Concept

Neoplasm

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BIO-488: Scientific project design in translational oncology

The theme of the course is the role of inflammation in cancer. It focuses on the regulation and multifaceted functions of tumor-associated inflammatory cells, and how they promote or oppose cancer.

BIO-611: Practical - Constam Lab

During development, cell fates are governed by multiple microenvironmental cues and their integration by specific signal transduction pathways. This course focuses on imaging of mechanosensory cilia o

BIO-680: Practical - De Palma Lab

Cell heterogeneity in the tumor microenvironment.

BIOENG-399: Immunoengineering

Immunoengineering is an emerging field where engineering principles are grounded in immunology. This course provides students a broad overview of how engineering approaches can be utilized to study im

BIO-392: Oncology

This course provides a comprehensive overview of the biology of cancer, illustrating the mechanisms that cancer cells use to grow and disseminate at the expense of normal tissues and organs.

BIO-471: Cancer biology I

The course covers in detail molecular mechanisms of cancer development with emphasis on cell cycle control, genome stability, oncogenes and tumor suppressor genes.

BIO-472: Cancer biology II

The course covers in detail the interactions of cancer cells with their environment with an emphasis on tumor-angiogenesis, inflammation, adaptive and innate immunity and cancer-induced immune suppres

PHYS-450: Radiation biology, protection and applications

This is an introductory course in radiation physics that aims at providing students with a foundation in radiation protection and with information about the main applications of radioactive sources/su

ME-480: Mechanobiology: how mechanics regulate life

The objective of this course is to expose students to the fundamentals of mechanobiology. We will highlight the technologies that enable the study of living systems including mechanical manipulation a

DH-406: Machine learning for DH

This course aims to introduce the basic principles of machine learning in the context of the digital humanities. We will cover both supervised and unsupervised learning techniques, and study and imple