This episode was originally published in 2018. It's one of our most popular episodes of all time, so we decided to run it again while we're in between seasons. Look for new Big Bio episodes in August. 
What is life? How did life arise from non-life? What did life look like at its origin?



Tune into this podcast to hear Art and Marty talk with Sara Walker, an expert in astrobiology and theoretical physics at Arizona State University. They discuss how life might have arisen on Earth and why biologists and physicists should work together to find a theory of life.
Her ideas could help decide what to do about artificial intelligence (SPOILER: The robots will take over, but it’s going to be OK). They might also help us find life on other planets.

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RE-RUN: Information, Aliens and the Origin of Life

The biggest biology podcast for the biggest science and biology fans. Featuring in-depth discussions with scientists tackling the biggest questions in evolution, genetics, ecology, climate, neuroscience, diseases, the origins of life, psychology and more. If it's biological, groundbreaking, philosophical or mysterious you'll find it here.  Support this podcast: https://podcasters.spotify.com/pod/show/bigbiology/support

Science

Life Sciences

This week on Big Biology we're sharing an episode from The Naked Scientists Podcast about how humans lost their tails.
Humans, chimpanzees, gorillas and orangutans do not have tails. It sets us apart from other primates, but suggests that our shared evolutionary ancestors had them. So why did we lose them, and how? Speaking with Chris Smith, from The Naked Scientists Podcast, NYU Grossman School of Medicine's Itai Yanai explains that the way this study began was literally a pain in the "tail" for one of his colleagues...
Credit: The Naked Scientists Podcast

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Big Biology Presents: The Naked Scientists Podcast

At what levels does causation happen in biology? Are metaphors useful for understanding biology?
In this episode, we talk with Phil Ball, a science writer who was also an editor for the journal Nature for over 20 years. Phil has written over 25 books, but our conversation focuses on his most recent: “How Life Works: A User’s Guide to the New Biology.” In the book, Phil covers a wide-range of topics from cells to proteins to biological agency, and makes the argument that traditional ideas and simplified metaphors in biology often don’t hold up. We talk with Phil about the concept of the selfish gene and unpack what it actually means and when it’s useful. Then we dive into the paradox of how multicellular organisms are composed of multiple levels of agency, yet are complex agents themselves. Phil also discusses the biomedical implications of thinking about cancer as one in many possible states that cells can inhabit across a landscape.

Art by Keating Shahmehri. Find a transcript of this episode on our website.

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Biology as its own metaphor (Ep 119)

How should biologists deal with the massive amounts of population genetic data that are now routinely available? Will AIs make biologists obsolete?
In this episode, we talk with Andy Kern, an Associate Professor of Biology at the University of Oregon. Andy has spent much of his career applying machine learning methods in population genetics. We talk with him about the fundamental questions that population genetics aims to answer and about older theoretical and empirical approaches  We then turn to the promise of machine learning methods, which are increasingly being used to estimate population genetic structure, patterns of  migration, and the geographic origins of trafficked samples. These methods are powerful because they can leverage high dimensional genomic data. Andy also talks about the implications of AI and machine learning for the future of biology research. 
Cover Art by Keating Shahmehri. Find a transcript of this episode at our website.

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Dog in the Machine (Ep 118)

How should we study complex biological networks? How do cells keep time and stay in sync? What does it mean for a network to be resilient?
In this episode, we talk with Rosemary Braun, Associate Professor at Northwestern University in the Department of Molecular Biosciences and a member of the NSF-Simons Center for Quantitative Biology. Rosemary is broadly interested in learning whether “more is different” when it comes to complex molecular networks operating across different temporal and spatial scales. We talk with her about systems approaches to uncovering the “Rules of Life” and about circadian (daily) rhythms. She and her team use machine learning to understand emergent phenomena in networks, with the goal of helping medical professionals target treatments based on an individual patient’s circadian rhythm.
Cover art: Keating Shahmehri. Find a transcript of this episode on our website.

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The time of your life (Ep 117)

How do biologists strike a productive balance between descriptive natural history and manipulative experiments in the lab or field? Should we bring back species to areas where they’ve gone extinct and what values do we use to make these decisions? What is wildness and how do we cultivate it?
On this episode, we talk with Harry Greene, a herpetologist and adjunct professor of Integrative Biology at the University of Texas at Austin, whose distinguished career has spanned decades. Harry is an E.O. Wilson Award recipient and also received the PEN Literary award for his book, Snakes: The Evolution of Mystery in Nature. In the episode, we talk with Harry about the importance of natural history to biology. We also tackle the topic of rewilding, a type of biological restoration that involves translocating species where they still occur to regions where they no longer are found, in order to restore ecosystem function. Harry talks about how his views on rewilding have changed over time, including how rewilding ourselves could improve our health and happiness

Cover art: Keating Shahmehri. Find a transcript of this episode on our website.

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Support this podcast: https://podcasters.spotify.com/pod/show/bigbiology/support

RE-RUN: Information, Aliens and the Origin of Life

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