The Research Experience
What makes this 10-week research experience unique and exciting is the combination of hands-on state-of-the-art research, didactic coursework, technical workshops, and direct guidance and collaboration with exceptional faculty.
This experience provides the students an opportunity to work in small teams, with students of diverse backgrounds in engineering, bioinformatics and the life sciences, to address problems in each of the thrust areas. Students will work together in groups of 3-5 on their projects, with teams consisting of students from both engineering and biology related backgrounds. Each team will also work closely with graduate students and faculty mentors.
The research experience includes:
- Courses in quantitative and integrative analysis
- Interdisciplinary team projects with faculty mentors from SBES and VBI
- Workshops on interdisciplinary teams, professional development, and state-of-the-art computation issues
- Student seminar series and final presentation to all BBSI faculty and students.
Some students will be invited back to Virginia Tech for a second 10-week summer research experience the following summer. Moreover, some students will also have an opportunity to continue their research projects at their home institution during the academic year. For this, students will be required to prepare a plan for continued study during the academic year and be invited to present the work they achieved during the academic year at the School of Biomedical Engineering and Sciences Annual Student Research Symposium or other related event.
The three research thrust areas:
- Computational systems biology
- Computational bio-imaging
- Computational physiology
Computational Systems Biology:
The availability of high-throughput data sets has made it feasible to begin the study of cellular networks and their relationship to genomic information. Mathematical modeling is an indispensable tool in this endeavor. Knowledge of traditional as well as newly developed mathematical techniques and their software implementations is crucial in systems biology research.
Example Project: Genomic data clustering. This project will introduce caBIG-VISDA software as a computational tool for cluster modeling, discovery, and visualization. Biomedical applications include defining new cancer subtypes, constructing hierarchical trees of cancer phenotypes, or discover the correlation between cancer statistics and risk factors.
Computational Bio-Imaging:
Imaging in the context of modern medical modalities and molecular/cellular imaging. This focus will have two components:
- general imaging science, and
- biomedical modalities.
The imaging science component covers general aspects of imaging that are relevant to all modalities and applications and are necessary to understand how images are used, interpreted, and manipulated. The modalities component is a high-level overview of modern modalities including x-ray, nuclear medicine, MRI, ultrasound, optical, tomography, etc.
Example Project: Comparison of ultrasound images and signals to histological images of muscle tissue. This project will introduce the student to several aspects of modern biomedical image analysis including:
- interdisciplinary team work by collaborating faculty and students in basic science to image histological slices and understand muscle tissue;
- multimodality image analysis, in particular microscope and ultrasound (CT and MRI images may also be available);
- relating images to cellular level structure; and
- image analysis software to solve real problems.
Computational Physiology:
Focus on physiology using engineering methods, namely mathematical, computational, and systems analyses. In physiological modeling, specific areas include the heart and circulatory system, the respiratory system, the renal system, sensory physiology, and thermal regulation. Students will work on
- identifying governing physical laws for a given physiologic system, and create a mathematical model quantifying the function of that system; and,
- explain relevant features for a given mathematical model of a physiologic system, and perform parametric studies, and draw conclusions about influences of parameters in healthy and pathological situations.
Example Project: Computational analysis of the biomechanics of vestibular hair cells. Students will begin with a qualitative description of a vestibular hair cell by identifying governing physical laws, and creating a simplified mathematical model that quantitatively describes the function of the cell. Students will then explain the relevance of each parameter in the model, perform parametric studies, and draw conclusions about the influences of the parameters in various physiologic situations, particularly in aerospace applications.
