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In episode 26, we talk about the origins of Pratyush's passion for statistical mechanics, deeply rooted in his background in material science, and think about how we can promote a profound understanding of statmech theory among people working in computational biophysics. From there, we explore ways of re-introducing physical rigor into modern data-driven approaches, which is the main concern that Pratyush says drives his research agenda. He ends up sharing a ton of interesting points on working with the industry, the value of education and knowledge sharing, or the philosophy of complex and cognitive systems, and ends up with a call for more time for silent thinking, where - he says - most of his original ideas came from.
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In episode 25, Ivet and me start with a general overview of the elastic network theory and its applications to biology, as well as its strengths and limitations. Ivet then tells us about the specific takeaways from the different lines of her research, talking about evolutionary dynamics signatures, mode excitations in allosteric effects, as well as her recent research on the relevance of hinge regions for drug discovery. We talk about the relevance of the proteins-as-graphs picture for machine learning, and end up with a few general reflections about the complementary roles of persistence and alertness in scientific careers.
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In episode 24, Katarzyna talks about the everyday concerns and common threads of an editor's job, from continuously learning about the rapid developments in the field to navigating the review process. She shares some inside stories about the experimental features that journals tinker with these days, and it's good to know that many interesting ideas are being tested out there in the wild. We then discuss a bit about the evolution of the publishing process, including its perception among us research scientists. We largely leave the questions of profits and finance out of the conversation, so this is purely a conversation between two science aficionados who care deeply about the scientific enterprise being transparent, just, open to novelty and focused on quality evidence.
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In episode 23, Zoe and me discuss the current status and promises of drug design, a field where many things seem trivial but nothing is really simple. Zoe talks about the challenges that precision medicine is facing, and how it fits into the grand landscape of future therapies. We go through some success stories, and I ask Zoe how the recent additions to drug design workflows help them in everyday scientific practice, both in terms of physics-based and data-driven models. We then spend a moment talking about the opportunities and responsibilities of a journal editor, and what are the lessons Zoe learned from creating her startup.
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In episode 22, we start by talking about the 2022 review of enhanced sampling methods that Lucie co-authored, one that provides long-needed organizing principles and unifying vocabulary for applications in this field. We also outline some challenges and community needs still waiting for the bold souls out there looking for ambitious projects. Lucie then moves on to share her experience with alternative publishing models, both as a member of Biophysics Colab and a former editor of eLife, and we dwell a bit on the challenges and possible solutions to what some would call a crisis in publishing, where evaluation metrics and publishing companies created unsustainable or even counterproductive incentive structures in sharing scientific results. We end on personal notes: already last year when I was visiting her lab in Stockholm, Lucie agreed to be on the very first list of interviewees, but it took me so long to figure it out that eventually Lucie gave birth to her twins and went on a maternal leave, so now that she's back more than a year later, I also asked her to share a few reflections on becoming a parent in academia.
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In episode 21, Tamar first explains how her unique background impacted the way she approached and conceptualized problems in biology, and how her research projects were born in the first place. We talk about the more recent research coming from Tamar's group on frameshifting, a fascinating process by which the readout of the genetic code can be offset by one or two letters to produce multiple proteins from a single viral gene. We then move on to discuss whether it's algorithms or compute that have contributed more to the growth of computational biophysics. Tamar's textbook and the multiple perspective articles she's written over the years serve us to dwell on the importance of writing for clarity and interdisciplinary collaboration. We end on a people-centric note, talking about the social bonds involved in both running and experimental collaborations.
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In episode 20, I start by asking Rommie how their research on the SARS-CoV-2 virus first unfolded during the early days of the pandemic, and from this story, we move on to discuss her original motivation to study large complex systems. We touch upon the exciting experimental developments that enable the realistic modeling of systems as big as entire viruses, and highlight some unexpected findings that came out of the large-scale simulations. Rommie also shares her reflections about the collaboration-driven nature of her lab and the complexities involved in interdisciplinary communication, and we wrap up with a few thoughts about the AI-driven brain drain from academia to industry.
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In episode 19, Alex and I discuss the history and future of developments in the CHARMM family of force fields, and whether Alex believes there is more physics that we need to include in our classical energy functions to work around our current challenges in biomolecular modeling. Throughout the conversation, he's advocated for a pragmatic, down-to-earth approach, with the idea of "big molecules, small physics". Alex also highlights the need to augment AI tools with HI, or human intelligence, arguing that so far most attempts at automating model development too much end up with parameters that are unphysical and non-transferable. Yet another interesting point is our often surprising reliance on truly ancient experimental data, and we try to make a point that these very non-sexy physical chemistry measurements straight from the 60s and 70s could truly advance the field if anyone was willing to fund them and actually get them done.
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In Episode 18, Erik Lindahl reminds us that despite our dependence on computational power and advanced technology, real breakthroughs are often waiting for those who have the patience to think carefully, come up with eye-opening ideas, and follow their sense of purpose. We discuss the different ways to be smart in science, highlighting the paradoxical need for both complexity and simplicity in thinking, and talk about what kind of questions in biology will keep us all busy for decades to come. Finally, Erik shares the story behind his series of lectures on concepts in molecular biophysics, a great component of the curriculum of every scientist in the field.
From the publisher's feed
With the convergence of data, computing power, and new methods, computational biology is at its most exciting moment. At PSI, we're asking the leading researchers in the field to discover where…