Ohio State Navbar

Sign In

Biomedical Informatics Courses

Go to Autumn 2017 Courses          Go to Spring 2018 Courses 


 

Autumn 2017


 
BMI 5710 - Introduction to Biomedical Informatics
Director: Courtney L. Hebert, MD, MS
Schedule: Tuesday/Thursday, 3:55 - 5:15 PM
Location: 245 Lincoln Tower
Synopsis: A survey of biomedical informatics theories and methods employed in the design, implementation and management of information systems supporting basic science, clinical and translational research, clinical care, and public health. Recommended course work in computer science, statistics, anatomy, physiology, and medical terminology.

 
Although it is not required, a background or experience with computer science, statistics, anatomy, physiology, and/or medical terminology is strongly recommended.

 

BMI 5760 – Public Health Informatics

Director: Tasneem Motiwala, PhD

Schedule: ​Online. In person sessions will be scheduled in consultation with students during the first week of the course.
Location: As scheduled with instructor
Synopsis: Introduction to the emerging and critical field of Public Health informatics. This course will highlight the history, current and future use of informatics in the public health settings, and give students an understanding of the role and broad application of informatics to promoting health and preventing disease.

 
This class will be taught primarily online. Meetings will occur only monthly in person.

 
BMI 7891 – Seminars in Biomedical Informatics

Director: Ewy Mathé, PhD
Schedule: Seminars are Fridays, 1:00 - 2:00 PM
Location: : Varies
Synopsis: ​The purpose of this course is for faculty and external guest speakers to give presentations on current BMI research and theories critical to the advancement and awareness of biomedical informatics within the healthcare and research communities. Alternate classes will consist of journal-club style discussions moderated by faculty​, in which trainees will present on their current research projects.

 
Trainees will choose a select number of seminars to attend as determined by the course director. Seminars can be chosen from either the departmental CALIBRE seminar series (Fridays, 1:00 - 2:00 PM) or from the seminar series, which brings in external speakers to present on their research (schedule is listed on departmental calendar).
​​​​​​​
​​​​​​​​​​​​This course is geared specifically towards students and trainees working or taking coursework within the BMI department.


 

BMI 8050.01 – Analysis and Applications of Genome-Scale Data

Directors: Kevin Coombes, PhD and Fuhai Li, PhD
Schedule: Tuesday/Thursday, 9:35 - 10:55 AM
Location: 245 Lincoln Tower
Synopsis: ​The goal of this course is to introduce trainees to the fundamental algorithms needed to understand and analyze genome-scale expression data sets. The course will cover three major kinds of applications. (1) Class Comparison seeks to describe which features differ between two or more known classes of patient samples (such as normal vs. tumor). Methodology includes (generalized) linear models with careful attention to the issue of multiple comparisons. (2) Class Discovery seeks to discuss the inherent structure present in a data set. The methodology includes a wide variety of techniques for clustering samples (including K-means as well as various forms of hierarchical clustering) and assessing the number of clusters and the robustness of cluster assignments. We also cover methods such as principal components analysis that help visualize the data. (3) Class Prediction seeks to discover and validate models that can accurately predict the class or the outcomes of new samples. Methods include a wide variety of machine learning and statistical methods for feature selection and model construction. We will also discuss methods for cross-validation and independent validation of predictive models. The course will include an introduction to, and hands-on experience with, the R statistical software environment and to the use of R packages that can be applied to these kinds of problems.
​​​​​​​
Course objectives: Upon completion of this course, students should have: 1) A familiarity with the fundamental algorithms used in bioinformatics; 2) An understanding of the theoretical frameworks justifying those algorithms; 3) The ability to apply those algorithms to real-world problems using R; and, 4) Critical evaluation skills that allow for the analysis and design of bioinformatics approaches to real problems in biology and medicine.

 
​​​​​​​​​​​It is expected that students have basic knowledge of the following areas: 1. Computer science principles (logic, procedural and/or object oriented programming, data structures and algorithms). 2. Statistical methods. 3. Biomedical terminology.​​

BMI 5793/8193 - Individual Studies in Biomedical Informatics

Enables upper-level undergraduate and graduate students to do research projects with faculty other than their adviser. Students should get in touch with faculty whose research aligns with their academic interests to enroll in private studies​. Graded S/U.

 

BMI 7999/8999 - Research in Biomedical Informatics

Director: Each research advisor will have an open 7999 and 8999 course each semester for their students to enroll in. Research for thesis or dissertation purposes only.

