All Courses

 

BIOMEDICAL INFORMATICS (BIOINF) COURSES

(as of May 2019)

 

 

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)

Days/Times: Tuesdays/Fridays from 8:30 a.m. to 11:45 a.m.

Location: Room 430, Bridgeside Point 2 (450 Technology Drive by Hot Metal Bridge)

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. (fall term) and Xinghua Lu, M.D., Ph.D. (spring term)

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 9:00 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:  Shyam Visweswaran, M.D., Ph.D.

Term:  Spring

Days/Times:  Tuesdays/Thursdays 9:30 a.m. to 10:25 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 2103

Design & Analysis of Biomarker Studies (2 credits)

The objective of this course is to identify, describe and apply the statistical and epidemiological knowledge, tools and perspectives necessary for effectively designing, analyzing and interpreting biomarker studies (which may include diagnostic and medical tests, prognostic markers for prediction of future disease outcomes, and/or predictive markers for treatment response). The course will also focus on writing a funding proposal; students will develop a 3-4 page concept proposal as the class project.

Instructor:  Douglas Landsittel, Ph.D.

Term:  Summer (Summer 6-Week-1)

Days/Times:  Mondays/Wednesdays 9:00 a.m. to 11:05 a.m.

Location:  407A BAUM, 5607 Baum Blvd.

Prerequisites:  BIOINF 2118

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:  Roger Day, Sc.D.

Term:  Spring

Days/Times:  Tuesdays/Thursdays, 2:30 p.m. to 4:00 p.m.

Location:  407A BAUM, 5607 Baum Blvd.

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. 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:  Monday/Wednesday from 2:30 p.m.-4:00 p.m.

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:  Donald Taylor, Ph.D. and Michael Becich, M.D., Ph.D.

Term:  Spring, every odd year

Days/Times:  Thursdays, 11:00 a.m. to 12:00 p.m.

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)

Masters 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 Directed 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)

^