Blogging community of computational and mathematical oncologists
July 27, 2019 2 Comments
A few weeks ago, David Basanta reached out to me (and many other members of the mathematical oncology community) about building a community blog together. This week, to coincide with the Society for Mathematical Biology meeting in Montreal, we launched the blog. In keeping with the community focus, we have an editorial board of 8 people that includes (in addition to David and me): Christina Curtis, Elana Fertig, Stacey Finley, Jakob Nikolas Kather, Jacob G. Scott, and Jeffrey West. The theme is computational and mathematical oncology, but we welcome contributions from all nearby disciplines.
The behind the scenes discussion building up to this launch was one of the motivators for my post on twitter vs blogs and science advertising versus discussion. And as you might expect, dear reader, it was important to me that this new community blog wouldn’t be just about science outreach and advertising of completed work. For me — and I think many of the editors — it is important that the blog is a place for science engagement and for developing new ideas in the open. A way to peel back the covers that hide how science is done and break the silos that inhibit a collaborative and cooperative atmosphere. A way to not only speak at the public or other scientists, but also an opportunity to listen.
For me, the blog is a challenge to the community. A challenge to engage in more flexible, interactive, and inclusive development of new ideas than is possible with traditional journals. While also allowing for a deeper, more long-form and structured discussion than is possible with twitter. If you’ve ever written a detailed research email, long discussion on Slack, or been part of an exciting journal club, lab meeting, or seminar, you know the amount of useful discussion that is foundational to science but that seldom appears in public. My hope is that we can make these discussions more public and more beneficial to the whole community.
Before pushing for the project, David made sure that he knew the lay of the land. He assembled a list of the existing blogs on computational and mathematical oncology. In our welcome post, I made sure to highlight a few of the examples of our community members developing new ideas, sharing tools and techniques, and pushing beyond outreach and advertising. But since we wanted the welcome post to be short, there was not the opportunity for a more thorough survey of our community.
In this post, I want to provide a more detailed — although never complete nor exhaustive — snapshot of the blogging community of computational and mathematical oncologists. At least the part of it that I am familiar with. If I missed you then please let me know. This is exactly what the comments on this post are for: expanding our community.
Here are the blogs alphabetically by primary author. As a disclaimer, I was not familiar with some of these blogs before David’s spreadsheet introduced them to me, and so my snapshots are incomplete. For each blog, I have tried to highlight a few posts that I’ve found particularly interesting. In some cases, these posts have spawned discussions on twitter or here on TheEGG or other blogs, and so I occasionally highlight those responses as well.:
- David Basanta’s CancerEvo has been especially influential in my own interaction with the mathonco community. On his blog, David has developed new questions like |what is a species in cancer?” (it took me 4 years to come up with an answer to David’s question that I was happy with) and “are algorithms too complex?” (Sometimes they are complex enough to hide lies behind, and especially worrisome if they don’t jive with understanding); and written deep dives like his 3 part mini-series on competition and evolutionary-enlightened treatments: competition, heterogeneity, and treatment.
- Vincent Cannataro’s Blog combines his scientific outreach, announcements, and teaching. For an example, see his interactive evolutionary game teaching aid.
- Andrew Dhawan’s Tabula Rasa presents stories behind the preprints and discusses works in progress like his cursory analysis of the abundance of miRNA or a new hypothesis about circRNA as a cellular speedometer.
- Philip Gerlee’s research focuses on short mind-stretching posts like his observation on how petabytes of data don’t just produce understaning of cancer or that mathonco is lacking a definitive success story (to which Heiko Enderling provided a counter-example and I argued that it isn’t a counter-example).
- Thomas Hillen’s Syndemedic is a new blog with only two posts so far. It started with the question of what does mathematics contribute to oncology?
- Paul Macklin’s MathCancer blog focuses on discussions of his extensive open-source PhysiCell project for simulation cancer cells.
- Florian Markowetz’s Scientific B-sides deals with a wide-range of topics, including commentaries on our community. For example, discussions of reproducible in cancer research and the undue focus on novelty over insight.
