Show Notes
For people who work in the life sciences, a very common occurrence is for folks who work on the "wet" side of research, largely doing bench work, to become interested in or start wanting to transition to doing more "dry" research, like computational research in bioinformatics. In this special episode, dedicated to those thinking about transitioning from "wet" lab work to doing more "dry" lab type work, my guest Dr. Willian da Silveira explains his own transition from a full bench scientist to a full time bioinformatician. Dr. da Silveira also answers many questions from the bioinformatics subreddit on this topic. Following Dr. da Silveira's explanation of his career trajectory and his own shift from "wet" lab work to "dry" lab work, I ask a series of questions from the bioinformatics subreddit seen below, with time stamps included:
[19:00] Bioinformatics subreddit questions begin.
[20:00] What general stats and technical requisites are necessary to transition from wet lab to dry lab work?
[23:30] Is it boring to only do data analysis versus conducting lab experiments?
[27:50] Should you transition early, for example during a masters or PhD program, or can it be done later?
[33:30] Does the transition need to be forced or does it happen more often by chance?
[35:10] Is there a downside to being self-taught as a bioinformatician?
[36:20] What are the upsides of picking up bioinformatics later on, starting as a wet lab scientist first?
[40:25] How to get accepted into a bioinformatics PhD program with no formal CS education?
[42:07] What about dry lab to wet lab transitioning?
[48:07] How do you get your foot in the door when switching from the wet lab to a dry lab with little or no dry lab experience on your CV?
[50:45] If you do feel stuck, would the best route be to go ahead and pick up some formal education like a paid masters degree?
[52:48] Would it make sense to transition to dry lab work given employment and financial considerations?
Finally, to end the discussion, I ask Willian what he thinks the ideal mix of wet lab and dry lab experience might look like.
More from The Bioinformatics and Beyond Podcast
Dr. Justin Siegel begins this episode by explaining what enzymes are, how they have evolved, and why Dr. Siegel is motivated to try to engineer enzymes to perform functions tailored to help humanity instead of to perform functions based on how they evolved in nature. He explains the primary goal of the work discussed and relating enzyme sequence to function. Dr. Siegel also explains how his work was the first of its kind by scaling up enzyme design to hundreds of mutants instead of dozens.
Dr. Justin Siegel explains the past, present, and future of wet lab work and wet lab automation. We start by hearing a description of what it is like to work in a wet lab, covering the contrast between the excitement of seeing life changing results and the countless hours of monotony that is often involved to produce these results.
Dr. Afshin Beheshti begins this episode by explaining what microRNAs are and why they are emerging as an important area of biological research. He then explains how microRNAs relate to viruses, which is a recently developing area of research in this already young field of study. Dr. Beheshti then tells the story of how he started to discover that microRNAs could be a driver of COVID-19 infections.
This episode concludes the podcast’s series of episodes focused on space biology and space omics. NASA scientist Dr. Afshin Beheshti discusses the many high level hazards and corresponding molecular features of spaceflight throughout this episode. For instance, we begin with a discussion of the hazards of radiation and microgravity. Dr. Beheshti spends time explaining a high level view of what each hazard is, why it is a concern for spaceflight, and educates us on many useful and interesting pieces of information for each hazard. Further hazards discussed include confinement and isolation, hostile and closed environment, and distance from Earth.
This episode discusses Dr. Tejaswini Mishra’s recent publication in Nature Biomedical Engineering: https://www.nature.com/articles/s41551-020-00640-6 Dr. Mishra begins the episode by explaining the origin story of this work and how the idea for this paper came to be. She then explains how this study enrolled thousands of participants and used the participants’ smartwatch or wearable device data to detect COVID-19 infections. After explaining how this study began, Dr. Mishra discusses how she and her team came up with two main algorithms for detecting COVID-19 infections from wearables data. Dr. Mishra also discusses the many variables that could be monitored with wearables in addition to standard measures used for predicting illnesses like heart rate. Finally, we hear about the main results of this study including the successful detection of several active COVID-19 infections in study participants. We also hear a comparison of this work against the COVID-19 wearables study featured previously on the podcast. We end by hearing Dr. Mishra’s thoughts on the future of wearables for detecting infectious diseases and for improving human health in general.