Title: The Software Engineer’s Role in Predictive Biology
Abstract: In the age of big data, predictive biology has scaled dramatically creating a community of biologists and bioinformaticians with a need for strong computational power. This talk will introduce a large open-source system aimed to meet these goals known as the Department of Energy’s Systems Biology Knowledgebase (KBase, http://kbase.us). KBase includes over 200 applications in the areas of genome assembly and annotation, sequence alignment, metabolic modeling, expression and more. There is also support for external tool integration through an SDK. KBase is designed to be open and collaborative where users can utilize public datasets, import custom data, create workflows built upon Jupyter notebooks, and share these workflows with others.
With every large software project comes the need for software engineering. We will discuss the software engineer’s role in such a project related to research and development. We will examine related research using software testing, machine learning, and modeling in the framework of systems biology. We will also discuss how configurability impacts apps inside KBase, and how research in software engineers can address these issues.