Yang Kuang - US grants

The investigator undertakes studies aimed at gaining an understanding of the global qualitative behavior of solutions of some ecological models with delays or diffusions. These fall in three parts: (1) finite-dimensional systems of ordinary differential equations, (2) delay differential equations, and (3) diffusive systems with time delays. The principal themes of the research are the fundamental problems of finding various criteria for the uniform persistence of these considered systems, the global stability of steady states, and the existence of periodic solutions and spatial patterns. In particular, the investigator will study some mathematical models of populations dispersing among patches in heterogeneous environments, where various kind of interactions will be considered. For systems with more than two populations, one of the main objectives is to find concrete conditions under which all populations will coexist in the long term. For two-species interaction models, global stability of steady states, existence of periodic solutions or spatial patterns will be main concerns. Time delays and space variations constitute integral components of most ecological, biological, physiological, chemical, physical, economic and atmospheric processes. The planet as a habitat of mankind and other species has become too small to support an extravagant exploitation of its resources. The damages are inevitable and usually occur with time delays in heterogeneous environments; no experiments are possible to fully simulate these effects. In order to better understand and control such processes, it is thus necessary and important to study them mathematically. Unfortunately, current mathematical techniques are far from adequate to handle these numerous real problems. The proposed research will lead to an improved understanding of the dynamical interplay of the effects of time delays and diffusions. In particular, the final results can be useful to a wide spectrum of people like ecologists, engineers, system scientists and others who plan for a better management of the planet and life.

9306239 Kuang The investigator studies the global qualitative behavior of solutions of some ecological models with delays or diffusions. The principal themes of this work are the fundamental problems of finding various criteria for the uniform persistence of these considered systems, the global stability of steady states, the existence of periodic solutions and spatial patterns, and the existence of chaotic behaviors. These topics indeed cover most aspects of the so-called global qualitative analysis of nonlinear systems. In particular, the investigator studies some mathematical models of populations dispersing among patches in heterogeneous environments, where various kind of interactions are considered. In addition to performing the traditional local stability or bifurcation analysis, he considers global stability, bifurcation, and chaos aspects of the nonlinear systems. Time delays and space variations constitute integral components of most ecological, biological, physiological, chemical, physical, economic and atmospheric processes. Almost all these real-life processes are nonlinear in nature. They are normally too complicated to simulate in a lab, or too difficult to understand from experimental work alone. In order to better manage or control such processes, it is necessary to study them mathematically. Most of the previous approaches to these applied mathematical problems have been local (pretending the system behaves in a small region as if it were linear rather than nonlinear) and thus do not paint the whole picture of the real systems. This project tries to gain a full view of the real picture by focusing on the nonlinear effects of the dynamics of the considered systems. This work offers a better understanding of the dynamic interplay of the effects of time delays and diffusions. In particular, the final results can be useful to ecologists, engineers, and system scientists. ***

