Translating Proteomics Nautilus Biotechnology

AI might be the biggest buzz word of the decade, but the buzz is warranted in terms of its practical potential in biological research. In this episode of Translating Proteomics, Parag and Andreas discuss some of the early wins for AI in biology, practical ways AI can be applied to biology research in the near term, challenges in that application, and how proteomics researchers in particular can use AI to advance their work.
Chapters:
00:00 – Why now is the time to apply AI to biomedicine05:28 – Difficulties and potential solutions when applying AI to biology14:20 – How AI will impact the study of proteins19:34 – Risks of AI in biomedicine

From high school biology on up, we're taught the central dogma of biology - that biological information flows from DNA to RNA to proteins. This representation of the central dogma is, however, very much a simplification of its original formulation by Francis Crick and over-applying it can lead us down spurious paths and faulty conclusions. In this episode of Translating Proteomics, Parag and Andreas dive into the real meaning of the central dogma and discuss how modern biology research, including proteomics, shows we must drastically alter the ways we use and interpret the central dogma.
Chapters:
00:00 – What is the central dogma and how is it misinterpreted?
08:06 – Regulation and control in biology
11:58 – The need for new models in biology

Protein biomarkers are proteins measured as indicators of biological processes. People often hope biomarkers will take the form of elevated or decreased amounts of single proteins, but few single protein measurements provide specific and sensitive indications of biological processes. In this episode of Translating Proteomics, Parag and Andreas discuss why it is difficult to find new biomarkers and describe how new techniques can enable the development of multi-protein, multi-time point, and even multiomic biomarkers that have more potential than any single protein measurement.
Some key points of discussion:
Biomarkers are difficult to find because of the methods we use to find them and because there is a ton of variability in natural biological systemsMost proteins are biomarkersWe need more proteome-scale data over space and time to find new biomarkers
Learn more about biomarkers.
Let us know what you think about the podcast.

It's no surprise that biological systems change dramatically over space and time, but we often ignore these dynamics when comparing biological samples. In the latest episode of Translating Proteomics, Parag and Andreas discuss why it's essential to take space and time into account and envision ways we can design experiments that explicitly incorporate spacial and temporal considerations.
Chapters:
00:00 - Biological systems as dynamic, adaptive systems
04:45 - How current experimental designs rarely take space and time into account
11:54 - The tools necessary to sufficiently measure biology in space and time
Some key takeaways from the conversation:
Different biological processes occur at very different time scalesComplex, multiomic interactions can only be understood over time and spaceWe need to properly collect, annotate, and share omics-level data in order to understand the rules that govern complex biology
Let us know what you think about the podcast.

Sure, proteomics may revolutionize precision medicine and biomarker discovery, but did you know it can help make better cheese? Listen to the latest episode of our new series, "Translating Proteomics" featuring Nautilus Co-Founder and Chief Scientist, Parag Mallick, and Nautilus Senior Director of Scientific Affairs and Alliance Management, Andreas Huhmer to learn the many ways we can put the proteome to work as the proteomics revolution begins to bear fruit.
Let us know what you think about the podcast.
Learn more about applications of proteomics
In this episode, Parag mentions work from Matthias Selbach's Lab. Learn more about the Selbach Lab here.

The idea to measure the proteome to get a clear understanding of healthy and diseased tissues at the molecular level has been around for many years but has not come to fruition in a broadly accessible and applicable way. In this episode we discuss:
Why now is the time to make this goal a realityWhy past efforts to broadly leverage proteomics did not work outWhat we've learned from the pastWhat's changed in proteomics and science in general that makes a proteomics breakthrough possible
Learn more about proteomics
Let us know what you think about the podcast.