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Advanced Studies in Bioinformatics and Data Science

What is Bioinformatics?

Precipitated by the immensity and explosion of publicly available genomic information, the field of bioinformatics has emerged as an important and dynamic interdisciplinary field in biomedical studies. Bioinformatics develops and applies computer technology as well as informatics, including mathematics and statistics, to store, analyze, interpret, and manage vast amounts of biological data. Data science is a quickly evolving interdisciplinary field that allows biomedical researchers to extract knowledge and insights from data in various forms. Through the integration of computer technology, software tools, databases, data analysis, systems and processes for data mining, bioinformatics and data science make it possible to generate large data sets and models, and thus address important biological questions and advance biomedical knowledge.

Advanced Studies in Bioinformatics and Data Science

The FAES Graduate School at NIH offers a unique Advanced Studies in Bioinformatics and Data Science to serve the quickly evolving needs of today’s biomedical research community. As one of the most dynamic fields intersecting biology and computer science, bioinformatics and its data analysis tools equip life sciences researchers and professionals with highly in-demand skills in the pharmaceutical and biotechnology industries. The Advanced Studies in Bioinformatics and Data Science will provide students with the theoretical foundations and practical skills to harvest the wealth of information contained in the vast amount of biological phenomena. The courses have been designed to train today’s biomedical researchers in new methods and techniques in data science and to prepare them to translate and analyze the immensity of biological data generated by advances made through recent applications of genomic research. NIH researchers and others will be also able to use these techniques to new applications relevant to basic biology and other data science research projects.

General Requirements

The program is designed for participants who hold an advanced degree in life sciences or STEM fields. The Advanced Studies comprises a 14-credit curriculum. Courses are held in the evenings to fit the needs of working professionals and postgraduate fellows.

Required Courses

BIOF 309 | Introduction to Python OR BIOF 312 Introduction to Perl
BIOF 518 | Theoretical and Applied Bioinformatics
BIOF 521 | Bioinformatics for Analysis of Next Generation Sequencing


BIOF 339 | Practical R
BIOF 395 | Introduction to Text Mining
BIOF 399 | Deep Learning for Healthcare Image Analysis
BIOF 450 | Evolutionary Genomics and Computational Biology
BIOF 475 | Introduction to New Technologies in Data Science
BIOF 501 | Introduction to R: Step-by-Step Guide (7 weeks)
BIOF 509 | Machine Learning and Object-Oriented Programming With Python
BIOF 529 | Super R with Shiny!
STAT 500 | Statistics for Biomedical Scientists I and II
STAT 500 I-O | Statistics for Biomedical Scientists I
STAT 500 II-O | Statistics for Biomedical Scientists II

Learning Outcomes

Upon completion, students will be able to:
■ Learn to use effectively different techniques to analyze biological data from high throughout approaches
■ Perform statistical analysis and visualization of biological data
■ Apply bioinformatics techniques for analysis of genomic, expression and proteomic data
■ Understand the uses and limitations of bioinformatics data analysis tools and technologies
■ Learn how the computational methods are used in new applications in basic biology and also how they are translated into the development of new drugs and diagnostic tools.