Computational scientist researches ways to evaluate and monitor microbial life in water

Sade Davenport, Ph.D., got her interest in science, technology, engineering and mathematics (STEM) from her parents. With her dad being an electrical engineer for the United States Navy and her mom a mechanical engineering project manager also for the Navy, it wasn’t a hard decision for Davenport to pursue a degree in STEM.

Davenport attended North Carolina Agricultural and Technical State University and received a bachelor’s degree in biology followed by both a master’s and doctoral degree in computational science and engineering. While completing her doctoral degree, Davenport began searching for fellowships online when she found an Oak Ridge Institute for Science and Education (ORISE) opportunity with the Office of the Director of National Intelligence (ODNI) for an Intelligence Community Postdoctoral Research Fellowship (IC Postdoc Program).

“My reason for applying was because the opportunity provided me with more training and skills for my future career and the funding provided was enough to cover my living expenses so I can focus on furthering my research training toward being an independent researcher,” she said. “This program was ideal for supporting innovative interdisciplinary research oriented upon examining complex real-world data sets.”

The IC Postdoc Program offers scientists and engineers from a wide variety of disciplines unique opportunities to conduct research relevant to the Intelligence Community.

Davenport is part of a computational system biology research laboratory team led by Scott Harrison, Ph.D., at North Carolina Agricultural and Technical State University. Together, they are researching ways to streamline and integrate a systematic multi-omics approach stemming from three software technologies: data warehousing of genomic and environmental information to support subsequent variable identification and discriminant analysis; a neural network-based method to discern information encoding protein structure; and a visual and semantic model for interpreting the evaluated information within the context of network biology, the interactome.

With recent developments in biotechnology and computational biology that provide for a greater capacity for generating and evaluating data, life’s diversity can now be more powerfully investigated in a comparative context across genomic sequences, multiple lineages and environmental contexts.

“The challenge is to harness these emergent capabilities into a platform that can navigate complex genetic variations and environmental dynamics,” Davenport said.

The team’s combined approach toward evaluating environmental conditions along with microbial composition and function will inform better understanding of aquatic ecosystems and promote objectives for water quality and safety.

“Water is an essential source to sustain life; it has a history of not only physical and chemical conditions but also of the planktonic microorganisms that reside in it,” she said. “By learning more about microscopic life in water, we will better understand fluctuations in aquatic microbial life.”

A typical day for Davenport involves going into the lab to work on the software development side of their project, mainly in the R programming language, which facilitates robust analysis and visualization of the planktonic data. Afterwards, she works on project documentation, presentations and articles that are going to be submitted to journals and will have discussions with her mentor, Harrison, to discuss current technical approaches and their current project.

Davenport spoke highly of the program, recommending it to graduating doctoral students.

“During my time I also pursued additional technical training in topics of interest to me, including learning structured query language (SQL) and obtaining a certificate in Quantum Computer Fundamentals,” she said. “This year, I will learn how to sequence using nanopore technology, which is exciting because now I can collect and use real data from the field and not be only reliant on existing databases.”

After completion of the program, Davenport aims to either work for a government agency, such as the U.S. Environmental Protection Agency (EPA) or the Centers for Disease Control and Prevention (CDC), as a data scientist or apply for a third year with the program.     

In the meantime, Davenport has two things to look forward to: writing a set of two primary articles and welcoming a new member to the family alongside her husband in November. While waiting, she hopes to publish her articles, “Analysis of Oceanic Fungal Gene Expression through an Integrative, Machine Learning Architecture” and “Evolutionary Dynamics of Phosphorylation Sites of Signal Transduction Proteins in Phylogenetic Subgroups of Fungi,” to relevant journals. 

The Intelligence Community Postdoctoral Research Fellowship Program is funded by the Office of the Director of National Intelligence (ODNI) and managed by the Oak Ridge Institute for Science and Education (ORISE) under an agreement between the IC and the U.S. Department of Energy (DOE). ORISE is managed for DOE by ORAU.