Algebraic and Combinatorial Computational Biology

Raina Robeva was born in Sofia, Bulgaria. She holds a Ph.D. in Mathematics from the University of Virginia and is a Professor of Mathematics and a Karl E. Peace Fellow in Mathematics at Randolph-Macon College in the United States. Her current research is in the broad fields of mathematical and systems biology. In addition to editing this second edition, she has authored and edited several books, including A Bridge to Higher Mathematics (CRC Press, 2024), Algebraic and Combinatorial Computational Biology (Academic Press, 2019), and Algebraic and Discrete Mathematical Methods for Modern Biology (Academic Press, 2015). She has chaired the Advisory Board of the National Institute for Mathematical and Biological Synthesis (NIMBioS), led the Committee on Special Interest Groups of the Mathematical Association of America, and served for over a decade as the founding Editor-in-Chief of Frontiers in Systems Biology. Matthew Macauley is an Associate Professor at Clemson University in South Carolina. Since finishing his PhD in Mathematics from the University of California, Santa Barbara, he has been a research visitor at the Biocomplexity Institute of Virginia Tech, the Institute for Systems Biology in Seattle, and the University of Southern Denmark. He has also taught internationally in both South Africa and Taiwan. Macauley has supervised two PhD and five MS students, as well as a number of undergraduate research students. With Raina Robeva, he has co-organized three faculty development workshops on teaching discrete and algebraic methods in mathematical biology to undergraduates.

• 1. Multi-scale graph-theoretic modeling of bimolecular structures2. DNA nanostructures: Mathematical design and problem encoding3. Graphs associated with DNA rearrangements and their polynomials4. Regulation of gene expression by operons: Boolean, logical, and local models5. Modeling the stochastic nature of gene regulation: probabilistic Boolean networks6. Inferring interactions in molecular networks via primary decompositions of monomial ideals7. Analysis of combinatorial neural codes: an algebraic approach8. Predicting neural network dynamics: insights from graph theory9. Multistationarity in biochemical networks: Results, analysis, and examples10. Optimization problems in phylogenetics: Polytopes, programming and interpretation11. Clustering via self-organizing maps on biology and medicine12. Toward revealing protein function: Identifying biologically relevant clusters with graph spectral methods