Kuang
0077790
All organisms are composed of multiple chemical elements
such as carbon, nitrogen, and phosphorus. Recent research in the
area known as ecological stoichiometry has highlighted the
ecological importance of the relative abundance of chemical
constituents, known to vary considerably among species and across
trophic levels. However, most theoeretical studies in ecology
have until very recently ignored the sources and consequences of
this chemical heterogeneity. The investigator and his colleagues
undertake theoretical investigations of ecological stoichiometry.
They develop a relatively new theoretical framework for
ecological dynamics that explicitly incorporates stoichiometric
constraints. This base model involves a stoichiometric
counterpart of the familiar Rosenzweig-MacArthur equations in
which the effective carrying capacity of the resource species and
the transfer efficiency of the consumer species are constrained
by stoichiometric principles. Introduction of stoichiometric
considerations in these equations (here, akin to "food quality")
allows for a rich array of ecologically realistic dynamics,
including deterministic extinction of the consumer species when
resources are abundant but of poor quality. They expand this
model in five different directions, to explore ecological
realities (i.e., complications) whose consideration has proved
illuminating in other, non-stoichiometric settings. Specifically,
they analyze the dynamics of 1) a multi-nutrient model; 2)
trophically complex models in which multiple consumer species
share a resource; 3) time delays in nutrient recycling that are a
realistic component of terrestrial ecosystems; 4) two patch
models featuring habitat heterogeneity and dispersal of the
consumer; and 5) age structured models in which juvenile and
adult consumers differ in their nutrient requirements. The
project aims to provide an analytically rigorous foundation for
burgeoning empirical research into ecological stoichiometry.
All living things, including humans, are constructed of
approximately the same set of basic building blocks, chemical
elements such as carbon (C), nitrogen (N), phosphorus (P), and
several dozen more in smaller amounts. However, different
organisms contain different proportions of these key elements in
their biomass and thus must extract these elements from their
environment to differing degrees. In many situations, the
environment does not provide these key nutrient elements in the
abundance and proportions that are optimal for organism growth
and reproduction. Thus, the chemical environment of life may set
limits on the success of organisms in various situations. In this
project the investigators use mathematical models to simulate the
flow of multiple chemical elements in natural food webs to better
understand how the requirements of living things for multiple
chemical elements establish key feedbacks between the living and
non-living world. This work is important for two reasons. First,
it may provide a better fundamental understanding of how chemical
elements move through food webs. Second, improved fundamental
knowledge of how nutrients move in the environment and how to
simulate those movements with mathematical tools may help predict
and manage natural and human-dominated ecosystems, including
those affected by nutrient inputs from human activities (e.g. N
and P inputs from fertilizer, sewage) or by global change (e.g.
effects of increased atmospheric carbon dioxide on C and nutrient
flow in the environment).

Abstract

Awards: DMS 0342388, 0342239, 0342325
Principal Investigators: Yang Kuang, Val Smith, Marilyn S. Smith

This multi-campus team is studying processes within a single
biological host that can be described by models inspired by ecological
stoichiometry, the study of the balance of energy and multiple
chemical resources (usually elements) in ecological
interactions. These concepts have been broadened by their extension to
biological stoichiometry, which has proven to be an important new lens
through which we can view and understand complex biological
interactions. Within this general theory, the cycling and utilization
of energy and multiple nutrients by organisms and their constituent
cells occupies a central position. With its emphasis on the flow of
elemental matter, such as carbon, nitrogen, and phosphorus,
stoichiometric theory covers multiple biological scales. It also
allows, via rigid physical and chemical constraints, the construction
of robust mechanistic and predictive models. Originally formulated and
verified in the fields of limnology and plant ecology, biological
stoichiometry has recently been applied at physiological scales to
such diverse areas as organism development and tumor growth. In this
proposal we aim to synthesize and apply theoretical and empirical
approaches to biological stoichiometry within the grand framework of
internal disease. Recent headline-grabbing findings that connect
nutritional factors to disease dynamics indicate there is an
increasing need for stoichiometry-based mathematical models of
internal disease that track the effects of potentially limiting
resources. The proposed work weaves together threads of theoretical
and experimental research. Our primary aim is the construction of
predictive and verifiable theoretical models which can begin to
explicitly deal with the effects of stoichiometric interactions in
within-host disease dynamics. Such models will be built in a modular
fashion, starting with simple deterministic models, and then
progressively adding stochasticity, spatial heterogeneity, and
genetics. At each step the models will be challenged, calibrated, and
tested by in vitro laboratory experiments.

The proposed work will have a broad impact in both science research
and education, and eventually in internal disease management and
treatment. Regarding the former, our research team is truly
interdisciplinary, with group members in mathematics, theoretical
physics, ecology, and biomedicine. Our collaborative efforts will
provide undergraduate and graduate students and junior scientists of
diverse ethnic/racial backgrounds with first-hand educational
experience in cross-disciplinary communication and exploration. The
current proposal is a step towards new ways to understand disease,
aiming to develop robust and experimentally calibrated mathematical
theories of disease-host interactions that can be applied to a wide
variety of diseases. We firmly believe that such theories have a
central role to play in present and future research. These grants for
proposals submitted as a collaborative proposal from three
institutions are made under the Joint DMS/NIGMS Initiative to Support
Research Grants in the Area of Mathematical Biology. This is a joint
competition sponsored by the Division of Mathematical Sciences and the
Directorate for Biological Sciences at the National Science Foundation
and the National Institute of General Medical Sciences (NIGMS) at the
National Institutes of Health.

