All Courses

BIOMEDICAL INFORMATICS (BIOINF) COURSES
(as of January 2022)

Biomedical Informatics Colloquium (Lecture Series) (This is not a formal course.)
This course meets once each week for one hour.  The current research of Biomedical Informatics faculty and senior fellows will be presented.
Instructor:  Various speakers
Term:  Fall and Spring
Days/Times:  Fridays, 11:00 a.m. to 12:00 noon
Location:  407A BAUM, 5607 Baum Blvd.
Expected class size:  50

BIOINF 2016
Foundations of Translational Bioinformatics (3 credits)
The course goals are to gain familiarity of data produced with current biotechnologies, such as DNA arrays (e.g. SNP data), microarrays (transcriptional profiles), proteomics (mass spectrometry data), epigenomics (methylation profiles). Understand what can be done with such data to infer relations between genome, epigenome, and phenome, in order to discover molecular mechanisms of diseases, or identify biomarkers, or discover novel therapies for diseases.
Instructor: Madhavi Ganapathiraju, Ph.D.
Term:  Spring, every odd year
Days/Times: TBD
Location: 407A BAUM, 5607 Baum Blvd.
Expected class size: 10-16

BIOINF 2018
Introduction to R Programming for Scientific Research (3 credits)
Science is increasingly inter-disciplinary, and programming has become a valuable skill in many investigations. This course is designed to empower you with the ability solve scientific problems through writing computer programs. Emphasis is placed on using the R language to solve biology problems.
Instructor: Erik Wright, Ph.D.
Term:  Summer (Summer 6-week-2) of Fall Term
Days/Times: TBA
Location: Room 430, Bridgeside Point 2 (450 Technology Drive by Hot Metal Bridge)
Expected class size: 10-15

BIOINF 2019
Biomedical Data Streaming (3 credits)
In this project, students and a faculty mentor will explore data streaming technologies to implement scalable and distributed biomedical data ecosystems. In particular, students and a faculty mentor will conduct a project to learn how biomedical data processing can be enhanced with processing power of modern data-streaming infrastructures to enable continuous biomedical data acquisition and analysis.  Upon completion of this project, students will be able to understand major principles and trade-offs in design and development of a comprehensive biomedical data processing pipeline for data-intensive applications. Students will gain practical skills in selecting, applying, and developing data streaming solutions appropriate for specific data processing and data analysis tasks.
Instructor: Vladimir Zadorozhny, Ph.D.
Term:  Spring
Days/Times: TBA
Location: TBD
Expected class size: 10-15

BIOINF 2032
Biomedical Informatics Journal Club (ISSP 2083) (1 credit)
Biomedical informatics is a broad field encompassing many different research domains. What all of the domains have in common is the need to review and publish scientific papers and to give talks that present research to different audiences. The aim of this journal club is to expose students to recent research in various topics of biomedical informatics and to teach students how to critique a research article, present research from a research study; and critique a verbal presentation of research.
Instructor:  Kayhan Batmanghelich, Ph.D. and Songjian Lu, Ph.D. 
Term:  Fall and Spring
Days/Times:  Fridays, 10:00 a.m. to 11:00 a.m.
Location:  536B BAUM, 5607 Baum Blvd.
Expected class size:  35

BIOINF 2070
Foundations of Biomedical Informatics 1 (3 credits)
This course serves as an introduction to core methods and topics in biomedical informatics using the context of the Learning Health System (LHS). A LHS combines data and information managements, discovery, and application of discoveries to clinical and population health. Discussion of the challenges associated with the construction of a LHS will be used to contextualize and motivate content to be covered in the course (people, data and knowledge, and evaluation).
Instructor:  Richard Boyce, Ph.D.
Term:  Fall
Days/Times:  Tuesdays/Thursdays 9:30 a.m. to 10:25 a.m.
Location:  407A BAUM, 5607 Baum Blvd.
Expected class size: 15

BIOINF 2071
Foundations of Biomedical Informatics 2 (3 credits)
This course serves as an introduction to core methods and topics in biomedical informatics using the context of the Learning Health System (LHS). A LHS combines data and information managements, discovery, and application of discoveries to clinical and population health. Discussion of the challenges associated with the construction of a LHS will be used to contextualize and motivate content to be covered in the course (challenges and analysis and interpretation to create knowledge).
Instructor: Madhavi Ganapathiraju, Ph.D.
Term:  Spring
Days/Times:  Mondays/Wednesdays 9:30 a.m. to 10:55 a.m.
Location:  407A BAUM, 5607 Baum Blvd.
Prerequisites:  CS 1501 Algorithm Implementation and CS 2710 Foundations of Artificial Intelligence
Expected class size: 15

