Adilson Motter - US grants

This project focuses on modeling synchronization and coherent behavior in realistic networks with complex structure. As an emerging field, the study of synchronization in complex networks has so far not seen sufficiently strong connections between theory and the actual behavior of real systems. The first objective of the proposed research is the empirical analysis of collective dynamics in complex systems in the technological, social, and biological domains. This will be achieved by developing methods for data analysis of the dynamics of three types of systems: power grids, human communities, and biochemical reaction systems. The second objective is to extend the current theoretical framework for analyzing the synchronized and coherent dynamics in such systems. The final objective is to combine the empirical observations and the theoretical development in the modeling of these complex systems as networks of simple dynamical units. This approach will be used to investigate how the collective dynamics is influenced by the underlying network structure and the properties of the individual dynamical units.

The study of synchronization in power grids is important to assess and reduce the influence of voltage phenomena in triggering large blackouts. The study of coherent dynamics in human communities is relevant to help build more efficient strategies for the allocation of services and resources and for the assessment and management of risks. The study of synchronization in biochemical reaction systems is important to advance our understanding of large biochemical networks in living organisms. The planned research activities are interdisciplinary and will involve the training of undergraduate students, including students from under-represented minorities, and one graduate student. Outreach activities are also planned in the form of individual research advising and public lectures at a local high school, allowing our research results to be presented to a large and diverse public.

The proposed research exploits an idea of John Tukey that was never published. Called scagnostics (a Tukey neologism for "scatterplot diagnostics"), the original idea leads to a more general characterization of high-dimensional point sets using visually-based geometric and graph-theoretic measures. These measures comprise a canonical set of 9 features of pointwise data typically observed by experienced statisticians. Computing these measures on all possible 2D axis-parallel orthogonal projections in a p-dimensional space results in a p(p- 1)/2 × 9 matrix of measures. The objective of the proposed research is to generalize scagnostics to a new approach called Visual-Model-Based Transformations (VMBT). Visually-based transforms, together with multivariate analyses, can reveal visual patterns that are of interest to analysts. When interesting patterns are discovered in transform-space, one can invert the map and infer patterns in the raw data space.

Scagnostics exploits an important aspect of visualizations. A visualization can be thought of as a visual representation of an underlying mathematical model. Even simple charts of raw data rest on a model that helps (one hopes) to reveal some interesting aspect of the data. We often take these models for granted when we view familiar graphs. However, understanding mathematical models underlying visualizations can help us to devise more effective models for revealing structure in more complex datasets. Visual-Model-Based Transformations are a class of models that may prove especially effective for this purpose. Such models are motivated by visual structures perceived and processed by analysts. Given this visual motivation behind their design, visual models are likely to reveal features of data that are quite different from those appearing in common statistical and scientific graphics.

This conference support award is for the Annual International Conference on Chaos and Nonlinear Dynamics "Dynamics Days" to be held in Evanston, Illinois, on January 4-7, 2010. The conference will bring together a diverse group of experts in complementary areas of nonlinear phenomena, including chaos, complex networks, granular materials, time series analysis, non-equilibrium statistical physics, pattern formation, self-organization, and fluid dynamics. The conference participants will be comprised of experts in theory and applications as well as students and postdoctoral researchers. There will be substantial emphasis on topics that cut across disciplinary boundaries, such as dynamical processes in complex systems.

Dynamics Days is an annual conference organized with the specific purpose of providing an interface for researchers from diverse scientific disciplines but with common interests in chaos and nonlinear dynamics. This meeting has become internationally known as a very effective venue for researchers to share their most recent results in understanding, modeling, and controlling nonlinear dynamical systems.
The proposed conference will follow this tradition and create an interdisciplinary environment that will facilitate interactions between researchers from related but different fields. This is expected to generate new insights and lead to potentially transformative interdisciplinary research. The inclusion of students and early-career researchers, including those from underrepresented groups, is a central part of the conference. This will promote the transfer of expertise to the next generation of engineers, physicists, and mathematicians.

