Overview of the field of biomedical informatics,combining perspectives from medicine, computer science, and social science. Use of computers and information in health care and the biomedical sciences, covering specific applications and general methods, current issues, capabilities and limitations of biomedical informatics.
This course is customized for 1st-year PhD and MA students in the biomedical informatics graduate program and also
open to other interested students at Columbia. It provides a detailed overview of symbolic methods.
.
This course aims to provide a comprehensive understanding of computational approaches in the microbiome field. Through the discussion of state-of-the-art methods and algorithms, we will review key methodological challenges in microbiome data analysis, such as taxonomic inference, compositional data analysis, reference-free metagenomic reconstructions, and applications of machine learning. To understand the role of these challenges and methods in the wider context of biological research in the field, we will discuss major high-impact controversies among researchers as well as impactful areas of clinical and biological investigations. The course will comprise of lectures, short weekly assignments, a midterm, and a final presentation. Each week will comprise a lecture on computational methods and another on clinical impact and controversies. By the end of the course, students will have a deep understanding of the current state of microbiome research and potential future directions, and will be able to dissect and analyze different computational approaches for their advantages and disadvantages in the context of progress in the field.
This course is suitable for: biology-oriented students who wish to obtain a better understanding of computational challenges in the field; CS/engineering students who wish to get exposure to applications of computational methods in biology; microbiome enthusiasts.
Prerequisites:
A prior introductory class in mathematics or statistics.
Prerequisite: open to public. Presentations by medical informatics faculty and invited international speakers in medical informatics, computer science, nursing informatics, library science, and related fields.
Research in medical informatics under the direction of a faculty adviser.
Research in medical informatics under the direction of a faculty adviser.
Prerequisite: approval of adviser. Readings on topics in medical informatics under the direction of a faculty adviser.
Prerequisite: instructors permission. Participation in medical informatics educational activities under the direction of a faculty adviser.
Prerequisite: completion of all M.Phil. requirements, and approval of a research proposal by the supervising faculty adviser.
Prerequisite: completion of all M.Phil. requirements. Ph.D. candidates may be required to register for this course every term during the preparation of the dissertation.