This five-year project, entitled "Developing a Professional Learning Community Model for Secondary Precalculus Teachers: A Model for Teacher Professional Growth," will produce a model for a Professional Learning Community (PLC) for pre-calculus teachers in secondary schools. It will generate research knowledge from cycles of (1) defining, (2) studying and (3) refining the model and its components. The project leadership team will then be able to describe the support structure, group processes and tools needed to assist secondary pre-calculus teachers in providing high quality instruction for their students.

PLC tools will be developed and refined to facilitate Teachers' "reflection-on-students'" thinking and reasoning relative to the major concepts of pre-calculus mathematics. The activities of the PLCs will also support teachers' continued conceptual and mathematical development, while promoting reflections on the effectiveness of their classroom practices.

The leadership team expects that the teachers' rich reservoir of new knowledge and understandings will be observable in the ways in which they orchestrate learning experiences for their students. They anticipate qualitative improvements in their classroom practices (perceivable in their questions and questioning patterns, the design and substance of their tasks, the conceptual focus of their exams), resulting in improved learning in their students. Implementation of this model will produce a set of research-developed tools to assist individual schools in devising and implementing a plan to support secondary teacher professional growth.

An interdisciplinary team of investigators carry out an
undergraduate training initiative at Arizona State University.
The training plan intimately combines new cross-disciplinary
courses and summer research programs. The former are constructed
to allow maximal participation among undergraduate cadres, and
facilitate life science majors to achieve a minor in mathematics,
and, likewise, mathematics majors to enrich their education with
a minor in bioscience. The summer research program is a
competitive enterprise involving at least eight ASU faculty
members from life sciences, mathematics, and biophysics.
Research projects span modeling of ecological and evolutionary
processes through the new lens of stoichiometric constraints,
bio-economics, chemostat theory, and modeling of visual
perception.

This project has potential to make broad impact in both
local and global education environs. Regarding the former, the
ASU UBM team is truly interdisciplinary, with members in
mathematics, biology and biophysics, exceptionally well suited
for interdisciplinary training for undergraduates in biological
and mathematical sciences. Its collaborative efforts can provide
undergraduate and graduate students of diverse ethnic/racial
backgrounds with first-hand educational experience in
cross-disciplinary communication and exploration. As for global
impact, the proposed holistic approach (involving mathematical
biology courses at various levels and summer research projects)
in mathematical biology training can vertically integrate all the
components in the ASU education system. It is therefore expected
that this proposed program may yield many invaluable lessons to
serve mathematical bioscience education and research nationwide,
enriching the experience for the next generation of students in
this integrative and interdisciplinary scientific endeavor.

The three-year Program Enhancing the Mathematical Sciences Workforce in 21st Century Mentoring Through Critical Transition Points (MCTP) at Arizona State University (ASU) will establish a learning through research community in the mathematical sciences that relies on mentorship, academic support and summer research opportunities for at least 25 undergraduate students each year. The Mathematical and Theoretical Biology Institute (MTBI)- devoted to the training of undergraduate and graduate students in the application of mathematics will: (1) recruit and select summer REU students; (2) guarantee sequential research summer opportunities for undergraduates; (3) keep track of their academic status after leaving the program for three years; and (4) prepare the students for graduate school and/or future employment.

