Category: Graduate

Credit Hours: 3
Day/Time:
Location: WK 321, Walker Plaza Building, 719 Indiana Avenue, Indianapolis, IN 46202 [map]
May have some guest lectures, not necessarily in the same room and time
First Class:
Website:
Instructor: Sarath Chandra Janga, Ph.D., Assistant Professor, Bioinformatics
Office Hours: Tuesdays and Thursdays, 11 am–12 pm or by Appointment
Office: WK 309, Walker Plaza Building, 719 Indiana Avenue, Indianapolis, IN 46202 [map]
Phone: (317) 278-4147 (Office)
Email: jangalab@iupui.edu
Website: http://www.iupui.edu/~jangalab/
Prerequisites:

Description

Translational medicine (TM) attempts to bring clinical and biomedical research practices and outcomes to patient care (“bench to bedside”). Informaticians have assisted clinicians and biomedical scientists in dealing with the large volumes of data derived from various high-throughput methodologies, developing disease models and drug design. This course will focus on the complexities of low, medium and high-throughput applications in translational medicine and train the students in solving translational medicine data management problems employing various informatics frameworks.

Credit Hours: 3
Day/Time: Mondays, 6–8:30 pm
Location: IT 271, 535 West Michigan Street, Indianapolis, IN 46202 [map]
May have some guest lectures, not necessarily in the same room and time
First Class:
Website:
Instructor: Sarath Chandra Janga, Ph.D., Assistant Professor, Bioinformatics
Office Hours: Tuesdays and Thursdays, 11 am–12 pm or by Appointment
Office: WK 309, Walker Plaza Building, 719 Indiana Avenue, Indianapolis, IN 46202 [map]
Phone: (317) 278-4147 (Office)
Email: jangalab@iupui.edu
Website: http://www.iupui.edu/~jangalab/
Prerequisites:

Description

In this course, we will cover the advanced concepts of genomics, molecular and systems biology and explore different (computational) approaches for analyzing high-throughput datasets resulting from these respective fields. This will be achieved by giving a biology background to motivate a computational need/task with most assignments involving a computational exercise to handle such datasets or to implement relevant algorithms. At the end of the course, you should be able to describe solutions (preferably elegant) to address a wide range of basic biological and biomedical problems.

The course is aimed at students who have some experience in programming (or are willing to learn it at a quick pace) and are willing to apply these skills in omics settings using a variety of programming languages/tools.

The instructor will give a detailed introduction to each of the areas below and introduce commonly used applications in bioinformatics/systems biology in the first 9-10 weeks. Then the students will be asked to present recent articles published in the last 2 years (each student has to present a paper or two) along with details of their project work (each student chooses a particular theme/problem related to the paper/s presented) and submit a project report on the research problem (project work) they addressed, towards the end of the semester.