21
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Crossing Over…Markov Meets Mendel

      research-article
      *
      PLoS Computational Biology
      Public Library of Science

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Chromosomal crossover is a biological mechanism to combine parental traits. It is perhaps the first mechanism ever taught in any introductory biology class. The formulation of crossover, and resulting recombination, came about 100 years after Mendel's famous experiments. To a great extent, this formulation is consistent with the basic genetic findings of Mendel. More importantly, it provides a mathematical insight for his two laws (and corrects them). From a mathematical perspective, and while it retains similarities, genetic recombination guarantees diversity so that we do not rapidly converge to the same being. It is this diversity that made the study of biology possible. In particular, the problem of genetic mapping and linkage—one of the first efforts towards a computational approach to biology—relies heavily on the mathematical foundation of crossover and recombination. Nevertheless, as students we often overlook the mathematics of these phenomena. Emphasizing the mathematical aspect of Mendel's laws through crossover and recombination will prepare the students to make an early realization that biology, in addition to being experimental, IS a computational science. This can serve as a first step towards a broader curricular transformation in teaching biological sciences. I will show that a simple and modern treatment of Mendel's laws using a Markov chain will make this step possible, and it will only require basic college-level probability and calculus. My personal teaching experience confirms that students WANT to know Markov chains because they hear about them from bioinformaticists all the time. This entire exposition is based on three homework problems that I designed for a course in computational biology. A typical reader is, therefore, an instructional staff member or a student in a computational field (e.g., computer science, mathematics, statistics, computational biology, bioinformatics). However, other students may easily follow by omitting the mathematically more elaborate parts. I kept those as separate sections in the exposition.

          Related collections

          Author and article information

          Contributors
          Role: Editor
          Journal
          PLoS Comput Biol
          PLoS Comput. Biol
          plos
          ploscomp
          PLoS Computational Biology
          Public Library of Science (San Francisco, USA )
          1553-734X
          1553-7358
          May 2012
          May 2012
          17 May 2012
          21 May 2012
          : 8
          : 5
          : e1002462
          Affiliations
          [1]Department of Computer Science, Hunter College of CUNY, New York, New York, United States of America
          Whitehead Institute, United States of America
          Author notes
          Article
          PCOMPBIOL-D-11-01246
          10.1371/journal.pcbi.1002462
          3355070
          22629235
          2d655315-ef5a-4c34-a3b9-10a4b9ccb459
          Saad Mneimneh. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
          History
          Page count
          Pages: 12
          Categories
          Education
          Computer Science

          Quantitative & Systems biology
          Quantitative & Systems biology

          Comments

          Comment on this article