The Online Graduate Certificate in Applied Bioinformatics (ABNF-CERT) is offered as a graduate level program ideally suited for working professionals who wish to gain knowledge and practical experience in bioinformatics. Building on the core curriculum of UD’s MS, PSM and PhD bioinformatics degree programs, the Online Graduate Certificate will allow students to gain core competency in bioinformatics for real-world applications from genomic medicine to agriculture. No previous programming or database experience is required but a familiarity with molecular biology concepts is recommended.
Academic Outcomes
- Earn credential from a highly reputable bioinformatics program to advance your career
- Earn graduate level college credits that can be applied towards a Master’s or PhD degree program
- Gain core competency for rapidly growing bioinformatics job opportunities in fields from genomics, pharmaceuticals and health care to big data analytics
- Gain knowledge and experience in bioinformatics and systems biology methods and tools and practical programming and database skills for real-world applications
- Learn cutting-edge state-of-the-art course contents from nationally and internationally renowned researchers and practitioners in the field
- Learn in an interactive, experiential and multidisciplinary team environment that couples lecture-based instructions with hands-on exercises and term projects
Requirements (Browse Courses)
The course curriculum consists of four graduate level courses that can be taken in any order. Each course will be offered annually during either Fall or Spring semester. Two courses will be offered each semester so that the Certificate program can be completed in as little as one year.
- BINF644 Bioinformatics (3 Credits): Principles of molecular sequence analysis and genome annotation with practical guides to bioinformatics resources, databases and tools
- BINF694 Systems Biology (3 Credits): Bioinformatics interpretation and biological network analysis of omics data from next-generation sequencing (genomics, transcriptomics) and other high-throughput technologies
- BINF640 Databases for Bioinformatics (3 Credits): Principles and techniques of bioinformatics database development cycle from data modeling to relational database management and web hosting
- BINF690 Programming for Bioinformatics (3 Credits): Principles and techniques of computer programming using Python language framed within the context of bioinformatics
New Online Bioinformatics Courses
The Center of Bioinformatics & Computational Biology (CBCB) is proud to announce the offering these new graduate level online and hybrid courses.
- BINF667-010 Applied Machine Learning (3 Credits): This course introduces students to the basic concepts to understand machine learning principles and paradigms, and equips them with knowledge of machine learning pragmatics that are involved in a complete learning process from formulating a problem to choosing the appropriate techniques/tools to evaluating the results.
- BINF667-011 Data Science with Online Competitions (1 Credit): The course aims to introduce students to online data science competitions on Kaggle. Students will participate in various online competitions on Kaggle and get hands-on experience with applied machine learning.
- BINF690-194 (BINF690-010 Hybrid) Programming for Bioinformatics (3 Credits): This course teaches principles of computer programming using Python language. The course covers basic technique, syntax, best practices, advanced programming concepts and basic algorithm designs through a series of lectures, assignments and projects framed within the context of bioinformatics. The course has no prerequisites and is designed to teach Python to all levels, from beginner to experienced programmer. Once a student completes this course they will be able to write, understand, and edit complex programs in Python. Students will also gain a firm grasp of using the GIT version control system, as well as several common bioinformatics packages and techniques. This course covers Python 2, with mention of differences between Python 2 and 3.
Tuition
- Discounted tuition rate
How to Apply
- Applicants to the program must be in the last semester of undergraduate study or hold an undergraduate degree in biological, computational, or other disciplines from an accredited four-year college or university. However, applicants are expected to have competence in mathematics, computer science and/or biology
- OFFICIAL TRANSCRIPT (a minimum grade average of 3.0 on a 4.0 system is considered competitive)
- TWO LETTERS OF RECOMMENDATION
Ideally, at least one letter from a professor, while the other letter can be from employers or others who have had a supervisory relationship with the applicant and are able to assess the applicant’s potential for success in graduate studies - RESUME/CV outlining work and academic experience
- APPLICATION ESSAY consisting of the answers to the following questions:
- What educational background and scientific research or employment experience prepare you for this bioinformatics certificate program?
- What are your long-term professional objectives?
- What specific attributes of the bioinformatics program make you feel that this certificate is appropriate to help you achieve your professional objectives?
- TOEFL Scores:Students from non-English speaking institutions require an official paper-based TOEFL score of at least 550, at least 79 on the Internet-based TOEFL, or a minimum IELTS score of 6.5. TOEFL scores more than two years old cannot be considered official
- GRE Scores are recommended but may be waived upon application review.
Please contact bioinformatics@udel.edu for more information.