↓ Skip to main content

PLOS

Crossing Over…Markov Meets Mendel

Overview of attention for article published in PLoS Computational Biology, May 2012
Altmetric Badge

Mentioned by

twitter
13 X users

Citations

dimensions_citation
64 Dimensions

Readers on

mendeley
155 Mendeley
citeulike
7 CiteULike
Title
Crossing Over…Markov Meets Mendel
Published in
PLoS Computational Biology, May 2012
DOI 10.1371/journal.pcbi.1002462
Pubmed ID
Authors

Saad Mneimneh

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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 155 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 6%
Germany 3 2%
Portugal 2 1%
Netherlands 2 1%
Brazil 2 1%
Uruguay 1 <1%
France 1 <1%
Colombia 1 <1%
Peru 1 <1%
Other 3 2%
Unknown 129 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 45 29%
Student > Bachelor 22 14%
Student > Ph. D. Student 21 14%
Professor > Associate Professor 15 10%
Student > Master 7 5%
Other 22 14%
Unknown 23 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 59 38%
Biochemistry, Genetics and Molecular Biology 34 22%
Medicine and Dentistry 7 5%
Computer Science 7 5%
Neuroscience 4 3%
Other 17 11%
Unknown 27 17%