The program is part of a systemic effort that will insure the successful transition of selected students from community college and colleges will enroll in a graduate graduate program in the mathematical sciences. The MTBI long-term overarching goal is to build a large community of researchers from which additional Ph.D.'s in the mathematical sciences primarily from underrepresented groups will emerge. It is anticipated that this project, like our previous REU (MTBI) projects, will succeed in increasing the enrollment and the graduation of students from groups that have traditionally been underrepresented in the mathematical sciences or in fields that demand strong mathematical training. For example, MTBI has served 220 undergraduate students over nine years-with many participating in two or more sequential summer research experiences selecting between 23 and 36 undergraduate participants each summer. The success of MTBI's programs is evident from the number of its alumni who continue on to graduate school. Specifically, the total percentage of underrepresented minority alumni of MTBI in graduate school is 62.5% (87 out of 139); the percentage pursuing Ph.D.'s is 34.5% (48 out of 139); the percentage of women in graduate school is 64% (64 out of 100); the percentage of women pursuing Ph.D.'s is 29% (29 out of 100). Participation in MTBI provided the research experience, mentorship and support needed to successfully continue their studies in mathematics. The proposed program will establish a model for education through research in a collaborative setting that focuses on actions at critical transition points from college to the Ph.D. level. The goal is that this model will instigate systemic and large-scale educational and mentorship changes at ASU and other emergent urban universities.

Organisms are composed of chemical elements such as carbon, hydrogen, oxygen, nitrogen, and phosphorus. Research in the area known as ecological stoichiometry (ES) has highlighted the ecological importance of the relative abundance of chemical constituents, known to vary considerably among species and across trophic levels. ES deals with how the balance of energy and elements affect and are affected by organisms and their interactions in ecosystems. It has proven to be an important new lens through which to view and understand ecological interactions and has gained momentum by explicitly linking the elemental physiology of organisms to their food web interactions and ecosystem function. Thus, ES theory covers multiple biological scales and allows, via rigid physical and chemical constraints, the construction of robust mechanistic and predictive mathematical models. While biology has a research tradition that is empirical in nature and often only weakly connected to formal quantitative analyses, mathematical and theoretical biology on the other hand has had a research agenda that has often been somewhat distanced from mainstream empirical biology. There is not enough effort and attention on marrying empirical results with theoretical findings. The investigators will extend and generalize existing well-received stoichiometry-based mathematical models to encompass a broader range of ecological situations, including cell quota dynamics, consumer age- or size-structures, variable consumer stoichiometry, and delayed nutrient cycling. Once such a generalized theoretical framework is established, the investigators will construct and evaluate models inspired by recent empirical discoveries in ES, including one considering the effects on consumer dynamics of not only insufficient food nutrient content but also of excess food nutrient content, and another considering the effects of stoichiometric dietary mixing. Finally, the investigators will challenge these parameterized stoichiometric models against observed population growth dynamics qualitatively and quantitatively. In doing so, the investigators hope to achieve a far-reaching synthesis between model and experiment in the form of new theoretical applications that may allow for direct and quantitative predictions of the effects of stoichiometric constraints on ecosystem processes. The models the investigators will investigate may motivate challenging but tractable problems in areas of qualitative and computational studies of nonlinear differential equations and delay differential equations.

This project will have a broad impact in both local and global environs. The biological findings of this project may have a number of practical applications to issues such as eutrophication, biofuel production, global change, and biodiversity. Its theoretical outcomes will provide a solid and user-friendly framework to build mathematical models that allow quantitative prediction of ecological interactions. Moreover, it will find many ready applications in cancer and other within host diseases dynamics and treatment modeling since one can view cancer cells and pathogens as invading species in a host ecosystem. The investigators' collaborative efforts will provide undergraduate and graduate students of diverse ethnic/racial backgrounds with first-hand educational experience in cross-disciplinary communication and exploration. Finally, the investigators are partnering with Arizona State University's School of Life Sciences award-winning Ask-A-Biologist program to develop articles and virtual experiments related to this project to enhance middle- and high school student learning of biological and mathematical concepts.

