Home | Columbia University Department of Systems Biology

Research
The Columbia University Department of Systems Biology brings together researchers specializing in computational biology, experimental biology, and technology development to discover how biological traits emerge from complex molecular networks.
Education
Systems biology and computational biology are becoming increasingly important disciplines in the biological sciences. Through PhD graduate education and postdoctoral training we prepare young scientists to become leaders in this exciting and rapidly growing field.
- Graduate Education
- Postdoctoral Training
Infrastructure
Our core facilities include centers for next-generation sequencing and high-throughput screening, as well as a high-performance computing center dedicated to research in molecular and systems biology.
- Columbia Genome Center
- Advanced Research Computing

News

Research News

Precision Medicine Sends Cancer for a Loop

In a tour de force of precision medicine, an international team led by two Columbia University Herbert Irving Comprehensive Cancer Center (HICCC) researchers has demonstrated the potential of a new approach to prostate cancer treatment.

Research News

Nature Publication: “Predicting Functional Effect of Missense Variants using Graph Attention Neural Networks” (Yufeng Shen, PhD)

A discussion with Yufeng Shen regarding his latest publication in Nature Machine Intelligence: “Predicting functional effect of missense variants using graph attention neural networks”.

Awards and Grants

Chaolin Zhang, PhD, receives prestigious Maximizing Investigators' Research Award from NIH/NIGMS

Chaolin Zhang will receive a prestigious Maximizing Investigators' Research Award (MIRA) (R35) of $4,313,684 over five years from NIH/NIGMS for “Complexity and evolution of splicing-regulatory networks”.

Awards and Grants

Andrea Califano, PhD, receives grant from the National Cancer Institute

Andrea Califano will receive $6,909,000 over seven years from the National Cancer Institute for “Predicting Cancer Cell Response to Endogenous and Exogenous Perturbations at the Single Cell Level”.