Degree At A Glance
- Credits: 30-32
- Tuition per Credit: $775
- On Campus and Online Courses Available
- Rolling admissions
- Choose from two distinct tracks
- Available as a 4+1 program
Use the links below to apply online at no cost, or to request further information.Apply Online Request Information
There is an incredible need for properly prepared bioinformaticians, to address the current revolution in biology. The field of bioinformatics will be a constant necessity, as the amount of data keeps growing and the nature of it keeps changing. Faculty from the biology department and data science program who will teach classes include Gina Lamendella, Vince Buonaccorsi, Jill Keeney, Loren Rhodes, and Kim Roth.
A Distinct Experience
Click on the banners below and learn more about what makes the Bioinformatics program unique at Juniata College.
Juniata is a leader in the GCAT-SEEK Consortium, a group of educators who seek to incorporate cutting-edge, high-throughput DNA sequencing technologies and computational methods into their curricula to provide students with hands-on opportunities to apply this technology to investigate biological questions. To further specialize their education, students can design their curriculum to follow one of two tracks: Computational concentration or Biotechnology concentration.
There are a growing number of internship and employment opportunities with local biotechnology and bioinformatics companies for those that enter this program. Two such companies are noted below.
Wright Labs applies novel microbial genomics methods to solve medical and environmental problems within a network of +80 academic, governmental, and private institutions. Founded at Juniata College’s Center for Entrepreneurial Leadership, Wright Labs is a story of student-led scientific innovation and entrepreneurship. We hire students and post-graduates through a plethora of research internships and new-hire opportunities. These high-impact practices enable researchers to create, dream, and design something of their very own, directly facilitating their self-discovery process.
CSI - Contamination Source Identification
CSI is the first, comprehensive technology that delivers nucleic acid sequencing data from clinical samples in a timeframe allowing for rapid diagnosis and selection of targeted antimicrobial therapies, thereby improving antibiotic stewardship. Our proprietary databases are continuously re-populated with pathogens identified from spatiotemporally relevant samples, keeping pace with rapid pathogen evolution and transmission routes. In addition, CSI computational pipelines perform real-time detection of antibiotic resistance genes, key to surveillance, infection control, and modeling emergence of antibiotic resistance.
Juniata's strengths in biology, computer science, and data-science will be leveraged not only by the faculty facilitating the bioinformatics program, but also by the students that are enrolled in the program. Opportunities for relevant course enrollment will exist, and the ability to mine knowledge and resources from these related disciplines will make for a rich and engaging experience.
A Juniata bioinformatics student will:
- Understand the different disciplines and application of bioinformatics (genomics, transcriptomics, proteomics, metabolomics)
- Acquire, validate, analyze, and present data to support biological interpretation
- Apply computational and statistical methods utilizing a variety of modern tools, technologies, and programming languages to solve problems in the life sciences
- Apply appropriate data visualization techniques for complex data
- Acquire the facility to interpret primary scientific literature
- Conduct a bioinformatics study in industry and/or the research environment
- Communicate technical information clearly to specific audiences
- Understand and uphold ethical guidelines applicable to data management, algorithm/software implementation, development, and data analysis.
Master of Bioinformatics (MBI) Curriculum
|Core Courses||MBI course #||Credits|
|Bioinformatics Fundamentals||BIN 500||4|
|Computer Science Fundamentals||DS 510||4|
|Advanced Cell and Molecular Biology||BIN 516||4|
|Statistics or Biostatistics Fundamentals||DS 520 or BIN 505||3|
|Computational Elective Course||MBI course #||Credits|
|Database Systems||DS 570||3|
|Multivariate Statistics||DS 530||3|
|Machine Learning||DS 552||3|
|Big Data Techniques||DS 575||3|
|Mathematics Fundamentals||DS 516||3|
|Data Science Fundamentals||DS 500||4|
|Data Acquisition and Visualization||DS 525||3|
|Biotechnology Electives Course||MBI course #||Credits|
|Genetic Analysis||BIN 599||3|
|Modern Molecular Techniques (Lab)||BIN 580||4|
|Medical Microbiology (Lab)||BIN 540||4|
|Molecular Microbiology (Lab)||BIN 531||4|
|Environmental Genomics (Lab)||BIN 600||4|
|Next Generation Sequencing Methods||BIN 585||3|
|Capstone Course||MBI course #||Credits|
|Capstone Experience||BIN 581||3|
- Core Courses (15 credits)
- Electives (at least 11 credits): Students can choose a minimum 11 credits of elective
- Computational track students must take a minimum of three (3) courses from the Computational electives.
- Biotechnology track students must take at least three (3) courses, one (1) of which must be a laboratory-based course from the Biotechnology electives and at least one (1) course from the Computational electives category.
- Capstone Experience (4 credits) A comprehensive project-based capstone experience, with a large focus on bioinformatics analysis of large datasets.
- Total credits: 30-32 credits.
For more information, please contact:
Assistant Director of Graduate Admissions