This project will develop a recruitment network for mathematically talented students in community colleges in Maricopa County, Arizona, to help facilitate their successful transitions to baccalaureate programs in the mathematical sciences at Arizona State University (ASU). This project, in addition to serving students in the Phoenix area, will serve as a model for universities elsewhere hoping to implement a successful transition program for community college students in the mathematical sciences. Summer enrichment programs will be offered at Scottsdale Community College that will introduce students to topics in set theory and proofs, mathematical finance and biology, and computer graphics. An 8-week summer research experience will be offered at ASU to qualified mathematical science majors, including alumni from the summer program at Scottsdale, to provide pre-professional experience to make them competitive for careers and selective graduate programs and associated fellowships in the mathematical sciences. In addition, ASU mathematics faculty will develop "project seminar" courses, to be offered during the academic year, on mathematical problems related to weather prediction and atmospheric dynamics; image processing and Fourier analysis; network dynamics and graph theory; and mathematical models of cancer (especially brain and prostate cancer). This award is designed to provide opportunities to undergraduate mathematics majors to work as part of a team on an interdisciplinary problem; read journal articles to gain some background on a new subject quickly; analyze open-ended problems using computer simulation as a discovery tool; and present a talk or poster on their work at an appropriate workshop or research conference.

Arizona State University has one of the largest undergraduate mathematics programs in the United States. This 5-year pilot project will engage approximately 38 mathematically talented students in the Maricopa County community colleges and 12 mathematics majors at ASU each year. It seeks to provide a national model for other partnerships between community colleges and 4-year institutions to increase the number of undergraduate students with advanced training in mathematics and scientific computation. Special efforts will be made to recruit students who are first-generation college students as well as students who are female and/or members of underrepresented groups in the mathematical sciences. All student participants will be U.S. citizens or permanent residents.

DMS-1518529
Kuang

The Ebola epidemic in West Africa continues to cause significant morbidity and mortality. The World Health Organization declared the Ebola epidemic in West Africa a Public Health Emergency of International Concern on 8 August 2014. As the epidemic continues to spread at an alarming rate in some areas of West Africa, there is an urgent need to develop, test, and calibrate novel mathematical models of Ebola transmission and control with the goal of generating real-time, science-based forecasts of the epidemic in West Africa in order to quantify the times, locations, type and intensity of interventions that would be required to achieve control. To this end, the investigators and their colleagues formulate and validate models that can be used to predict the number and location of new cases, in order to facilitate decision-making on the allocation of resources that will allow timely medical treatment and isolation of the sick and to implement effective and sensible travel controls. This project provides first-hand educational experience in cross-disciplinary communication and exploration and cutting-edge research opportunities for undergraduates and graduate students. It also provides professional development for graduate students. The investigators disseminate their findings to a diverse range of mathematicians, modelers, and public health and biomedical researchers.

The investigators divide the project efforts into three modeling tasks. At first, they formulate dynamical models of the evolving infection reproduction number, comparing how well a simple SI model and the logistic model fit past and current real Ebola epidemics data. In this initial task, instead of treating the whole population as susceptible, they treat the susceptible population size and the final epidemics size as parameters and allow the reported data to inform these parameter values. Subsequently, they present a novel delay differential equation based modeling framework that allows models to treat susceptible population size as a dynamical variable, which is highly correlated to current infectious population size. More specifically, they initialize the susceptible population size as zero instead of the current thinking that susceptible population size equals the total population size initially. This is simply due to the fact that individuals become susceptible to Ebola only if they had a direct and close contact with infectious Ebola patients. In the second half of this project, they formulate and validate partial differential equation-based models in order to estimate the Ebola spread speed and to predict the locations and numbers of new Ebola cases subject to various treatment options and travel control policies. The project is supported by the Division of Mathematical Sciences and the Division of Environmemtal Biology.

Human activities are altering the influx of nutrient supplies to Earth's ecosystems. A recent study reveals that nutrient supply dramatically changed the prevalence and interaction strength between two plant viruses, barley yellow dwarf virus and cereal yellow dwarf virus. Since viruses hijack host cell machinery to replicate which requires nitrogen and phosphorus to synthesis nucleic acids and proteins, given more amounts of nitrogen and phosphorus, one would expect to see higher numbers of virus replication. By studying and understanding the complex relationship between key nutrients and disease dynamics, we may help in planning and advising the future of agricultural practice. This project will also provide opportunities for undergraduates and graduate students in research and instructional environments; interdisciplinary training and professional development for graduate students; and broad dissemination of our results to a diverse range of mathematicians, modelers, ecologists and biomedical researchers. Our efforts will provide undergraduate and graduate students of diverse ethnic/racial backgrounds with first-hand educational experience in cross-disciplinary communication and exploration.

