Subject: SYBB

Term: Spring 2023

SYBB 312R: Basic Statistics for Engineering and Science Using R Programming (102/10933)

TR 02:30-03:45 PM Jan 17-May 01

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 (103/10934)

TR 10:00-11:15 AM Jan 17-May 01

Brynjarsdottir, 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 (104/10935)

TR 02:30-03:45 PM Jan 17-May 01

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 (101/11377)

TR 01:00-02:15 PM Jan 17-May 01

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 (105/11378)

TR 01:00-02:15 PM Jan 17-May 01

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 387: Undergraduate Research in Systems Biology (100/10594)

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 (101/10610)

LaFramboise, T

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 (800/10944)

MTWRF 10:00-12:00 PM Jan 04-Jan 13

Bebek, G

This class begins and ends prior to the start of the traditional spring term.

SYBB 412: Survey of Bioinformatics: Programming for Bioinformatics (100/10551)

TR 02:30-03:45 PM Jan 17-May 01

Bebek, G

Completion of SYBB 402-Introduction to Scientific Computing or equivalent is necessary for success in this class. SYBB will be offered January 4-13, 2023 for those who have not previously taken this class.

SYBB 459: Bioinformatics for Systems Biology (100/10829)

MW 12:45-02:00 PM Jan 17-May 01

Koyuturk, M

Description of omic data (biological sequences, gene expression, protein-protein interactions, protein-DNA interactions, protein expression, metabolomics, biological ontologies), regulatory network inference, topology of regulatory networks, computational inference of protein-protein interactions, protein interaction databases, topology of protein interaction networks, module and protein complex discovery, network alignment and mining, computational models for network evolution, network-based functional inference, metabolic pathway databases, topology of metabolic pathways, flux models for analysis of metabolic networks, network integration, inference of domain-domain interactions, signaling pathway inference from protein interaction networks, network models and algorithms for disease gene identification, identification of dysregulated subnetworks network-based disease classification. Offered as CSDS 459 and SYBB 459.

SYBB 472: BioDesign (100/10501)

M 06:00-08:00 PM Jan 17-May 01

Drummond, C

Medical device innovations that would have been considered science fiction a decade ago are already producing new standards of patient care. Innovation leading to lower cost of care, minimally invasive procedures and shorter recovery times is equally important to healthcare business leaders, educators, clinicians, and policy-makers. Innovation is a driver of regional economic development and wealth creation in organizational units ranging in size from the start-up to the Fortune 500 companies. In a broader context, the pace of translational research leading to product and service innovation is highly interdisciplinary, thus, new products and services result from team efforts, marked by a systematic, structured approach to bringing new medical technologies to market and impacting patient care. In this course we examine medical technology innovations in the context of (A) addressing unmet clinical needs, (B) the process of inventing new medical devices and instruments, and (C) subsequent implementation of these advances in patient care. In short, the student learns the process of "identify, invent, implement" in the field of BioDesign. Offered as EBME 472, IIME 472 and SYBB 472.

SYBB 501: Biomedical Informatics and Systems Biology Journal Club (100/10182)

W 11:30-12:30 PM Jan 17-May 01

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 601: Systems Biology and Bioinformatics Research (100/10589)

Lodowski, D

(Credit as arranged.)

SYBB 651: Thesis M.S. (100/10287)

Bebek, G

(Credit as arranged.)

SYBB 651: Thesis M.S. (101/10590)

Lodowski, D

(Credit as arranged.)

SYBB 651: Thesis M.S. (102/10668)

LaFramboise, T

(Credit as arranged.)

SYBB 701: Dissertation Ph.D. (100/10275)

Bush, W

(Credit as arranged.)

SYBB 701: Dissertation Ph.D. (101/10276)

Lodowski, D

(Credit as arranged.)

SYBB 701: Dissertation Ph.D. (102/10277)

Chance, M

(Credit as arranged.)

SYBB 701: Dissertation Ph.D. (103/10542)

Cameron, M

(Credit as arranged.)

SYBB 701: Dissertation Ph.D. (104/10945)

Bebek, G

(Credit as arranged.)

SYBB 701: Dissertation Ph.D. (105/11123)

Cameron, C; Scott, J

(Credit as arranged.)