are and how you learned them!

Sonic Hedgehog

You’re a data scientist, and your cancer research colleague says that he recently read a paper about the role of Sonic Hedgehog and cancer survival rates. You’re a fan of the videogame, but what does that have to do with cancer?

The answer is nothing. Your colleague is actually referring to a type of protein: the Sonic Hedgehog (SHH) protein. Researchers have found that SHH’s signaling, expression, and levels impact tumor growth and patient survival and prognosis.

Person with headphones on, holding a game controller and cheering. Gold rings in the background.

The Curse of Dimensionality

You’re a cancer researcher, and your data science colleague is trying to explain the “curse of dimensionality” to you. She says that “when the number of dimensions grows, the amount of data needed to accurately generalize grows exponentially,” but the definition feels vague to you. You don’t quite understand.

You ask your colleague for a simplified example, and she says it’s when an increase in the number of features used to describe the data makes it so you need more data points to draw meaningful conclusions. With each feature (like age, number of cancerous nodes, type of tumor, patient history, etc.), the number of data points you need increases.

person in a lab coat pointing to a screen, presenting a chart with an upward curve


You’re a cancer researcher talking to your data scientist colleague about what tool might be good to help you integrate multiple data sets for analysis. Your colleague suggests DIABLO, and while it at first makes you think of an extra spicy hot sauce, you head to the internet and dig deeper!

You find that DIABLO stands for “Data Integration Analysis for Biomarker Discovery using Latent cOmponents.”

hot chili peppers, spices, and hot sauce in a bowl on a table


You’re a data scientist analyzing data about something called “ELMO.” You have fond memories of a certain childhood character but are curious what this term means for cancer research.

Your colleague is happy to explain! ELMO stands for “Engulfment and Cell Motility” and is a family of related proteins involved in intracellular signaling networks.

child looking at a tv screen with a portion of red teddy bear on the screen

Shotgun Sequence

You’re a data scientist, and your cancer research colleague says he’s working on shotgun sequencing and asks if you can help with some analysis. You’re very familiar with data analysis but haven’t heard the term shotgun sequencing before.

Your colleague explains that shotgun sequencing is a laboratory technique for determining the DNA sequence of a genome.

DNA sequence

Five Tips for Effective Communications

Now that we’ve had some fun with weird and interesting data science and cancer research terms, let’s explore ways you can improve your collaboration skills when working on a trans-disciplinary team!

  1. Recognize differing knowledge and experience.
    • Remember that each person brings a different background to the team. How different that background is will vary from person to person! So, while you may tend to assume that your colleagues know the same (or similar) information as you, that’s often not the case.
  2. Use the most straight-forward language that will maintain accuracy. 
    • Sure, you could refer to Sonic Hedgehog when talking to a data scientist, but do you need to? Would what you’re telling them make sense (and be informative enough) if you called it a protein? Sometimes the answer will be yes, and other times, you need to be specific, and that’s okay. Judge for yourself in each situation, and see if you can identify instances where you can swap more basic language for those niche terms!
  3. Include helpful context clues. 
    • Similar to the previous tip, when you do use those potentially confusing terms, make a habit of adding context clues! For instance, if you mention DIABLO, volunteer the additional information that it’s a good tool for integrating multiple data sets for analysis. Adding context can help your colleagues follow along with conversations that might otherwise be outside their experience.
  4. Develop a shared team communication style.
    • Over time, you and your colleagues on a trans-disciplinary team will (ideally) develop a shared communication style. You’ll accumulate vocabulary and definitions that are specific and relevant to your work together. By committing to working together to resolve confusion, you’ll build trust, and communication will get easier (and stronger).
  5. Embrace asking questions!
    • Last, but far from least, asking questions (and being willing to answer them yourself) will help you avoid misunderstandings and ensure your team functions more efficiently. Remember, your colleagues are a resource!
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