1. OEB 192 – 09.11.18 Phenotypic diversity & epigenetics

4. (Verstrepen et al., 2005)

5. (Elowitz et al., 2002)

6. (Ozbudak et al., 2004)

7. (Balaban et al., 2004)

8. (Stewart et al., 2005)

10. Monday (11/23): Diversification & coevolution

11. Wednesday-Friday (11/18-11/20) - Origins Forum Title: "AGE of Innovation: a story about how life learned to breathe and thrive as told by hundreds of microbial genomes" Speaker: Eric Alm (MIT) Date: Wednesday, November 18 th Time: 4:00 – 5:00 PM Location: Biological Laboratories Lecture Hall, 16 Divinity Ave., Rm. 1068 Contact: Carol Knell (cknell@cfa.harvard.edu)cknell@cfa.harvard.edu - MIT Microbiology Seminar Series Title: “Selective Pressures on Enzymes and Adaptation of Metabolic Systems” Speaker: Chris Marx (Harvard University) Date: Thursday, November 19 th Time: 11:30AM – 12:30PM Location: McGovern Auditorium, Whitehead Institute - OEB Weekly Seminar Series Title: “Phalanx or Traitors? Role of the gut microbial community in the health of lepidopteran insects” Speaker: Jo Handelsman (University of Wisconsin–Madison) Date: Thursday, November 19 th Time: 4:00 – 4:30 PM Location: Biological Laboratories Main Lecture Hall with post-seminar reception to follow in room 1058 (16 Divinity Ave., Cambridge) Host: Cavanaugh Lab Contact: Katharine Parodi (kparodi@oeb.harvard.edu)kparodi@oeb.harvard.edu - Dudley Herschbach Teacher Scientist/Lecture Title: "Scientific Teaching: What Happens when Faculty act like Scientists?" Speaker: Jo Handelsman (University of Wisconsin–Madison) Date: Friday, November 20 th Time: 2:00 – 2:30 PM Location: Sever Hall, Room 113 Contact: Katharine Parodi (kparodi@oeb.harvard.edu)kparodi@oeb.harvard.edu

12. Friday, 11/20 From genes to physiology via metabolism 20 November 2009, 12:00 pm, Warren Alpert 563 (HMS) Frederik Nijhout Frederik Nijhout Department of Biology Duke University Michael Reed Michael Reed Department of Mathematics Duke University Abstract Metabolic networks are typically analyzed under the assumption that they operate at steady-state. System properties such as control coefficients and robustness are studied by small perturbations of the steady-state, and the evolution of such networks is assumed to be driven by maximization or optimization of steady-state fluxes. Nothing could be farther from reality. In life, metabolic systems are subject to continuous and large fluctuations in input and demand, and the expression levels of many genes vary dramatically during the day. We will discuss our studies on the dynamics of metabolic networks, concentrating on (1) folate and glutathione metabolism, and (2) dopamine and serotonin metabolism. Our studies show that stability and robustness in metabolic networks is due to dynamically active homeostatic mechanisms, rather than passive establishment of a steady-state. Similar non-steady-state processes undoubtedly operate in genetic networks and signaling networks as well. For more details and papers see metabolism.math.duke.edu/metabolism.math.duke.edu/