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Bioinformatics and Systems Medicine

By merging biology, statistics, mathematics and computational modeling, these interdisciplinary approaches help our researchers understand biological data and link them to clinical data to benefit patients. Topics include Precision Health, Genomic Medicine, Pharmacogenetics, Functional Genomics, Next Generation Sequencing, Single Cell Sequencing, Microarray Data Analysis, Imaging, Biological Pathways, Smart Clinical Trials, and Multimodality Modeling.

Students can pursue an education in Bioinformatics and Systems Medicine under the following academic programs: Graduate Certificate, Master of Science (MS), Doctor of Philosophy (PhD).


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SELECTED COURSES IN BIOINFORMATICS AND SYSTEMS MEDICINE

In addition to a core set of foundational courses for all concentrations, the following are selected courses focusing on Bioinformatics and Systems Medicine.

Course Description:
The course gives a comprehensive entry-level introduction to bioinformatics. It covers a wide variety of topics in bioinformatics, including but not limited to genome analysis, transcription profiling, protein structure and proteomics. Two major goals are 1) to help students understand the scope, basic concepts and theory of bioinformatics; and 2) to become familiar with tools for bioinformatics-related data analysis. Using software tools will be a major component of the course but advanced programming skills are not required. A laptop computer is necessary to use the bioinformatics software and tools in class and while performing the research tasks for the course project.

Course Description:
Pharmacogenomics is the study of how human genetic variation impacts drug response. It is one of the major promises of the genome project: that individual genetic information can be used to tailor drugs to patients, maximizing efficacy and minimizing adverse reactions. An understanding of pharmacogenomics requires dual understanding of the basics of genetics and genomics and of pharmacology. This course will provide the background to understand the current state and literature in pharmacogenomics, including the methods used in research and the current issues in discovery and implementation of pharmacogenomics.

Course Description:
This course provides students practical skills and statistical concepts and methods that underlie the analysis of high-dimensional genomic and Omics big data generated by high throughput technologies. It will also address issues related to the experimental design and implementation of these technologies. Lectures will often be delivered with live demonstrations. Students will engage in practical problem solving sessions. The R language will be used for programming throughout the course.

Course Description:
Systems medicine is an interdisciplinary field of study that looks at the systems of the human body as part of an integrated whole, incorporating biochemical, physiological, and environment interactions. Systems medicine draws on systems science, omics, imaging, systems biology, and considers complex interactions within the human body in light of a patient's genomics, behavior and environment, and design the precision medicine at systems level. Students will engage in hands-on projects exploring methods of systems medicine.

Course Description:
Biomedical data in the form of images, videos or other unstructured signals are continuously collected by clinicians, such as radiologists, dermatologists or ophthalmologists, life science researchers and increasingly by ourselves with our personal devices. Tools able to distill quantitative actionable information from these data are essential to generate phenotypes, aid diagnosis, screening, treatment and automate repetitive tasks. In the era of personalized medicine and big data, they have become an urgent medical need. In this course, you will be introduced to the essential pattern recognitions techniques to build and evaluate such tools. We will be covering the basics of image/signal processing, computer vision and applied machine learning with hands on examples relevant to biomedical applications.

Course Description:
This course will provide the foundations of precision medicine and its relations with genomics by exposing trainees to the use and interpretation of genetic studies of human populations in the context of phenotypes and diseases. The course will cover principles of genetics underlying associations between genetic variants and disease susceptibility and drug response.

Course Description:
Bioinformatics play significant roles in modern genetics and genomics studies. Nearly every large-scale biology projects require a significant component of bioinformatics and computational approaches. This course provides an introduction to advanced technologies and resources in genetics, epigenetics, transcriptomics, and phenotype studies, organized as “topics”. Students will be provided with knowledge and skills to apply canonical algorithms in bioinformatics tasks, to identify potential challenges, and to develop their own analysis pipelines.


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FACULTY


Han Chen, PhD
Han Chen, PhD

Assistant Professor

Research Areas: Statistical genetics & genomics, Correlated data analysis, Statistical computing

Licong Cui, PhD
Licong Cui, PhD

Assistant Professor

Research Areas: Ontologies and terminologies, Big data analytics, Neuroinformatics

Assaf Gottlieb, PhD
Assaf Gottlieb, PhD

Assistant Professor

Research Areas: Image/Signal Processing, Machine Learning, Translational Medicine

Arif Harmanci, PhD, MS
Arif Harmanci, PhD, MS

Assistant Professor

Research Areas: Information Extraction, Functional Genomics, Genomic Privacy

Pora Kim, PhD, MS
Pora Kim, PhD, MS

Assistant Professor

Research Areas: Bioinformatics, Computational biology, Computational cancer genomics

Akdes Serin-Harmanci, PhD
Akdes Serin-Harmanci, PhD

Assistant Professor

Research Areas: Precision Medicine, Machine Learning, Genomics

Hua Tan, PhD
Hua Tan, PhD

Assistant Professor

Research Areas: Systems Biology, Computational Biology, Bioinformatics

Jianguo Wen, PhD
Jianguo Wen, PhD

Assistant Professor

Research Areas: Cancer immunotherapy, Cancer nucleic acid therapy

Hulin Wu, PhD
Hulin Wu, MS

Professor

Research Areas: Biostatistics, Computational Biology, Computational Modeling, Bioinformatics Tools

Guangming Zhang, PhD
Guangming Zhang, PhD

Assistant Professor

Research Areas: Medical Imaging Informatics, Biomechanical Analysis, Machine Learning

Weiling Zhao, PhD
Weiling Zhao, PhD

Associate Professor

Research Areas: Epigenetic gene regulation in eukaryotes, Biomarkers and target discovery, Cancer cell microenvironment

Zhongming Zhao, PhD, MS
Zhongming Zhao, PhD, MS

Professor

Research Areas: Precision Medicine, Bioinformatics, Pharmacogenomics

W. Jim Zheng, PhD
W. Jim Zheng, PhD

Professor

Research Areas: Bioinformatics, Systems biology, Genomics

Degui Zhi, PhD, MS
Degui Zhi, PhD, MS

Associate Professor

Research Areas: Bioinformatics, Statistical Genetics, Deep learning

Xiaobo Zhou, PhD
Xiaobo Zhou, PhD

Professor

Research Areas: Bioinformatics, Systems Biology, Imaging Informatics

Career Outlook

We crunched the numbers and they don't lie.

Career Outcomes for Bioinformatics and Systems Medicine
  Average Salary   Average Salary Range
Houston $157,160 $77,000 - $286,000
Texas $110,088 $58,000 - $257,000
Nationwide $143,698 $86,000 - $298,057
Positions
  • Medical Technologist
  • Bioinformatics Engineer
  • Systems Biologist
  • Research Scientist
  • Bioinformatician
  • Medical Assistant
  • Bioinformaticist
  • Bioinformatics Analyst
  • Bioinformatics Associate