All cells are made of chemical elements. Ecological stoichiometry (ES), is the study of the balance of chemical elements in ecological interactions. ES and the theory of evolution have been found to be crucial lenses through which one can view and understand the dynamics of populations and communities of microorganisms. ES covers multiple biological scales, and it allows the construction of robust, mechanistic, and predictive mathematical models based on cell nutrient levels. Within this theory, the utilization of energy and multiple chemical elements (especially carbon, nitrogen, and phosphorus) between organisms and their environment occupies a central position. However, the ES framework has yet to be effectively integrated into the modeling of host-pathogen interactions. This project seeks to identify the relationships of some key biological mechanisms to the rich dynamics often observed in simulating host (plant)-pathogen models incorporating nutrient quality and quantity in host and pathogen populations. These relationships may provide novel insights for better plant disease control. Specifically, we will construct mathematical models of host-pathogen interactions that are based on empirical discoveries. The models that the research team will investigate are novel both mathematically and computationally, as they will motivate challenging problems in areas of qualitative and computational studies of nonlinear differential equations and delay differential equations.

While natural phenomena may often appear to be complex and hence difficult to predict, in between those seemingly chaotic events, there can be moments of strikingly beautiful patterns and forms. In certain sense, synthetic biology is about identifying and reproducing these patterns and mathematics is about describing and understanding the mechanisms behind their formations. Although spatial patterns are ubiquitous in living organisms, the task of identifying the underlying mechanisms can be daunting due to the overwhelming complexity of living cells and organisms. Indeed, the study of natural patterns dates back to many centuries in the past. In this proposal, the team proposes to combine gene circuit engineering and mathematical analysis to advance our understanding of reaction-diffusion (RD) based biological pattern formation. Specifically, there are three main objectives the team hopes to achieve in the proposed research: Aim 1, Experimentally and mathematically characterize RD based cellular pattern formation driven by rationally designed gene circuits. Aim 2, Investigate implications of nutrient limitation on pattern formation. Aim 3, Engineering and testing of pattern formation of interacting populations. Specifically, the team proposes to engineer a set of gene circuits to direct bacterial cells to form self-organized patterns without predefined spatial cues. The role of network topology, nonlinearity, gene expression stochasticity, and environmental signals in contributions to observed spatially structured patterns will be examined. To this end, this interdisciplinary team plans to mechanistically formulate a series of plausible RD models that accurately describe gene regulation, protein production, quorum sensing, and dispersion driven by synthetic circuits. Moreover, the team plans to develop appropriate experimental, computational, and mathematical tools based on the single-cell agarose pad platform that shall allow us to quantitatively and experimentally probe the fundamental mechanisms of spatial patterns formation across molecular, single-cell, and colony scales.

All organisms are made up of the same set of chemical elements such as carbon (C), nitrogen (N), and phosphorus (P), although there are differences in the proportions of these elements among species. Such diversity affects the roles organisms play in key ecosystem services such as carbon sequestration and nutrient cycling. However, scientists don't yet have a complete understanding of the biological rules that dictate the proportions of C, N, and P in living things. One hypothesis is that C:N:P proportions are a function of how fast an organism grows because, to grow fast, organisms must produce P-rich structures to drive rapid construction of cellular materials. While various data support this view, other studies do not and so researchers do not yet know when this "growth rate rule" holds and when it doesn't. This project will subject three species (a bacterium, an alga, and a crustacean) to a variety of environmental and evolutionary conditions to see when C:N:P proportions of each organism follow this "growth rate rule" and when they don't. The research team will also build mathematical models of these processes to predict what happens when organisms that do (or do not) follow the growth rate rule interact with each other. The proposed research will advance scientific understanding how food webs and ecosystems work and improve predictions of how they respond to perturbations, including increasing atmospheric carbon dioxide concentrations and inputs of nitrogen and phosphorus pollution from agriculture and sewage. Furthermore, to help develop a broadly trained scientific work force, the project will partner with local tribal communities to engage Native American undergraduate students in the research.