This project focusses on discovering and modeling fundamental properties of inertial particle transport in open (large-scale) fluid flows, using a novel approach that combines advanced methods from nonlinear dynamics and chaos theory with Lagrangian fluid dynamics. Large-scale inertial phenomena are of significant interest to a wide range of physical processes involving the advection of small rigid particles, whose trajectories may deviate from the trajectories of the fluid elements due to particle finite-size and density. The research will: 1) characterize the impact of inertial effects on single-particle and ensemble dynamics, including the possible formation of attractors and voids; 2) determine the particle and fluid parameters that can lead to the PI's recently discovered fluid-dynamic trapping and clustering of heavy inertial particles in two-dimensional open fluid flows; 3) explore applications of these results to situations involving segregation, mixing, and reactive processes with inertial particles. The expected results include the systematic characterization of inertial phenomena and would be transformative both to the basic theory and the many applications. The proposed research will help advance the understanding of mechanisms underlying natural processes such as rain formation and planet formation, and of applications ranging from chemical to environmental engineering. The planned research activities will involve a graduate student and undergraduate students, including students from underrepresented groups. The project is also expected to impact the PI's course on nonlinear dynamics and chaos and his outreach activities at a local public high school.

The investigator will develop and apply mathematical and computational methods to predict compensatory, rescue perturbations that can mitigate the propagation of failures in perturbed complex networks. The research is motivated by the increasing availability of information about the component parts of large biological and physical networks, which is creating an unprecedented opportunity to address pressing problems determined by large-scale network dynamics. The project will use nonlinear dynamics and complex network techniques and will be implemented through five complementary components of broad significance: the development of (1) deterministic and (2) stochastic methods to identify rescues; the application of these methods to (3) mitigate extinction cascades in perturbed food-web networks, (4) recover lost cellular function in defective metabolic networks, and (5) control cascading failures in power-grid networks. This research will lead to the identification of physically implementable compensatory perturbations, thereby enabling control of the network's large-scale dynamics. An overarching objective of the project is to integrate underlying principles of this research into the development of teaching and outreach innovations in three different frameworks: (i) summer internship activities for undergraduate students from underrepresented groups; (ii) computer-based interactive tools for undergraduate and graduate complex systems education; and (iii) on-line exhibits in partnership with Chicago's Museum of Science and Industry, which will further integrate the research and educational outcomes of this project.


The proposed mathematical development will create methods that can be used to rescue and control complex networks in a wide range of domains. This will allow the discovery and characterization of new phenomena that are likely to foster breakthroughs in various contexts. In particular, it will enable new ecosystems management approaches to halt the loss of biodiversity, yield new methods to recover lost cellular function, with implications for medical research, and lead to novel methods to mitigate cascading failures in electrical power grids. The planned activities are interdisciplinary and will provide a unique training ground for graduate and undergraduate students (including students from underrepresented groups) in a way that traditional disciplinary research programs cannot. The educational and outreach activities will help create infrastructure for complex systems education at Northwestern and will disseminate the research results and methodologies to a large and diverse audience.

This workshop support award is for the bi-annual meeting on complex networks "Network Frontier Workshop" to be held at Northwestern University, Evanston, Illinois, December 4-6 2013. The meeting will bring together a diverse group of experts in complementary areas of network science, dynamical systems, and complex systems, with substantial emphasis given to topics that cut across disciplinary boundaries. Participants will include experts both in theory and in applications as well as students and postdoctoral researchers. They will, in addition, participate in discussions about future directions that are likely to lead to transformative research. The program will include tutorials, presentations by young researchers, and discussions about career opportunities, in addition to research talks by leading experts in the field.

In this workshop, presenters will report recent results in the area of network science and related applications. Participants will become aware of the latest results in their respective subfields, and will also be able to discuss with other experts in an interdisciplinary environment. This is expected to generate new insights and stimulate new interdisciplinary collaborations. In addition, the workshop will involve activities jointly organized with the Northwestern SIAM Student Chapter, which will include tutorials by experts, presentations by students and postdoctoral researchers, and discussions about career opportunities. The participation of early-career researchers will also help promote the transfer of expertise to the next generation of engineers, physicists, and mathematicians.

DESCRIPTION (provided by applicant): This collaborative project will develop and integrate complementary mathematical and experimental microbiology approaches to identify gene targets for the design of antibiotic drug combinations that can select against resistance. Diseases caused by microbial infection are the second leading cause of death worldwide. A major challenge in the treatment of such infections is the development of new classes of antibiotics. Inevitably, the introduction of a new antibiotic into the clinic is accompanied by the emergence of resistant microbes. There are, therefore, two major issues to consider in the development of new antibiotic drugs: 1) the identification of novel targets and 2) the discovery of approaches that will limit the emergence of resistance. The major goal of this project is to develop and apply an innovative methodology that can address these two problems simultaneously. The proposed research builds on the recent discovery that the combination of two antagonistically interacting antibiotics (where one drug suppresses the effect of the other) can select against antibiotic resistance. The applicability of this concept has been limited by the fact that most existing antibiotics do not have a known antagonistic partner. The specific aims are thus to develop approaches that will allow us a) to identify gene targets for the design of antagonistic drugs for existing antibiotics and b) to identify paired gene targets that would permi the development of novel antagonistically-interacting drug pairs. This will be achieved by systematically identifying synthetic rescues, which are genetic interactions whereby the negative phenotypic effect of a gene deletion can be partially compensated by the targeted inactivation of other genes. Such rescues are the genetic counterpart of antagonistically interacting drugs and, as such, present potential targets for the development of novel, antagonistic drug combination therapies that can select against drug resistance. To overcome the combinatorial explosion in the number of possible gene-gene combinations in a bacterium, the discovery of such desired drug targets will be guided by new predictive modeling integrated with directed experimental validation. The project will be focused on Escherichia coli K12, which is a robust experimental system that is amenable to mathematical modeling.