- Hitesh Mistry and David Orrell’s Systems Forecasting focuses on simple operationalized models inspired by pharmacokinetic/pharmacodynamic modeling. Some interesting recent posts include discussions of the cancer reproductibility project and the danger of ignoring uncertainty in collaborative conceptual models. Hitesh’s challenges on twitter (alongside Noel Aherne’s provocative response to Sandy Anderson and disagreements with Paul Macklin) have inspired me stretch my views on coarse-graining vs abstraction in models.
- Rob Noble’s These few lines combines both discussions of ideas, code, and metamodeling. For example, Rob uses his blog for explaining newly developed open source code like ggmuller, introducing his (now) iconic Box-Einstein plot for the tradeoff between model ‘wrongness’ and complexity (in part as a response to my thoughts on wrongness and to which I eventually replied with the Noble Eightfold Path to Mathematical Oncology that built on Rob’s metamodeling tweet), or pointing out the ambiguity in the use of ‘de novo resistance’ between biologists and clinicians (this prompted me to write on other qualitative difference between biological and clinical concepts of resistance).
- Jan Poleszczuk’s Compute Cancer on general computational topics of interest to oncologists like how to estimate uncertainty in treatment outcomes of ODE models, or how to avoid boundary effects in ABMs by dynamically expanding lattices. Jan focuses on general computational techniques that are useful for all modelers but aren’t necessarily linked to any specific traditional publication. I think that this sort of writing about the art and practice of modeling is very important.
- Jacob Scott’s Connecting the dots focuses on the behind-the-papers discussions of his publications, and occasionally discusses work-in-progress like his reflections on evolutionary graphs in cancer.
- Ryan Schenck’s Blog focuses on his journey as an interdisciplinary Genomic Medicine and Statistics DPhil student dividing his time between Oxford and Tampa. Alongside discussions of his progress, presentations, and papers, he also writes posts about the mathonco community. For example, his post on where mathematical oncology fits in the research ecosystem that was prompted by twitter discussions with Jeffrey West and in part as a reflection on Rob Noble’s controversial division of mathematical vs computational biology (a distinction to which I’m inclined to add algorithmic biology as a third alternative).
Prior to the new computational and mathematical oncology blog launching, the Theory, Evolution, and Games Group encouraged posts from members of the mathematical oncology community and includes contributions on oncology from: Vincent Cannataro on dark selection from spatial cytokine signaling networks; Jill Gallaher on diversity working together: cancer, immune system, and microbiome; Philip Gerlee and Philipp Altrock ask is cancer really a game?; David Robert Grimes on oxygen fueling dark selection in the bone marrow; Dan Nichol on how evolutionary non-commutativity suggests novel treatment strategies; Rob Noble on cancer, bad luck, and a pair of paradoxes; Robert Vander Velde on cancer metabolism and voluntary public goods games, and ratcheting and the Gillespie algorithm for dark selection; and Matthew Wicker on identifying therapy targets & evolutionary potentials in ovarian cancer.
Although in the future, I will be directing mathonco writers and posting my own mathematical oncology contributions on the new blog. If you want to pitch a post idea for the new blog, please free to email me or chat with me in person if you’re in the Oxford area.
Finally, are there any blogs that I missed? Or any particularly exciting posts that I should have highlighted? Please let me know.
Maybe I should make a blogroll.
Thanks for including me. Does this mean I have to start writing again?
Yes. I think this means you are contractually obliged to blog again.
But in all seriousness, it would be great to have you blogging again. Either on your blog or on the new comp&math onco community blog.
I think people would be especially interested in hearing more about your ‘all biology is computational biology’ perspective. For example, I have some objections based on algorithmic biology not being computational biology that I’ve been meaning to write about. In general, I think your article and follow up posts are great conversation starters. Something like ‘all oncology is computational oncology’ focusing the arguments from your paper to cancer research would be a nice contribution to the new blog!