 
Prereq: Permission of instructor. Repeatable to a maximum of 99 credit hours or 20 completions. This course is graded S/U.

 

​​Spring 2018


 
 

BMI 5730 - Introduction to Bioinformatics

Director: James L. Chen, MD
Schedule: Wednesday/Thursday: 12:45 - 2:05 PM
Location: 245 Lincoln Tower
Synopsis: Introduces students to basic topics of bioinformatics including sequence analyses, proteomics, microarrays, regulatory networks, sequence and protein databases. Recommended background in molecular biology and computer science.
 
 
Prereq: Not open to students with credit for BMI 730 or IBGP 730
 
 
 
 

BMI 5740 - Introduction to Research Informatics

Director: Lang Li, PhD

Schedule: ​Online with in-person working sessions. 
Synopsis: A survey of biomedical informatics theories and methods employed in the design, implementation and management of clinical and translational research programs. 
 
Prereq: Not open to students with credit for 740.
 
 
Although it is not required, a background in computer science, statistics, anatomy, medical terminology, and/or molecular biology is recommended. 

 
BMI 5770 - Health Analytics: Data Discovery to Dissemination
Director: Timothy Huerta, PhD
Schedule: Online
Synopsis: Health Analytics is the science of analyzing health data for knowledge discovery and decision making. The sheer diversity of data types in health care settings results in what scholars call a DRIP environment: Data Rich-Information Poor. Data has become ubiquitous in healthcare settings from clinical decision making to operational/business planning; health decisions are now being made similarly. 
 
 
No programming experience is required, but students are expected to vigorously engage in their own learning and parts of courses will require that students use and adapt to tools demonstrated during class.

 

BMI 5793/8193 - Individual Studies in Biomedical Informatics

Enables upper-level undergraduate and graduate students to do research projects with faculty other than their adviser. Students should get in touch with faculty whose research aligns with their academic interests to enroll in private studies​.
 
Prereq: Permission of instructor. Repeatable to a maximum of 60 credit hours or 4 completions. This course is graded S/U.

BMI 7830 - Integrative Methods of Bioinformatics for Human Diseases​

Directors: Yan Zhang, PhD and Raghu Machiraju, PhD
Schedule: Tuesday/Thursday, 9:35 - 10:55 AM
Location: 245 Lincoln Tower
Synopsis: ​With the fast development of high throughput technologies such as microarray, next generation sequencing (NGS) and mass spectrometry and whole slide imaging (WSI), bioinformatics becomes an essential part of biomedical research on human diseases. Analysis of the large amount of high throughput data becomes the new bottleneck in many research projects. Even more required is an integrative approach that uses multiple types of data to glean biomarkers or achieve patient stratification.  The goal of this course is to let students get familiar with the commonly used bioinformatics data analysis tools via hands-on training and discussion on both classical and state-of-the-art literature. The topics include integrative analysis and visualization of both microarray and NGS data for genotyping, genomics, proteogenomics, and from WSI studies towards human diseases as well as advanced methods based on gene network inference and analysis.​

BMI 7891 – Seminars in Biomedical Informatics

Director: Ewy Mathé, PhD
Schedule: Seminars are Fridays, 1:00 - 2:00 PM
Location: Rotates
Synopsis: ​The purpose of this course is for faculty and external guest speakers to give presentations on current BMI research and theories critical to the advancement and awareness of biomedical informatics within the healthcare and research communities. Alternate classes will consist of journal-club style discussions moderated by faculty​, in which trainees will present on their current research projects.
 
 
Trainees will choose a select number of seminars to attend as determined by the course director. Seminars can be chosen from either the departmental CALIBRE seminar series (Fridays, 1:00 - 2:00 PM) or from the seminar series, which brings in external speakers to present on their research (schedule is listed on departmental calendar).
​​​​​​​
​​​​​​​​​​​​This course is geared specifically towards students and trainees working or taking coursework within the BMI department.

 

BMI 7999/8999 - Research in Biomedical Informatics

Director: Each research advisor will have an open 7999 and 8999 course each semester for their students to enroll in. Research for thesis or dissertation purposes only.
 
 
​Prereq: Permission of instructor. Repeatable to a maximum of 99 credit hours or 20 completions. This course is graded S/U.