This award will support the Multidisciplinary Complex Systems Research Workshop to be held at the National Science Foundation in Arlington, Virginia, September 12-14, 2016. The workshop will bring together a diverse group of experts in complementary areas of complex systems and will be preceded by a series of weekly webinars. The overarching goal of the activity is to address scientific issues that are relevant to the scientific community and bring to surface possible areas of opportunity for multidisciplinary research in the study of complex systems. The specific goals of the workshop include: 1) identifying the most substantive research questions that can be addressed by fundamental complex systems research; 2) recognizing community needs, knowledge gaps, and barriers to research progress in this area; 3) identifying future directions that cut across disciplinary boundaries and that are likely to lead to transformative multidisciplinary research in complex systems. The outcomes of the workshop will include the preparation of a report to inform the scientific community at large of the current status and challenges as well as future opportunities in multidisciplinary complex systems research as perceived by the participants of the workshop.

The workshop is motivated by the observation that many processes in natural, engineered, and social contexts exhibit emergent collective behavior and are thus governed by complex systems. Because challenges in understanding, predicting, designing, and controlling complex systems are often common to many domains, a central objective of the workshop is to facilitate the exchange of ideas across different fields and avoid disciplinary boundaries typical of many traditional scientific meetings. The workshop participants will include experts both in theory and in applications as well as a selection of postdoctoral researchers and graduate students from various domains. Because of the cross-disciplinary nature of the workshop, the participants themselves will become aware of the latest developments in fields related to but different from their own. This environment will foster discussions on the state of the art, potential issues, and most promising directions in multidisciplinary complex systems research. The inclusion of early-career researchers will help to promote the transfer of this expertise to the next generation of engineers, mathematicians, and scientists.

A key question in biology is how genetically identical cells achieve varied appearances and behaviors. These distinct cell states are realized by variations in gene expression within certain cells in the population; different genes are turned “on” or “off” in these cells. These variations in gene expression can lead to different phenotypes within a population of genetically identical cells. For example, variations in gene expression can lead some cells in a population of genetically identical bacteria to become antibiotic tolerant while other cells in the population remain suspectable to antibiotics. This project will address how variations in gene expression lead to important phenotypic changes in bacteria. To complement the research, an interactive series of lessons on mathematics in biology will be developed for high school students. These lessons will be distributed through a series of teacher workshops.<br/><br/>Irreversibility, hysteresis, and multistability in cell state have been quantitatively studied in a handful of specific bacterial systems — B. subtilis sporulation, the lac repressor, and the lysis-lysogeny switch are now classic examples. Here, the investigators seek to expand the understanding of these concepts to the genomic scale: the investigators will examine the time scales of reversibility, and the prevalence of irreversibility, following transient repression of all genes with known function in E. coli. To accomplish this, the investigators will develop a new reagent for light-inducible transient gene repression called LIT-CRISPRi. They will use a combination of experimental data and theory to establish expectations for the time scale of transcriptional, translational, and growth rate recovery following transient gene repression in the fully reversible case (in the absence of hysteresis) and characterize behavior for one well-studied irreversible case (the lac operon). They will then use these tools to characterize E. coli’s growth rate dynamics before, during, and after transient gene repression for a genome scale library of LIT-CRISPRi knockdowns under different environmental conditions. From these data, the investigators will examine the distribution of growth rate recovery times, identify cases of irreversibility or exceptionally long timescale recovery (quasi-irreversibility), and further validate these phenotypes through secondary experiments. Finally, they will use RNAtag-Seq to perform time-resolved transcriptomics before, during, and after transient gene repression for several genes exhibiting (quasi-)irreversible dynamics identified by our screen. Taken together, the work will establish fundamental expectations for the time scales of cellular adaptation and irreversibility following gene repression.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.