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Episode 13 - Daniel Zuckerman: Trajectory ensembles, writing books, and learning biology through physics

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Innhold levert av Miłosz Wieczór. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Miłosz Wieczór eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

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In the thirteenth episode, Daniel Zuckerman and I talk about textbooks on statistical biophysics and a physics-based vision of biology, a few of which he himself authored. Daniel reveals that his passion for clarity in writing comes from his early humanities background, and makes a case for how well-thought and physically motivated narratives can unlock profound insights into the inner workings of biology. Then, we move on to discuss the physical theory behind trajectory ensembles, Daniel's preferred lens through which to view statistical mechanics. We dissect the strengths and limitations of this approach, and let ourselves speculate about its future evolution.

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27 episoder

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iconDel
 
Manage episode 424267249 series 3555369
Innhold levert av Miłosz Wieczór. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Miłosz Wieczór eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.

Send us a text

In the thirteenth episode, Daniel Zuckerman and I talk about textbooks on statistical biophysics and a physics-based vision of biology, a few of which he himself authored. Daniel reveals that his passion for clarity in writing comes from his early humanities background, and makes a case for how well-thought and physically motivated narratives can unlock profound insights into the inner workings of biology. Then, we move on to discuss the physical theory behind trajectory ensembles, Daniel's preferred lens through which to view statistical mechanics. We dissect the strengths and limitations of this approach, and let ourselves speculate about its future evolution.

  continue reading

27 episoder

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