Subject: SYBB
Term: Fall 2023
SYBB 311: Technologies in Bioinformatics (100/7671)
TR 02:30-03:45 PM Aug 28-Dec 08
Bebek, G
This course introduces students to the high-throughput technologies used to collect data for bioinformatics research in various fields including genomics, proteomics, clinical informatics, imaging, and metagenomics. This class surveys the conceptual models and tools used to analyze and interpret data collected by high-throughput technologies, and the latest applications of bioinformatics in the current state of science. This course will focus on genotyping, DNA/RNA sequencing, mass spectrometry-based proteomics, phosphoproteomics, electronic health records, metagenomics and immunology. The knowledge structures that we will cover include biomedical ontologies and databases, bioinformatics tools, essential algorithms in bioinformatics and networks. There will be in class exercises and assignments covering tools for genome/proteome exploration and analysis. This is an active learning course that will provide a hands-on learning experience for the students.
Offered as SYBB 311 and SYBB 411.
SYBB 312R: Basic Statistics for Engineering and Science Using R Programming (103/7486)
TR 02:30-03:45 PM Aug 28-Dec 08
Song, D
For advanced undergraduate students in engineering, physical sciences, life sciences. Comprehensive introduction to probability models and statistical methods of analyzing data with the object of formulating statistical models and choosing appropriate methods for inference from experimental and observational data and for testing the model's validity. Balanced approach with equal emphasis on probability, fundamental concepts of statistics, point and interval estimation, hypothesis testing, analysis of variance, design of experiments, and regression modeling. Note: Credit given for only one (1) of STAT 312, STAT 312R, STAT 313 or SYBB 312R.
Offered as STAT 312R and SYBB 312R.
SYBB 312R: Basic Statistics for Engineering and Science Using R Programming (102/7550)
TR 01:00-02:15 PM Aug 28-Dec 08
Nandy, S
For advanced undergraduate students in engineering, physical sciences, life sciences. Comprehensive introduction to probability models and statistical methods of analyzing data with the object of formulating statistical models and choosing appropriate methods for inference from experimental and observational data and for testing the model's validity. Balanced approach with equal emphasis on probability, fundamental concepts of statistics, point and interval estimation, hypothesis testing, analysis of variance, design of experiments, and regression modeling. Note: Credit given for only one (1) of STAT 312, STAT 312R, STAT 313 or SYBB 312R.
Offered as STAT 312R and SYBB 312R.
SYBB 312R: Basic Statistics for Engineering and Science Using R Programming (101/7607)
TR 10:00-11:15 AM Aug 28-Dec 08
Song, D
For advanced undergraduate students in engineering, physical sciences, life sciences. Comprehensive introduction to probability models and statistical methods of analyzing data with the object of formulating statistical models and choosing appropriate methods for inference from experimental and observational data and for testing the model's validity. Balanced approach with equal emphasis on probability, fundamental concepts of statistics, point and interval estimation, hypothesis testing, analysis of variance, design of experiments, and regression modeling. Note: Credit given for only one (1) of STAT 312, STAT 312R, STAT 313 or SYBB 312R.
Offered as STAT 312R and SYBB 312R.
SYBB 312R: Basic Statistics for Engineering and Science Using R Programming (100/10795)
MW 12:45-02:00 PM Aug 28-Dec 08
Jenkinson, J
For advanced undergraduate students in engineering, physical sciences, life sciences. Comprehensive introduction to probability models and statistical methods of analyzing data with the object of formulating statistical models and choosing appropriate methods for inference from experimental and observational data and for testing the model's validity. Balanced approach with equal emphasis on probability, fundamental concepts of statistics, point and interval estimation, hypothesis testing, analysis of variance, design of experiments, and regression modeling. Note: Credit given for only one (1) of STAT 312, STAT 312R, STAT 313 or SYBB 312R.
Offered as STAT 312R and SYBB 312R.
SYBB 312R: Basic Statistics for Engineering and Science Using R Programming (104/10796)
TR 11:30-12:45 PM Aug 28-Dec 08
Mondal, A
For advanced undergraduate students in engineering, physical sciences, life sciences. Comprehensive introduction to probability models and statistical methods of analyzing data with the object of formulating statistical models and choosing appropriate methods for inference from experimental and observational data and for testing the model's validity. Balanced approach with equal emphasis on probability, fundamental concepts of statistics, point and interval estimation, hypothesis testing, analysis of variance, design of experiments, and regression modeling. Note: Credit given for only one (1) of STAT 312, STAT 312R, STAT 313 or SYBB 312R.
Offered as STAT 312R and SYBB 312R.
