6th q-bio Summer School Themes

The school will comprise overlapping series of lectures and several major themes (e.g., stochastic gene regulation). A prospective student should have research interests in one of the following areas.

QB1, Stochastic Gene Regulation (Santa Fe, NM)

In this theme, we will explore stochasticity and cell-to-cell variability in the measurement and modeling of biochemical systems. In particular, we will concentrate on the effects that small numbers of important molecules (i.e. genes, RNA, and protein) have on the dynamics of living cells. We will review experimental manifestations of stochastic effects in molecular biology, as can be measured using single-cell and single-molecule techniques. We will discuss the most recent analytical and numerical methods that are used to model these systems and show how these methods can improve interpretation of experimental data. We will study how different cellular mechanisms control and/or exploit randomness in order to survive in uncertain environments. Similarly, we will explore how single-cell measurements of cell-to-cell variability can reveal more information about underlying cellular mechanisms. This section of the summer school will include a number of instructor-suggested group projects, in which students will apply various numerical techniques to formulate, identify and solve stochastic models for gene regulatory systems. Students will then apply these tools to model experimental flow cytometry or other single-cell data. Access and knowledge of Matlab will be helpful, but is not strictly necessary. This section of the summer school is organized by Brian Munsky. Please address all questions about this section of the summer school to its organizer.

QB2, Cell Signaling (Santa Fe, NM)

This series of lectures, which is offered at the Santa Fe campus, will be focused on modeling cell signaling. We will begin with an overview of the inherent features of cell signaling systems, including the modularity of proteins, the importance of post-translational modifications (e.g., multisite phosphorylation), and an overview of cell signaling motifs, such as kinetic proofreading, serial engagement, and regulated recruitment (co-localization of enzymes and substrates). We will then discuss how these features complicate efforts to develop predictive mechanistic models of cell signaling systems and possible solutions, in particular the rule-based modeling approach. We will cover methods for simulating a model, visualizing and annotating a model, and fitting procedures. We will make extensive use of software tools that are compatible with the BioNetGen language (BNGL) or the closely related Kappa language (http://kappalanguage.org/). An example of such a tool is BioNetGen (http://bionetgen.org). For additional information, contact Bill Hlavacek.

QB3, Biomolecular Simulations (Santa Fe, NM)

Description of Theme As system biology thrives to excel in providing cellular level behavior of complex biological systems, it has become imperative to integrate the molecular level events for better understanding at the system level. The objective of this theme is to provide training on computational methodologies to extract molecular level events at different resolutions. In addition we intend to provide a brief review on recent theoretical and computational methods and state-of the-art computing architectures. Finally, we will use examples from our own research to show that the real strength of these computational methodologies can only be materialized when combined with experimental studies. This section of the summer school is organized by "Gnana" S Gnanakaran. Please address all questions about this section of the summer school to its organizer.

QB4, Viral Dynamics (Santa Fe, NM)

This series of lectures focus on viral and immune systems dynamics at the cellular population level, that is the modeling of interactions of immune cells and viruses within an individual. There will be a basic introduction to the biology of these systems, followed by lectures on modeling specific issues/processes/immune systems. We will cover both modeling of the healthy immune system, and viral infections such as human immunodeficiency (HIV), hepatitis (B and C), and influenza. Particular attention will be given to the evolutionary processes shaping these viruses in vivo, including the topic of phylogenetics. The approach to all these subjects will include discussions of the mathematical framework, the types of available data and how to link models and data to generate new hypotheses, estimate parameters and gain the most biological insight from restricted datasets. Group projects will include journal club presentations, small simulations projects, and there will be scope for research-type projects if enough student interest is manifested. This section of the summer school is organized by Ruy Ribeiro. Please address all questions about this section of the summer school to its organizer.

QB5, Synthetic Biology (San Diego, CA)

In this theme, students will learn how to use computational modeling tools for design and evaluation of synthetic gene networks. We will review basic modeling approaches including Boolean networks, mass action kinetics, stochastic simulation algorithms and provide hands-on training sessions on using corresponding software tools. Then we will apply these tools to the design and analysis of basic elements of synthetic circuits such as positive and feedback loops, oscillators, toggle switches, logical gates, quorum-sensing circuits, enzymatic machinery. Issues of stochasticity, cell-to-cell variability, robustness and parameter sensitivity will be addressed in depth in regards to evaluation of synthetic circuit performance.

QB6, Computational Neuroscience (San Diego, CA)

In this track, students will learn how to use computational modeling for analysis of biological neural networks. We will introduce basic models including biophysical conductance-based models, simplified rate equations, fast spiking models, synaptic transmission and plasticity and memory models. We will also cover information theory and spike train analysis and provide hands-on training sessions on popular software tools used in computational neuroscience. We will apply these tools to the analysis and simulations of specific neural circuits, synaptic dynamics, learning, and control of neural systems. The relevant topics of bifurcation theory, robustness, sensitivity analysis and information theory will be reviewed in regards to the dynamics of neural circuits. In addition, participants will have the opportunity to implement models of cortical neural dynamics in programmable and reconfigurable analog neuromorphic hardware. The course includes an introduction to neuromorphic engineering from a dynamical systems perspective, and live and interactive demonstrations.

Theme lectures will take place on weekdays from July 23-27 and July 30-August 3. All students will participate in the Student Symposium (August 6 and 7, 2012, Santa Fe, NM).

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