Bioinformatics (Master of Science)
Bioinformatics is an inter-disciplinary field that integrates natural sciences (biology and chemistry), computer science, and statistics. The field is less than two decades old and opportunities within it have grown exponentially over the last several years. Bioinformatics positions vary, ranging from entry-level basic computer programming jobs that require a bachelor’s degree to research in machine learning by Ph.D.-trained scientists and beyond. Many positions are master’s level consulting/service positions to biologists with large experimental datasets who lack the expertise to analyze them computationally.
The Master of Science in Bioinformatics program at Endicott is composed of eight 3-credit required courses, two 3-credit electives, and a 6-credit internship or thesis course option for a total of 36 credits. The core eight courses provide students with the breadth of content and technical skills to obtain a variety of bioinformatics jobs as students will have experience in programming, data retrieval and analysis, statistical applications, and the scientific foundation needed to understand the biological context of their work. All students will pursue either an internship or integrative thesis during the final summer session. This experience and the elective options enable students to specialize in an area of interest that will make them uniquely attractive for more focused bioinformatics job opportunities of their choosing.
The program is designed to be completed part time over two years. Delivery of the program will be in a hybrid format with a combination of on-line and in-person teaching (including labs) in the evenings and/or on weekends at the Beverly campus. Two to three courses will be taken concurrently with each lasting 15 weeks (fall/spring) or 10 weeks (summer). All of the courses have been developed specific to this program and are inter-disciplinary with a pedagogical focus on applied learning and bioinformatics research projects. Because the courses in the curriculum build upon each other, there necessarily is a specific sequencing that must be followed (see “Curriculum by Semester” heading below).
Bachelor’s degree in biology, chemistry, computer science, or mathematics with a minimum GPA of 3.0
Program Goals and Objectives
- To provide students with a broad understanding of the disciplines that comprise bioinformatics (biology, chemistry, computer science, mathematics, statistics) and the diverse functions of bioinformatics scientists.
- To provide students with in-depth knowledge of relevant biological sub-disciplines.
- To provide students with technical skills in computer programming, data acquisition and mining, research methods, and statistical analysis.
- To provide students with opportunities to enhance skills in critical thinking, problem solving, conceptualization of solutions, study design, and communication with biological and computer scientists.
- To provide students with an inter-disciplinary and applied learning environment that integrates theory and real-world application.
Curriculum Requirements - Total Credits Required: 36
Required Curriculum - 24 Credits
Elective - 12 Credits
Students may select either BIN680 or BIN690 but not both
At the end of the program, the student will demonstrate:
an ability to apply knowledge of computing, biology, statistics, and mathematics appropriate to the discipline
an ability to analyze a problem, and identify and define the computing requirements appropriate to its solution
an ability to design, implement, and evaluate a computer-based system, process, component, or program to meet desired needs in scientific environments
an ability to use current techniques, skills, and tools necessary for bioinformatics practice
an ability to function effectively on teams to accomplish a common goal
an understanding of professional, ethical, legal, security and social issues and responsibilities
an ability to communicate effectively with a range of audiences
a recognition of the need for, and an ability to engage in continuing professional development
detailed understanding of the scientific discovery process and of the role of bioinformatics in it
an ability to apply statistical research methods in the contexts of molecular biology, genomics, medical, and population genetics research
in-depth knowledge of relevant areas of biology and an understanding of biological data generation techniques