BMI 8150 – Rigorous and Reproducible Design and Data Analysis

Director: Guy N. Brock, PhD, Kevin Coombes, PhD, and Jeffrey Parvin, MD, PhD
Schedule: Fridays 2:00 - 5:00 PM
Location: 245 Lincoln Tower
Synopsis: ​This course has the two goals of teaching students in all aspects of life sciences how to computationally analyze datasets and to inculcate best lab practices in experimental design and analysis. Students will learn the computer language R, and use R to analyze datasets from transcriptome, genome, and clinical studies. Students will develop an understanding of sources of bias and the impact of these biases on results and potential conclusions. Examples will be taken from the literature of experimental designs that were rigorous and that had built-in flaws. At the completion of the course, students will have an intermediate level of competency in R and knowledge of how to manage and analyze large datasets.​.


 

 

Summer 2017

BMI 5750 - Methods in Biomedical Informatics and Data Science

Directors: Guy Brock, PhD
Schedule: Tuesday/Thursday: 9:00 - 10:20 AM
Location: Jennings 060
Synopsis: Students will gain a familiarity with methods used during the course of the design, implementation, and evaluation of Biomedical Informatics platforms, and be able to appropriately select and combine such approaches on a project-specific basis. This course will establish an application-oriented understanding of how to appropriately use such methods in order to satisfy project-specific needs and deliverables. The objectives and outcomes for this course are:
  • Demonstrate the ability to lead project teams utilizing the aforementioned methods.
  • Demonstrate the ability to critically evaluate the outcomes generated via the appropriate use of the aforementioned methods.
  • Demonstrate the ability to critically evaluate the outcomes generated via the appropriate use of the aforementioned methods.
The following items will be discussed during the summer-long course: Intro to UML Modeling, Modeling Activities & User Needs, Modeling Driven Architecture, Procedural Programming, Defining Data Types, Managing Collections of Data, Advanced Procedural Programming, Designing and Executing Database Queries, Advanced Query Operations, Web Application Design, and Accessing Databases Using Procedural Languages.​

 

 

General Coursework and Private Studies

Bioinformatics and Computational Biology Focused

Clinical and Translational Informatics Focused

High Performance Computing and Big Data Focused

Imaging Informatics Focused

Thesis Research and Skill Competency Courses for BMI-specific Trainees


 

General Coursework and Private Studies in Biomedical Informatics

BMI 5710 - Introduction to Biomedical Informatics

A survey of biomedical informatics theories and methods employed in the design, implementation and management of information systems supporting basic science, clinical and translational research, clinical care, and public health. Recommended course work in computer science, statistics, anatomy, physiology, and medical terminology.

 
Prereq: Not open to students with credit for 710.

 
Although it is not required, a background or experience with computer science, statistics, anatomy, physiology, and/or medical terminology is strongly recommended.

 

BMI 5793/8193 - Individual Studies in Biomedical Informatics

Enables upper-level undergraduate and graduate students to do research projects with faculty other than their adviser. Students should get in touch with faculty whose research aligns with their academic interests to enroll in private studies​.

 
Prereq: Permission of instructor. Repeatable to a maximum of 60 credit hours or 4 completions. This course is graded S/U.

 

BMI 7891 - Seminars in Biomedical Informatics

Faculty and outside speakers will give presentations on current BMI research and theory. Alternate classes will consist of journal-club style discussions moderated by faculty.

 
Prereq: Permission of instructor. Not open to students with credit for 881. Repeatable to a maximum of 10 credit hours. This course is graded S/U.​

 
This course is geared specifically towards students and trainees working or taking coursework within the BMI department.

 

Bioinformatics and Computational Biology Focused Coursework


BMI 5730 - Introduction to Bioinformatics

Introduces students to basic topics of bioinformatics including sequence analyses, proteomics, microarrays, regulatory networks, sequence and protein databases. Recommended background in molecular biology and computer science.

 
Prereq: Not open to students with credit for BMI 730 or IBGP 730

 

BMI 7830 - Advanced Topics in Bioinformatics

Building on the fundamentals of bioinformatics learned in BMI 5730, this course goes into much more depth of detail in the realms of computational biology, bioinformatics, and translational bioinformatics. More details forthcoming.

 
Prereq: 5730 (730 or IBGP 705 in quarter system)

 

 

Clinical and Translational Informatics Focused Coursework

BMI 5740 - Introduction to Research Informatics

A survey of biomedical informatics theories and methods employed in the design, implementation and management of clinical and translational research programs. 

