Hello, my name is Miguel. I’m a PhD student at the Schwartz Lab of the Weizmann Institute of Science. I am a biologist with great interest in understanding life from a quantitative, mechanistic and systematic perspective. My current efforts are focused on advancing the understanding of RNA modifications. And, I am from Mexico!
In the Schwartz lab, we work in the field of Epitranscriptomics, a relatively new and booming research field that deals with the biochemical modifications of RNA molecules of all living organisms and even viruses. My current work revolves around the RNA modification m6A. m6A is a highly abundant RNA modification present in all eukaryotes, and it has recently received attention as a potential therapeutic target for treating diseases such as Cancer, Osteoporosis, Obesity, and Diabetes. In my latest published work, we developed a methodology that is able to detect and quantify m6A in a high-throughput, single-nucleotide, and antibody-independent manner. We also uncovered a code that dictates m6A deposition across the transcriptomes of mouse and yeast, making m6A deposition predictable.
- 25-Oct-2020 - Teaching: Principles and practice of large scale data analysis using R 2021-1 course starts. Recordings available for WIS students and auditors
- 16-Oct-2020 - Published work: González et al., “Tolerance to Oxidative Stress in Budding Yeast by Heterologous Expression of Catalases A and T from Debaryomyces hansenii”
- 17-February-2020 - Poster: ILANIT-2020:; BioTrivia 1st place Winner! :) Video.
- 24-October-2019 - Short talk: “MAZTER-seq and the m6A code” Slides, 2019 RNA Biology and Processing meeting in memory of Prof. Yossi Sperling, Tel Aviv, Israel.
- 05-August-2019 - Media coverage: Sneaky RNA Tag Rendered Visible, article covering the publication of our work developing MAZTER-seq
- 27-June-2019 - Published work: Garcia-Campos, et al. “Deciphering the “m6A Code” via Antibody-Independent Quantitative Profiling.” Cell (2019).
- 4-March-2019 - Published preprint: Garcia-Campos, Miguel Angel, et al. “Deciphering the’m6A code’via quantitative profiling of m6A at single-nucleotide resolution.” BioRxiv (2019): 571679.