<p>In this episode, <a href="https://lindsaykpino.com/">Lindsay Pino</a> discusses the
challenges of making quantitative measurements in the field of proteomics.
Specifically, she discusses the difficulties of comparing measurements across
different samples, potentially acquired in different labs, as well as a method
she has developed recently for calibrating these measurements without the need
for expensive reagents. The discussion then turns more broadly to questions in
genomics that can potentially be addressed using proteomic measurements.</p>

      

      
      <p>Links:</p>
<ul>
  <li><a href="https://www.talus.bio/">Talus Bioscience</a></li>
  <li><a href="https://pubs.acs.org/doi/10.1021/acs.jproteome.9b00666">Matrix-Matched Calibration Curves for Asssessing Analytical Figures of Merit in Quantitative Proteomics</a>
(Lindsay K. Pino, Brian C. Searle, Han-Yin Yang, Andrew N. Hoofnagle, William S. Noble, and Michael J. MacCross)</li>
</ul>

#60 Differential gene expression and DESeq2 with Michael Love

A podcast about computational biology, bioinformatics, and next generation sequencing.