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Department of Bioinformatics and Systems Medicine

Bioinformatics and Systems Medicine focuses on molecular, cellular, and organ levels of the human biological system. Students and researchers with a focus on this domain develop and apply computational methods and tools for the study of genes, proteins, cells, biological networks, and images and integrate them with clinical and population data to address fundamental challenges in patient care. Topics include Precision Medicine, Genomics, Pharmacogenetics, Genetic Sequencing and Analysis (Single Cell, Exome, Whole Genome, etc.), Proteomics, Imaging Informatics, Biological Network, Smart Clinical Trials, Multimodality Modeling, and the integration of genotyping and phenotyping for patient care. Students and researchers in Bioinformatics and Systems Medicine work closely with those in Health Data Science and AI and Clinical and Health Informatics.

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). Students are admitted to the school, not a specific department, so that they can obtain a broad and comprehensive education experience while specializing with an in-depth training in the three areas offered by the Department of Health Data Science and Artificial Intelligence, Department of Clinical and Health Informatics, and Department of Bioinformatics and Systems Medicine.

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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.

  • BMI 5330 - Introduction to Bioinformatics

    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.

  • BMI 5331 - Foundations of Pharmacogenomics

    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.

  • BMI 5332 - Statistical Analysis of Genomic Data

    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.

  • BMI 5333 - Systems Medicine: Principles and Practice

    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.

  • BMI 6331 - Medical Imaging and Signal Pattern Recognition

    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.

  • BMI 6332 - Genomics and Precision Medicine

    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.

  • BMI 6333 - Current Topics in Genomics

    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.

  • BMI 7151 - Seminar in Precision Medicine

    Course Description:

    Seminar in Precision Medicine will introduce and discuss recent advances, frontier technologies, case studies, and future direction in precision medicine. The topics cover precision medicine, bioinformatics, systems biology, pharmacogenomics, genetics, genomic medicine, study design, methodologies and computational tools. Students enrolled in the course for credit are required to give a seminar presentation, attend at least 80% of the weekly seminars, and fill out evaluation forms. Each student seminar must be supervised by a faculty member (not necessarily the student's advisor). The faculty member will work with students to ensure that the seminars are both appropriate and interesting for the audience.

  • BMI 7320 - Topics for Artificial Intelligence in Cancer Discovery

    Course Description:

    This course introduces a few common deep learning architectures (e.g., convolution neural network, graph neural network, recurrent neural network and autoencoder) to the students who are new to AI. The primary aim of this course is to flatten the learning curve in AI and to provide students with a basis for further implementation of more complex models using enormous real-world data, especially in cancer research.

    This course will have a combination of lectures and demos to guarantee the students will have adequate first-hand experience with course concepts and with the opportunity to explore AI methods implemented in cancer research. We also include one tutorial of basic programming skills with Python and its machine learning libraries.

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FACULTY


Hongfang Liu, PhD
Hongfang Liu, PhD

Professor

Interim Chair, Department of Bioinformatics and Systems Medicine

Xiangning Chen, PhD, MS
Xiangning Chen, PhD, MS

Professor

Research Areas: Genetics and Genomics Study of Psychiatric Disorders, Biomarker Discovery, Disease Risk-Modeling, Evaluation and Prediction

Yulin Dai, PhD
Yulin Dai, PhD

Assistant Professor

Research Areas: Tissue/Cell type specificity in complex disease, Multi-Omics Data Integration


Wankun Deng, PhD
Wankun Deng, PhD

Assistant Professor

Research Areas: Machine Learning, Data Mining, and Transcriptomics and Proteomics


Luca Giancardo, PhD
Luca Giancardo, PhD

Associate Professor

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

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

Sayed-Rzgar Hosseini, PhD
Sayed-Rzgar Hosseini, PhD

Assistant Professor

Research Areas: Computational Systems Biology, Precision Cancer Medicine, Statistical Bioinformatics

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

Assistant Professor

Research Areas: Bioinformatics, Precision Medicine, Biological Database

Hui Li, PhD
Hui Li, PhD

Assistant Professor

Research Areas: Image processing, Clinical and Translational Research, Clinical Natural Language Processing (NLP) ...

Zhao Li, PhD
Zhao Li, PhD

Assistant Professor

Research Areas: Biomedical data mining, Biomedical NLP, and Big data analytics

Zhao Li, PhD
Ardalan Naseri, PhD

Assistant Professor

Research Areas: Algorithms, Computational Biology, Bioinformatics, and Population Genetics

Jinlian Wang, PhD
Jinlian Wang, PhD

Assistant Professor

Research Areas: Bioinformatics, Machine learning, Artificial Intelligence, Deep Learning, Rare disorders NGS data annotation ...

Jianguo Wen, PhD
Jianguo Wen, PhD

Assistant Professor

Research Areas: Cancer immunotherapy, Cancer Nucleic Acid Therapy

Hulin Wu, PhD, MS
Hulin Wu, PhD, MS

Professor

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

Lei You, PhD
Lei You, PhD

Assistant Professor

Research Areas: Image Processing, Deep Learning, Human-Machine Interaction

Guangming Zhang, PhD
Guangming Zhang, PhD

Assistant Professor

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

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

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