Online Masters in Bioinformatics, BioMedical Informatics No GRE

NYU Tandon School of Engineering - Bioinformatics Master Degree

The last decade has seen unprecedented changes in biotech, biomedicine, biomanufacturing, and bioengineering. Most of it is fueled by new genomics and other omics technologies that generate massive amount of data, but also do so at a higher and higher resolution going down to single molecules and single cells. The resulting data need to be interpreted carefully, because a single mutation in a base (e.g., “​SNP​”​) could be the cause of a disease. ​The resulting data is massive, as biotech​’​s Moore​’​s law grows exponentially (doubling every five months in comparison to computers​’ ​doubling every eighteen months).

Students who earn a Bioinformatics Advanced Certificate may apply those credits towards the Bioinformatics Master's Degree. Note that only 9 credits from the Advanced Certificate can be used towards the Bioinformatics Master Degree program.

Ranked #2 in Best Online Graduate Information Technology Programs by the students.S. News and World Report

The NYU Tandon Bridge course is recommended to those interested in a Bioinformatics master's degree who are lacking a Bioinformatics degree or other substantial related experience.

GRE or GMAT Score the university recognize that due to COVID-19 restrictions some applicants may experience difficulty in taking the GRE test and, in response, the New York University is committed to being flexible. For the Spring 2021 and Fall 2021 terms, the GRE is not required for all NYU Tandon Online MS programs.

Students will participate in interactive online modules, live webinars, assignments, and tests.

The online course is aimed at introducing the foundational ideas from computer science in designing and implementing bioinformatics algorithms.

The online course is aimed at introducing the key ideas from biology and biochemistry and how they are used in modern biotechnology.

The online course is aimed at introducing the fundamental concepts from mathematics, probability and statistics, as relevant to bioinformatics and computational biology.

This online course will introduce the basics of statistics and its applications in various fields of biology.

This online course is aimed at developing practical machine learning and econometric skills with applications to biological data.

The online proteomics course contributes an application focused specialty class to the bioinformatics curriculum.

The online course is aimed at developing practical bioinformatics skills of next generation sequencing analysis.

This online course will introduce will expose the students to different aspects of the data analysis and modeling activities that are expected of a Bioinformatician or a Computational Biologist. This course will explore a different set of online resources that contain complex data models of data ; the data thus collected will be used to expose novel model reconstruction tools. Other online resources and related exchange formats will be explored in order to show how simulation of biological systems models in its different forms has become more and more usable and an important tool for biomedicine.

The online course is aimed at introducing the key ideas from population genetics and how they are used to understand the interaction of basic evolutionary processes that determine the genetic composition and evolutionary trajectories of natural populations.

Machine learning concepts and tools for statistical genomics will be addressed along with distance concept, cluster analysis, heat map and class discovery.