This track has been designed for students who desire in-depth training in applications of bioinformatics and computational modeling.
Highly Recommended Courses
Bio Core 1: Molecules and Cells - BIOL-GA 1001, 4 points. A survey of the major topics of up-to-date molecular and cellular biology, starting with molecular structure and function of proteins and polynucleic acids and ending with cell division and apoptosis.
Bio Core 2: Genes, Systems, and Evolution - BIOL-GA 1002, 4 points. A survey of the major topics of modern biology, including genetics, genomics, systems biology, developmental genetics, cell biology, neurobiology, population genetics, and evolution.
Statistics in Biology - BIOL-GA 2030, 4 points, which is a pre-requisite for several other bioinformatic courses. Advanced course on techniques of statistical analysis and experimental design that are useful in research and in the interpretation of biology literature. Students will be trained to use the programming package R.
Applied Genomics: Introduction to Bioinformatics and Network Modeling - BIOL-GA 1130, 4 points. Introduces fundamental methods of analyzing large data sets from genomics experiments. Through a combination of lectures, hands-on computational training, and in-depth discussions of current scientific papers, students learn the conceptual foundations of basic analytical methods, the computational skills to implement these methods, and the reasoning skills to read critically the primary literature in genomics.
Programming for Biologists - BIOL-GA.1007, 4 points. Provides introductory theory and hands-on training in bioinformatics. Students are introduced to the Linux operating system and basic computer programming skills (Perl and Bioconductor). Topics covered: biological databases, pairwise and multiple sequence alignment, BLAST and related algorithms, sequence motifs, Hidden Markov Models, gene expression analysis, and resources for functional associations (gene ontology, pathways and networks).
Biological Databases and Datamining - BIOL-GA 1009, 4 points. The course is divided into three sections: 1) Introduction to MySQL and R. 2) Introduction to different data types, and 3) Machine learning methods for data mining. Students will learn to create their own database using MySQL and SQLite containing different types of biological data. Students will also learn to mine the heterogeneous biological data using machine-learning methods such as Support Vector Machines and Multiple Regressions. We will apply these methods on experimental data in order to classify and prediction gene function and regulation.
Bioinformatics & Genomes - BIOL-GA 1127, 4 points. Covers fundamental bioinformatics techniques with an emphasis on developing not only an understanding of existing tools but also the programming and statistics skills that allow students to solve new problems in a creative way.
Research - BIOL-GA 3303-3304, 1-6 points. Students in this track also typically take research credits, since hands-on experience in bioinformatics/genomics is especially important. Each student must complete a research paper under the supervision of a Biology faculty member, however, students may seek approval from the Director of the Master’s Program, for a main sponsor who is outside the Biology Department.
Special Topics in Physiology - BIOL-GA 1031, 4 points.
Hot Topics in Microbiology and Infectious Diseases - BIOL-GA 1023, 4 points.
Cell Biology - BIOL-GA 1051, 4 points.
Structure-Function Relationships in Cellular Macromolecules - BIOL-GA 2017, 4 points.
For additional course offerings through the Departments of Biology, Biomaterials, and Basic Medical Sciences (NYU medical school), please see the GSAS Bulletin, or at the registrar’s web site for the schedule of course offerings.