This project seeks to establish the conditions under which there is or is not a close coupling among growth rate, C:N:P ratios, and cellular allocation to P-rich ribosomes in three taxa: Pseudomonas putida (a heterotrophic bacterium), Chlamydomonas reinhardtii (a photosynthetic alga), and Daphnia pulicaria (a crustacean consumer). First, Pseudomonas, Chlamydomonas, and Daphnia will be grown under limitation by key non-substitutable resources (energy, N, P). Associations among growth, biomass, excretion and remineralization C:N:P stoichiometry, cellular RNA and protein contents, and metabolic rates will be quantified. These measurements will be used to develop mathematical models of these cellular processes. Next, the project will complete a series of evolution experiments, subjecting Pseudomonas, Chlamydomonas, and Daphnia to selection under limitation by different resources. The resulting descendants will be assessed as in the first component of the project. Then, the descendants will be used in ecological experiments to evaluate how evolutionary responses affect ecological processes. Finally, results from these experiments will be used to develop and test new mathematical models of ecological and evolutionary dynamics. The proposed work will produce several resources for use by the scientific community, including data on physiological and transcriptomic responses of three model organisms to ecological challenges as well as a repository of selected lines that will be shared with colleagues. The project will produce uniquely trained postdoctoral researchers, graduate students, and undergraduates with expertise in many disciplines, including genomics, physiology, ecology, evolution, and mathematics. If successful, the project will advance our understanding of biological systems from genes to ecosystems.

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.

This project will support students (undergraduate and graduate) and early-career (junior faculty and post-doctoral fellows) participating in the Seventh International Conference on Mathematical Modeling and Analysis of Populations in Biological Systems (ICMA VII), scheduled at Arizona State University, Tempe, USA, October 12-14, 2019. This conference will bring together researchers in the mathematical and biological sciences to share their latest research findings on the use of mathematical modeling and analysis to study problems arising in population biology and the life sciences, with emphasis on the fast-growing and challenging area of models in molecular and synthetic biology. The participants will range from internationally recognized established researchers to early career researchers and students (postdoctoral, graduate and undergraduate). The conference will include five plenary lectures given by selected researchers and approximately eighty invited or contributed talks by others, including early career participants. This conference will provide an opportunity for participants to establish new connections and energize established collaborations. Twenty students and early-career participants will be with an emphasis on women and members of underrepresented groups.

The broad theme of the conference is the formulation, validation, analysis and simulation of mathematical models for gaining insight into the spatiotemporal dynamics of biological populations. Specific topics include: fundamentals of molecular biology, mathematical immunology, genetic-epidemiology models, stoichiometric population models, mathematical oncology, mathematics of gene editing, and dynamics of multi-host-vector-pathogen systems. Mathematical modelling and analysis, coupled with novel mathematical and statistical techniques in data analytics, play a central role in providing realistic insight into the dynamics of real-life phenomena arising in the life sciences in general and molecular and synthetic biology in particular. In addition to allowing for the design and implementation of effective strategies for ensuring the persistence or extinction of some species (such as using gene editing to control the population abundance of malaria mosquitoes), molecular approaches potentially promote the development of new therapies for effectively combatting many human ailments, creating a need for population models which account for molecular techniques. For this effort to be effective, modelers and biologists need to build new collaborations, and a goal of the conference is to promote such interdisciplinary connections. The meeting will include participants whose research involves model derivation, mathematical and computational analysis of models and interfacing models with data and observations. The plenary speakers will be encouraged to reach a broad audience, surveying the current state of research in their field of study and suggesting new directions. More details may be found at the conference website:
https://math.asu.edu/icma-2019.

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.