Informatics and Bioinformatics
The study of Informatics is focused on the collection, curation, and analysis of large amounts of diverse data. Driven in large part by the emergence of robust applications of scale free computing, areas associated with Informatics are supported at the intersection of machine learning, data mining, scalable data storage and digital communication, as well as the fields of statistics and mathematics. At Baylor, students interested in Informatics can further refine their focus by pursuing majors in Data Science or Bioinformatics.
The amount of data produced by life science, physical science, and business domains far outpaces the ability of lab biologists, bench researchers, information managers or other domain experts to manage, or exhaustively analyze the data for meaning. In particular, domain experts often lack the computer infrastructure or deep understanding of the underlying computational complexity to effectively analyze these immense data sets. In addition, users must be able integrate data and data types across an ever expanding landscape of data varieties to uncover new knowledge. The undergraduate Data Science major is designed to prepare students to produce data driven solutions in a wide variety of disciplines.
First offered in 2020, the Bachelor of Science in Informatics (BSI) with a major in Data Science will expose undergraduate students to skills required to be successful in the high demand areas associated with data analytics. This includes programing, cloud computing, machine learning, visualization and statistical analysis. Students will engage in extended project-oriented classes and applied development and implementation of real-world solutions.
In addition, the Data Science degree requires that each student receive a minor in a separate discipline. This will ensure that students have the knowledge base necessary to adapt data science skills to domains of interest.
Rick Seaney, Baylor ECS Board of Advocates member and CEO of 3Victors, has supported the development of this program due .
"There is literally no limit to the number of jobs that are in dire need of quality data scientists and data engineers," Seaney said. "The mythical perfect data scientist is known as a data science 'unicorn', representing equal parts computer science, mathematics and subject matter expertise sprinkled with a blend of quality trustworthy storytelling. An excellent undergraduate foundation will be ample for a significant number of job opportunities with graduate degrees for those who want to participate on the leading edge of the space."
"At the time Baylor made the decision to create the program, bioinformatics was really an emerging field," said Dr. Erich Baker, chair and professor of Computer Science. In 1999, Baylor became the second university in the nation to offer bioinformatics as an undergraduate degree. (The first was Carnegie Mellon University, which now offers an undergraduate degree in computational biology.)
"Because the idea of an undergraduate degree in bioinformatics was so new, we had a lot of discussion about what to include in the program," Baker said. "Professors and advisors from the life sciences, mathematics and computer science were involved in the decision-making."
"What was created is an exhaustive curriculum," Baker said. "It's essentially a double major in biology and computer science with a minor in chemistry."
The mission of the program is to give students a wide background in a variety of areas: informatics (database design, web interfaces, data warehousing, distributed systems, security and library science); computational science (mathematics, statistics, algorithms, computer science, modeling, imaging and High-Performance Computing); and life science (genetics, physiology, embryology, immunology, developmental biology, medicine, epidemiology, pharmacology, psychiatry, veterinary medicine, ecology, forensics, anthropology and agriculture). The program also covers gene and genome product sequencing and structure analysis.
"Our goal is to produce students competent across multiple disciplines," Baker said. "We want them to know enough computer science to know what is computable, and enough life science to know what needs to be computed."