 
Prereq: Not open to students with credit for 740.

 
Although it is not required, a background or experience with computer science, statistics, anatomy, physiology, and/or medical terminology is strongly recommended.​

 

BMI 5760 - Public Health Informatics

Introduction to the emerging and critical field of Public Health informatics. This course will highlight the history, current and future use of informatics in the public health settings, and give students an understanding of the role and broad application of informatics to promoting health and preventing disease.

 
BMI 7040 - Clinical Informatics
In Development

 

BMI 7810 - Design and Methodological Approaches in Biomedical Informatics

An in-depth review of practical theories and methods employed in the design, implementation and management of complex clinical information systems.

 
Prereq: 5710 (710 in quarter system) or permission of instructor. Not open to students with credit for BMI810.​​

 

BMI 7840 - Advanced Topics in Biomedical Data Management

Instructor: Ümit V. Çatalyürek, PhD

Schedule: TBD, Autumn Semesters
Location: 245 Lincoln Tower
Synopsis: This course is an in-depth review of the latest developments in the areas of biomedical data management technologies, tools, and middlewares that support translational studies. The goal of this course is to provide an in-depth look at the expertise in the design, implementation, and management of systems used to collect, exchange, store, query, and analyze large-scale, heterogeneous biomedical data sets in order to support translational studies. 

 
Upon completion of this course, students will be able to:
  • Critically review literature on data management infrastructures
  • Evaluate and analyze existing translational informatics infrastructures
  • Design and develop new informatics infrastructure or infrastructure components to support new use cases in translational research
  • Synthesize information from a variety sources into a cohesive presentation
​Although it is not required, a background or experience with computer science, bioinformatics, imaging informatics, or clinical informatics is strongly recommended.

Imaging Informatics

BMI 5720 - Imaging Informatics

Teach students from different backgrounds the role of imaging in biomedical research, decision support and personalized medicine. Recommended familiarity with a programming language and operating system.

 
Prereq: Not open to students with credit for 720.

 

BMI 7820 - Biological and Medical Image Analysis

Provides a comprehensive review of key techniques for analyzing biomedical images, especially histological and microscopic images using an imaging informatics approach.

 
Prereq: 5710 (710 in quarter system) or permission of instructor. Not open to students with credit for 820.​

 

 

Skills Competency and Thesis Research Courses for BMI-specific Trainees​


 
Skills

BMI 5750 - Methods in Biomedical Informatics and Data Science

Students will gain a familiarity with methods used during the course of the design, implementation, and evaluation of Biomedical Informatics platforms, and be able to appropriately select and combine such approaches on a project-specific basis. This course will establish an application-oriented understanding of how to appropriately use such methods in order to satisfy project-specific needs and deliverables. The objectives and outcomes for this course are:
  • Demonstrate the ability to lead project teams utilizing the aforementioned methods.
  • Demonstrate the ability to critically evaluate the outcomes generated via the appropriate use of the aforementioned methods.
  • Demonstrate the ability to critically evaluate the outcomes generated via the appropriate use of the aforementioned methods.
The following items will be discussed during the summer-long course: Intro to UML Modeling, Modeling Activities & User Needs, Modeling Driven Architecture, Procedural Programming, Defining Data Types, Managing Collections of Data, Advanced Procedural Programming, Designing and Executing Database Queries, Advanced Query Operations, Web Application Design, and Accessing Databases Using Procedural Languages.

 

BMI 5790 - Acculturation to Medicine (In development)

This course will be used to acclimate students whose backgrounds are not as familiar with medical and healthcare settings. The course will be offered over the summer and will provide students with clinical and health care organization face time in which students will be able to see real-world application of biomedical informatics theories and principles. More details forthcoming.


Thesis and Dissertation Research​

BMI 7999 - Thesis Research in Biomedical Informatics

Instructor: Each research advisor will have an open 7999 course each semester for their students to enroll in
for thesis research purposes only.

Prereq: Permission of instructor. Repeatable to a maximum of 99 credit hours or 20 completions. This course is graded S/U.

BMI 8999 - Dissertation Research in Biomedical Informatics

Instructor: Each research advisor will have an open 8999 course each semester for their students to enroll in
for dissertation research purposes only.

Prereq: Permission of instructor. Repeatable to a maximum of 99 credit hours or 20 completions. This course is graded S/U.

 

​​​​
​​
​​​​​​​​​​​​​​