BIOINF 2118
Statistical Foundations of Biomedical Informatics (3 credits)
This is an introductory probability and statistics course intended primarily for biomedical informatics students. The first part of the course covers probability, including basic probability, random variables, univariate and multivariate distributions, transformations, expectation, numerical integration, and approximations. The second part of the course covers statistics, including study design, classical parametric inference, hypothesis testing, Bayesian inference, non-parametric methods, classification, ANOVA, and regression. We will use R for statistical computing and applications. Examples and applications will focus on biomedical informatics and related discipline.
Instructor: Chung-Chou Chang, Ph.D..
Term:  Spring
Days/Times:  Tuesdays/Thursdays, 8:30 a.m. to 10:00 a.m.
Location:  305A Parkvale Building
Expected class size:  10-15

BIOINF 2124
Principles of Global Health Informatics (3 credits)
This course explores challenges and opportunities in developing and supporting health information systems in developing-world settings by examining differences, and ways to both integrate and sustain systems in an appropriate way in low-resource settings, both internationally and locally. The course will review the current “state-of-the-art” in this field by looking at examples of systems currently deployed in the developing world, and explore opportunities for advancing this work through a series of case studies and hands-on exercises based on real-world scenarios.
Instructor:  Gerald Douglas, PhD
Term:  Spring, every odd year
Days/Times:  TBA
Location:  407A BAUM, 5607 Baum Blvd.
Prerequisites:  permission from instructor
Expected class size:  15-20

BIOINF 2125
Informatics and Industry (1 credits)
This class will be held once a week, for 1 hour.  The focus of the class is to provide an opportunity for students to interact with leading industry representatives and to learn techniques/tools that would enable them to market their skills in non-academic environments. We will invite speakers from various local, regional, national, and international industry relationships that we have established
Instructor:  Michael Becich, M.D., Ph.D.
Term:  Spring, every odd year
Days/Times:  TBA
Location:  407A BAUM, 5607 Baum Blvd.
Expected class size:  15-20

BIOINF 2129
Internship in Global Health Informatics (3 credits)
The Summer Internship in Global Health Informatics will be expanded to accommodate 5 students from the US. Students will travel to Malawi to study Global Health Informatics in low-resource settings alongside Malawian health and technology professionals. Students will have an opportunity to propose, design and develop a product or intervention relevant to solving a particular problem the group has identified.
Instructor:  Gerald Douglas, Ph.D.
Term:  Summer
Days/Times:  TBA
Location:  Malawi, Africa
Prerequisites:  BIOINF 2124 and permission from instructor
Expected class size:  4-5

BIOINF 2132
Special Topic Seminar in Medical Informatics (3 credits)
This course is designed for faculty to offer small groups of students a study course on a topic of mutual interest and concern in the faculty member’s area of expertise.
Instructor:  Department of Biomedical Informatics Faculty (will vary)
Term:  TBA
Days/Times:  TBA
Location:  407A BAUM, 5607 Baum Blvd.
Prerequisites:  Discuss with Instructor
Expected class size:  10
This course could be offered in any given term — check with Toni Porterfield (tls18@pitt.edu).

BIOINF 2134
Publication & Presentation in Biomedical Informatics (3 credits)
This course provides a practical overview of how to write a research manuscript and how to give a scientific talk. It is usually taken after completing the Project Course (BIOINF 2014). Students taking this course must have a completed research project that can be used to complete the course exercises. Each week, we will target a specific section of the manuscript or scientific talk. Didactic sessions describing common problems and approaches will alternate with student presentation and peer critique. The course also covers the details of the publication process. At the end of the course, a special presentation workshop gives students the opportunity to improve their talks using videotaping and debriefing methods. By the end of the course, students will have completed a research paper and a finalized colloquium presentation.
Instructor:  Harry Hochheiser, Ph.D.
Term:  Fall
Days/Times:  Tuesdays/Thursdays from 1:30 p.m. – 2:55 p.m.
Location:  407A BAUM, 5607 Baum Blvd.
Prerequisite: Completed data collection for study in research project with approval of both research advisor and course instructor.
Expected Class Size: 8

BIOINF 2480 (1-6 credits)
Master’s Thesis/Project Research

BIOINF 2990 (1-6 credits)
Masters Independent Study

BIOINF 2993 (1-6 credits)
Masters Directed Study

BIOINF 3990 (1-6 credits)
Doctoral Independent Study

BIOINF 3995 (1-6 credits)
Doctoral Independent Study

BIOINF 3998 (3 credits)
Doctoral Teaching Practicum

BIOINF 3999 (18 credits)
Doctoral Dissertation Research

NOTE:  Students registering for Full-time Dissertation Study must register under the School of Medicine’s Course Number:   FTDS 0000 (0 credits)