Bioinformatics (Master of Science)

Bioinformatics is an interdisciplinary field that integrates natural sciences (biology and chemistry), computer science, and statistics. Opportunities within the field 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 six 3-credit required courses, two 3-credit electives, and a 6-credit internship or thesis course option for a total of 30 credits. The core six 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. Students will pursue either an internship, integrative thesis, or two additional electives 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 over one calendar year. Delivery of the program will be mostly online format with in-person labs on weekends at the Beverly campus. One to two courses will be taken concurrently with each lasting six weeks. All of the courses have been developed specific to this program and are interdisciplinary 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).

Prerequisites

Bachelor’s degree in biology, chemistry, computer science, or mathematics with a minimum GPA of 3.0

Curriculum Requirements - Total Credits Required: 30

Required Curriculum - 18 Credits

BIN 501 - Introduction to Programming for Bioinformatics (Cr: 3)
BIN 510 - Probability and Statistics with Programming (Cr: 3)
BIN 520/520L - Molecular Genetics and Lab (Cr: 3)
BIN 521/521L - Protein Biochemistry and Lab (Cr: 3)
BIN 601 - Advanced Programming for Bioinformatics (Cr: 3)
BIN 602 - Data Mining for Bioinformatics (Cr: 3)

Elective - 12 Credits

Students may select either BIN680 or BIN690 but not both

BIN 603 - Principles of Software Design and Engineering (Cr: 3)
BIN 610 - Advanced Statistics and Data Visualization (Cr: 3)
BIN 620 - Biological Sequence Analysis (Cr: 3)
BIN 621 - Cheminformatics and Drug Discovery (Cr: 3)
BIN 622 - Proteomics (Cr: 3)
BIN 650 - High-Throughput Screening and Image Analysis (Cr: 3)
BIN 651 - Biological Systems Analysis (Cr: 3
BIN 670 - Introduction to Machine Learning and Distributed Computing (Cr: 3)
*Student may select BIN 680 or BIN 690 but not both
BIN 680 - Bioinformatics Internship (Cr: 6)
BIN 690 - Bioinformatics Thesis (Cr: 6)

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 interdisciplinary and applied learning environment that integrates theory and real-world application.

Learning Outcomes

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
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