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Department of Mathematics & Statistics

Interdisciplinary Training for Undergraduates in Biological and Mathematical Sciences

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Program Overview

PI: Dr. Edwin Tecarro
Co-PI: Dr. Akif Uzman, Dr. Jeong-Mi Yoon, Dr. Youn-Sha Chan

The Departments of Mathematics & Statistics (MS) and Natural Sciences (NS) began in the Fall 2007 the NSF-sponsored UHD UBM Program: Interdisciplinary Training for Undergraduates in the Biological and Mathematical Sciences. UHD UBM program seeks to enhance undergraduate education and training at the intersection of the biological and mathematical sciences. The program will prepare undergraduate biology or mathematics students for graduate study and careers in fields that integrate the mathematical and biological sciences. Students who participate in this program will receive a stipend for research and related educational activities.

Total amount founded to UHD: $899,750.00
Total grant amount: $899,750.00
Grand Duration: October 15, 2007 - September 30, 2012
Partner schools: none
Any other relevant information on the grant: The program promotes curriculum changes in UHD's programs in Biology and Mathematics, e.g., the creation of a new Calculus sequence for Life Science majors.

Program Requirements

  1. Students must commit to 2 semesters and one 10-week summer in which they participate in research, directed studies in areas relevant to their project, and take courses in biology and mathematics as assigned by their UBM advisors.
  2. Minimum course requirements include General Biology I/II, Calculus I/II, and one upper-division course in biology and mathematics.
  3. Students will present their work at local, regional, and national meetings (funds are available for travel)
  4. Maintain a minimum of 3.0 GPA in science and math in every semester the student participates in the program


  1. Semester stipends: $1875 / 10 hrs per week effort in research
  2. 10-week summer session: $5000 / 40 hrs per work effort in research


Eligibility and Application Form

Click here for grant information

Click here for Application Form (December 1, 2010 by noon in S716)

In order to be considered for this training program, applicants must meet the following minimum requirements:

  1. Be a citizen or permanent resident of the US
  2. Be a declared major in mathematical or life sciences at UHD
  3. Have a minimum 2.5 Grade Point Average

Research Projects and Faculty

Fungal Population Dynamics in Coastal Tallgrass Prairie Systems

Faculty: Dr. Phil Lyons (NS) and Dr. Shishen Xie (MS)

Project description: Coastal Prairie was once the dominant ecosystem throughout much of the Gulf Coast region of Texas and Louisiana. Now, only remnants of native prairie remain. Efforts are being made to preserve these remnants and to restore disturbed areas to native conditions. It is important to these efforts to develop a better understanding of Coastal Prairie ecology than currently exists. This study focuses on the ecology of Coastal Prairie and how soil microbial communities, particularly fungi, are affected by farming and restoration. To address this question we will monitor and analyze changes in fungal communities within bulk soil and the root rhizospheres of four native grass species throughout a restoration process. Molecular genetic analyses will be used for these studies. A simulated mathematical model based on statistical techniques (mean, confidence interval, and standardization, etc.), fuzzy analysis, and Principal Component Analysis (PCA) will be developed to analyze population structures of farmed and native Coastal Prairie Ecosystems during the restoration process.

Stress Analysis of Bacterial Biofilms

Faculty: Dr. Poonam Gulati (NS) and Dr. Youn-Sha Chan (CMS)

Project Description: In environments with sufficient moisture and nutrients, microorganisms grow as biofilms. A biofilm is a community of microbes that are growing attached to a surface and are encased in polymers that they have synthesized and secreted. This mode of living protects the microbes from the environment. Some studies have found that fluid shear influences the physical properties such as density and strength of biofilm. For instance, biofilms grown at higher shear are smoother and denser than those grown at low shear. A question we ask is how the shear stress effects the cell growth in a biofilm? How is the mechanical force transferred to the cells? Is there a biomechanical process involved? How do mechanical forces affect cell signals? In this project we will investigate the mechanism of biofilm formation and try to answer some of the proposed questions. Mathematical models using partial differential equations and qualitative and quantitative biochemical and molecular analyses will be used to address these questions.

Mathematical Models of Pierce's Disease

Faculty: Dr. Lisa Morano (NS) and Dr. Jeong-Mi Yoon (CMS), Dr. Volodymyr Hrynkiv (CMS)

Project Description: Pierces Disease (PD) is a threatening bacterial disease of grapevines with the capacity to kill an entire vineyard in one year. The disease is caused by a bacterium Xylella fastidiosa and is transmitted by a xylem-feeding insect commonly called a sharpshooter. Once transferred to the xylem vessels (water-conducting structures) by the insect, the bacteria multiply and lead to the blockage of water transport and subsequently death of the vine. The spread of PD in both Texas and California is a threat to wine grape industries in both states. We are currently collecting environmental data (elevation, precipitation, cold hardiness, plant community) from vineyards in Texas and combining with USDA insect trapping data for the last several years. As part of the PD Research and Education fund scientists have created a database of insect frequencies for all species of insects which could transmit the disease. We will start by running regression analysis between specific species and environmental variables to determine which environmental variables are responsible for insect spread (and ultimately disease spread). Eventually we will develop a canonical correspondence analysis model to evaluate patterns of environmental variables, vineyard, and insect species. We will be using similar analyses to model two future data sets we are generating. One will investigate xylem (sap) chemistry and the presence of bacterial endophyte species in PD susceptible and PD tolerant grapevines. Another will investigate patterns in wine quality characteristics and the presence of wine spoilage organisms.

Building a Diatom Succession Model for a Fresh Water Marsh

Faculty: Dr. Brad Hoge (NS) and Dr. Ronald Barnes (CMS)

Project Description: Data exists for diatom assemblages in the Anahuac wetlands. Some of this data gives assemblages of diatoms as a function of time. We wish to look at the time sequence of this data to see if there is some standard progression that wetlands follow as they mature. This model could be used to study the state of developing wetlands.

Mathematical Modeling of Interacting Signaling Pathways During Neural Development in Vertebrates

Faculty: Dr. Akif Uzman (NS) and Dr. Edwin Tecarro (CMS)

Project Description: The onset of the development of the central nervous system in vertebrate embryos (called neural induction) arises from an interaction between two signaling pathways, the BMP4 (bone morphogenetic protein-4) pathway and the MAPK (mitogen-activated protein kinase) pathway. No quantitative analysis of these pathways has been done to understand how this interaction leads to specific phenotypic outcomes. The current model of interactions between these two pathways hypothesizes that increases in MAPK activity lead to a repression of the BMP4 pathway, which induces subsequent neural development by inhibiting migration of the SMAD 1/4 transcription factor into the nucleus. Conversely, epidermal development is induced by the SMAD 1/4 transcription factor, which activates and/or represses genes leading to the development of epidermal tissue. Quantitative mathematical models will be explored to provide key testable insights into which key parameters control this developmental decision. Key biochemical parameters including relative protein concentrations and binding interactions will be determined to help define key parameters of proposed models.

Contact Information

For further information on each project, click on the faculty members names above.
For general information on the program, contact:

Dr. Edwin Tecarro

Dr. Akif Uzman



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