The M.S. in Computational Biology and Biostatistics at St. John’s University answers a growing demand for data analysts, data curators, database developers, statisticians, mathematical modelers, bioinformaticians, and software developers with training in both computer science and biology.
Solve urgent global problems using computational methods at St. John’s University in New York City.
The M.S. in Computational Biology and Biostatistics at St. John’s University answers a growing demand for data analysts, data curators, database developers, statisticians, mathematical modelers, bioinformaticians, and software developers with training in both computer science and biology. The program trains you in the use of computational methods and algorithms to represent and simulate biological systems, as well as to interpret large-scale experimental data.
The competencies you develop in the program prepare you to address some of the world’s most urgent problems, including food shortage, climate change, and emerging diseases. Because these issues disproportionately affect the world’s poor, the M.S. program aligns with the mission of St. John’s.
In addition to undergoing rigorous training in understanding and modeling the structures and processes of life, you develop a critical consciousness and ethical perspective, preparing you for service and leadership roles in local, national, and international spheres.
Professor, Mathematics and Computer Science
The M.S. in Computational Biology and Biostatistics provides students with undergraduate degrees in the natural sciences or mathematics with the opportunity expand their career options to the field of computational biology.
In addition to the general requirements for admission to graduate study in St. John’s College of Liberal Arts and Sciences, applicants must present a cumulative undergraduate grade point average of 3.0, as well as a 3.0 or better in the major discipline. No Graduate Record Examination scores are required. The program accepts applications year round.
Graduate Admission Information
Office of Graduate Admission
718-990-1601
[email protected]
The M.S. in Computational Biology and Biostatistics requires the successful completion of 36 graduate credits and a comprehensive examination. Because of the interdisciplinary nature of the program, the course offerings draw upon the expertise of faculty across departments in St. John’s College of Liberal Arts and Sciences.
Required
| Course Number | Course Title | Credits |
|---|---|---|
| BIO 207 | Biochemistry | 3 |
| BIO 208 | Molecular Biology | 3 |
| BIO 209 | Bioinformatics | 3 |
| BIO 212 | Cell Biology | 3 |
| MTH 161 | Introduction to Probability | 3 |
| MTH 163 | Statistical Modeling | 3 |
| MTH 165 | Introduction to Computing with Applications | 3 |
| MTH 209 | Linear Algebra I | 3 |
| MTH 240 | Computational Biology | 3 |
Electives (select three)
| Course Number | Course Title | Credits |
|---|---|---|
| BIO 210 | Practical Genomics/Transcriptomics | 3 |
| BIO 236 | Microbial/Molecular Genetics | 3 |
| BIO 248 | Laboratory Techniques and Applications I | 3 |
| BIO 250 | Topics in Immunology | 3 |
| BIO 299 | Scientific Literacy and Integrity | 3 |
| CUS 610 | Data Mining and Predictive Modeling I | 3 |
| CUS 615 | Data Mining and Predictive Modeling II | 3 |
| HCI 520 | Medical and Health Informatics | 3 |
| HCI 525 | Applied Healthcare Analytics | 3 |
| MPH/PAS 252 | Biostatistics | 3 |
| MTH 167 | Mathematical Modeling I | 3 |
| MTH 172 | Operations Research I | 3 |
| MTH 180 | Computer Algorithms | 3 |
| MTH 222 | Machine Learning | 3 |
| MTH 242 | Artificial Intelligence | 3 |
Comprehensive Examination
| Course Number | Course Title | Credits |
|---|---|---|
| CBB 105 | Comprehensive Examination | 0 |
Graduate Assistantships
St. John’s University offers competitive graduate assistantships to qualified full-time applicants. These positions typically include tuition remission and a stipend. Read more about Graduate Assistantships and additional forms of financial aid available to St. John’s graduate students.
The need to address major problems facing the world—including nutrition for a growing population, global climate change, aging populations, “civilization diseases” (e.g., cancer, diabetes, and cardiovascular diseases), and emerging infectious diseases—results in exponentially growing demand for researchers and professionals trained in biology and computational methods and approaches.
According to the US Bureau of Labor Statistics, employment in the fields of medicine and science will grow at 16 percent through 2028, much faster than average. The job outlook for mathematicians and statisticians is expected to grow 30 percent within the same period.
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