SYBB 387: Undergraduate Research in Systems Biology (100/7065)
Lodowski, D
This course provides students research experience in data science, proteomics, bioinformatics, and clinical informatics under the guidance of faculty affiliated with the Systems Biology and Bioinformatics program. Areas of research include production of big data at bench (cellular proteomics, structural proteomics, genomics, and interaction proteomics) and analysis of big data such as computational/statistical biology, bioinformatics tool development and clinical research informatics. A written report must be approved by the sponsor and submitted to the director of the Center for Proteomics and Bioinformatics before credit is granted.
SYBB 387: Undergraduate Research in Systems Biology (101/7066)
Chance, M
This course provides students research experience in data science, proteomics, bioinformatics, and clinical informatics under the guidance of faculty affiliated with the Systems Biology and Bioinformatics program. Areas of research include production of big data at bench (cellular proteomics, structural proteomics, genomics, and interaction proteomics) and analysis of big data such as computational/statistical biology, bioinformatics tool development and clinical research informatics. A written report must be approved by the sponsor and submitted to the director of the Center for Proteomics and Bioinformatics before credit is granted.
SYBB 387: Undergraduate Research in Systems Biology (102/7067)
Bebek, G
This course provides students research experience in data science, proteomics, bioinformatics, and clinical informatics under the guidance of faculty affiliated with the Systems Biology and Bioinformatics program. Areas of research include production of big data at bench (cellular proteomics, structural proteomics, genomics, and interaction proteomics) and analysis of big data such as computational/statistical biology, bioinformatics tool development and clinical research informatics. A written report must be approved by the sponsor and submitted to the director of the Center for Proteomics and Bioinformatics before credit is granted.
SYBB 387: Undergraduate Research in Systems Biology (103/7068)
Yang, S
This course provides students research experience in data science, proteomics, bioinformatics, and clinical informatics under the guidance of faculty affiliated with the Systems Biology and Bioinformatics program. Areas of research include production of big data at bench (cellular proteomics, structural proteomics, genomics, and interaction proteomics) and analysis of big data such as computational/statistical biology, bioinformatics tool development and clinical research informatics. A written report must be approved by the sponsor and submitted to the director of the Center for Proteomics and Bioinformatics before credit is granted.
SYBB 387: Undergraduate Research in Systems Biology (104/11448)
Cameron, C
This course provides students research experience in data science, proteomics, bioinformatics, and clinical informatics under the guidance of faculty affiliated with the Systems Biology and Bioinformatics program. Areas of research include production of big data at bench (cellular proteomics, structural proteomics, genomics, and interaction proteomics) and analysis of big data such as computational/statistical biology, bioinformatics tool development and clinical research informatics. A written report must be approved by the sponsor and submitted to the director of the Center for Proteomics and Bioinformatics before credit is granted.
SYBB 402: Introduction to Scientific Computing (100/7541)
MTRF 10:00-12:00 PM Aug 14-Aug 25
Bebek, G
This class begins and ends prior to the start of the traditional fall term.
SYBB 411: Technologies in Bioinformatics (100/7670)
TR 02:30-03:45 PM Aug 28-Dec 08
Bebek, G
This course introduces students to the high-throughput technologies used to collect data for bioinformatics research in various fields including genomics, proteomics, clinical informatics, imaging, and metagenomics. This class surveys the conceptual models and tools used to analyze and interpret data collected by high-throughput technologies, and the latest applications of bioinformatics in the current state of science. This course will focus on genotyping, DNA/RNA sequencing, mass spectrometry-based proteomics, phosphoproteomics, electronic health records, metagenomics and immunology. The knowledge structures that we will cover include biomedical ontologies and databases, bioinformatics tools, essential algorithms in bioinformatics and networks. There will be in class exercises and assignments covering tools for genome/proteome exploration and analysis. This is an active learning course that will provide a hands-on learning experience for the students.
Offered as SYBB 311 and SYBB 411.
SYBB 421: Fundamentals of Clinical Information Systems (100/7108)
T 06:00-09:00 PM Aug 28-Dec 08
Drummond, C
Technology has played a significant role in the evolution of medical science and treatment. While we often think about progress in terms of the practical application of, say, imaging to the diagnosis and monitoring of disease, technology is increasingly expected to improve the organization and delivery of healthcare services, too. Information technology plays a key role in the transformation of administrative support systems (finance and administration), clinical information systems (information to support patient care), and decision support systems (managerial decision-making). This introductory graduate course provides the student with the opportunity to gain insight and situational experience with clinical information systems (CIS). Often considered synonymous with electronic medical records, the "art" of CIS more fundamentally examines the effective use of data and information technology to assist in the migration away from paper-based systems and improve organizational performance. In this course we examine clinical information systems in the context of (A) operational and strategic information needs, (B) information technology and analytic tools for workflow design, and (C) subsequent implementation of clinical information systems in patient care. Legal and ethical issues are explored. The student learns the process of "plan, design, implement" through hands-on applications to select CIS problems, while at the same time gaining insights and understanding of the impacts placed on patients and health care providers.
