Bioinformatics is the field of science in which biology, computer science, and information technology merge into a single discipline. While the scope of this interdisciplinary field is very broad, there are three important sub-disciplines within bioinformatics: (1) the development of new algorithms and statistics with which to assess relationships among members of large data sets; (2) the analysis and interpretation of various types of data including nucleotide and amino acid sequences and structures; protein domains, interactions and networks; metabolic and disease pathways, etc; and (3) the development and implementation of tools that enable efficient access and management of different types of information.
The bioinformatics program in the Department of Epidemiology and Biostatistics is led by a faculty member, Dr. Igor Kuznetsov located in the Gen*NY*sis Center for Excellence in Cancer Genomics. He working on a wide range of research projects that involve developing bioinformatics tools for the analysis of genomic data. Dr. Kuznetsov's research is focused on the development of statistical and machine learning methods for the analysis of protein sequences and structures, large-scale genomic and proteomic datasets (including disease-related datasets), and genome-wide functional annotation. Dr. Kuznetsov co-teaches two graduate courses on Bioinformatics along with Dr. George Berg from the Department of Computer Science. In addition, Dr. Kuznetsov teaches Introductory Applied Statistics for Laboratory Sciences.
These bioinformatics courses can be chosen as electives by the students in Epidemiology and Biostatistics.
STA569- Principles of Bioinformatics
STA650- Advanced Topics in Bioinformatics
STA573- Introductory workshop on Bioinformatics