Algebraic and Combinatorial Computational Biology

<p>1. Multi-scale graph-theoretic modeling of bimolecular structures<br>2. DNA nanostructures: Mathematical design and problem encoding<br>3. Graphs associated with DNA rearrangements and their polynomials<br>4. Regulation of gene expression by operons: Boolean, logical, and local models<br>5. Modeling the stochastic nature of gene regulation: probabilistic Boolean networks<br>6. Inferring interactions in molecular networks via primary decompositions of monomial ideals<br>7. Analysis of combinatorial neural codes: an algebraic approach<br>8. Predicting neural network dynamics: insights from graph theory<br>9. Multistationarity in biochemical networks: Results, analysis, and examples<br>10. Optimization problems in phylogenetics: Polytopes, programming and interpretation<br>11. Clustering via self-organizing maps on biology and medicine<br>12. Toward revealing protein function: Identifying biologically relevant clusters with graph spectral methods</p>