Offered as EBME 473, IIME 473 and SYBB 421.
SYBB 501: Biomedical Informatics and Systems Biology Journal Club (100/6957)
W 11:30-12:30 PM Aug 28-Dec 08
Lodowski, D
The purpose of this journal club is to provide an opportunity for students to critically discuss a wide variety of informatics and systems biology topics and to present their works in progress. A wide range of informatics and systems theory approaches to conducting biomedical research will be accomplished through the guided selection of articles to be discussed during the club. Potential articles will be chosen from scientific journals including: Nature, Science, BMC Bioinformatics, BMC Systems Biology, the Journal of Bioinformatics and Computational Biology, and the Journal for Biomedical Informatics. During journal presentations, trainees will be expected to lead a discussion of the article that leads to the critical evaluation of the merit of the article and its implication for biomedical informatics and systems biology. The Journal Club will also provide a forum for trainees to present proposed, on-going, and completed research. Trainees will attend and participate in the Journal Club throughout their tenure in the program. The Journal Club will meet twice a month and each trainee will be required to present one journal article and one research in progress presentation yearly. The Journal Club will also include sessions where issues related to the responsible conduct of research are reviewed and extended.
SYBB 535: Independent Study in Biomedical Informatics (100/7085)
Bebek, G
For students pursuing MS or PhD degrees in SYBB, this course provides the opportunity for in-depth exposure to a subfield of systems biology and/or biomedical informatics. Degree-seeking students can enroll in this course prior to beginning 601 or 701 research. In conjunction with their proposed research advisor, enrolled students will undertake a self-directed study of a subfield of systems biology and/or biomedical informatics pertinent to their research area. The selected readings may also represent topics not covered by the student's coursework. The student's performance will be evaluated in an end-of-semester presentation or report at their advisor's discretion.
SYBB 555: Current Proteomics and Bioinformatics (100/11403)
F 01:00-04:00 PM Aug 28-Dec 08
Kiselar, J
This course is designed for graduate students across the university who wish to acquire a better understanding of fundamental concepts of proteomics and related bioinformatics as well as hands-on experience with techniques used in current proteomics. Lectures will cover protein/peptide separation techniques, protein mass spectrometry, and biological applications which include quantitative proteomics, protein modification proteomics, interaction proteomics, structural genomics and structural proteomics. Also, it will cover experimental design, basic statistical concept and issues related to high-dimensional data from high-throughput technologies. Laboratory portion will involve practice on the separation of proteins by two-dimensional gel electrophoresis, molecular weight measurement of proteins by mass spectrometry, peptide structural characterization by tandem mass spectrometry. It will also include bioinformatics tools for protein identification and protein-protein interaction networks. The instructors' research topics will also be discussed. Recommended preparation: CBIO 453, CBIO 455, and PQHS 431.
SYBB 601: Systems Biology and Bioinformatics Research (100/6994)
Lodowski, D
(Credit as arranged.)
SYBB 601: Systems Biology and Bioinformatics Research (101/11445)
Cameron, C
(Credit as arranged.)
SYBB 651: Thesis M.S. (100/7091)
Bebek, G
(Credit as arranged.)
SYBB 651: Thesis M.S. (101/7155)
Yang, S
(Credit as arranged.)
SYBB 651: Thesis M.S. (103/7260)
LaFramboise, T
(Credit as arranged.)
SYBB 651: Thesis M.S. (102/7261)
Lodowski, D
(Credit as arranged.)
SYBB 651: Thesis M.S. (104/11446)
Cameron, C
(Credit as arranged.)
SYBB 701: Dissertation Ph.D. (100/7042)
Lodowski, D
(Credit as arranged.)
SYBB 701: Dissertation Ph.D. (101/7043)
Chance, M
(Credit as arranged.)
SYBB 701: Dissertation Ph.D. (102/7044)
Bebek, G
(Credit as arranged.)
SYBB 701: Dissertation Ph.D. (103/7295)
Tilton, J
(Credit as arranged.)
SYBB 701: Dissertation Ph.D. (104/7306)
Bush, W
(Credit as arranged.)
SYBB 701: Dissertation Ph.D. (105/7307)
Williams, S
(Credit as arranged.)
SYBB 701: Dissertation Ph.D. (106/7599)
Cameron, M
(Credit as arranged.)
SYBB 701: Dissertation Ph.D. (107/11447)
Cameron, C
(Credit as arranged.)