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.
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.
Research NewsMethod for Determining Protein Function Opens Opportunities for Precision Cancer Medicine
A new algorithm called VIPER offers the first method for analyzing a single tumor biopsy to identify proteins that drive cancerous activity in individual patients.
Research NewsStudy of Glioblastoma Tumor Evolution Reveals Strategies Against Advanced Disease
Genetically distinct populations of cells appear to drive malignancy before and after therapy. The findings provide insights into GBM drug resistance and how it might be overcome.
Research NewsGraduate Students Invent Technique for Reprogramming Translation
MD/PhD students Andrew Anzalone and Sakellarios Zairis engineered RNA motifs capable of inducing ribosomal frameshifting. Their method could offer new opportunities for synthetic biology.
Research NewsNew Method for Identifying Genetic Alterations that Modulate Gene Expression
The Bussemaker Lab showed that variants in cofactor genes called cQTLs can change the connectivity between transcription factors and their target genes.
EducationSystems Biology Scientists Help Expand Microbiome Research
A cross-departmental Microbiome Working Group is building bridges between computational biologists and other CUMC investigators interested in understanding how the human microbiome affects health.
Awards and GrantsBarry Honig Named ISCB Fellow
The award recognizes Honig's "seminal contributions to protein structure prediction and molecular electrostatics, and his more recent work on protein function prediction, protein-DNA recognition, and cell-cell adhesion.”
Research NewsTatonetti Lab Connects Drug Interactions to Deadly Heart Condition
Using a new data science method for analyzing observational data and validating predictions, the scientists identified several drug combinations that appear to cause a dangerous type of arrhythmia called torsades de pointes.
EducationNew Course Covers Fundamentals of High-Performance Computing
Developed by the Mailman School of Public Health in partnership with the Department of Systems Biology, it addresses practical and theoretical challenges facing scientists interested in analyzing large data sets.
In the PressWang Lab Work on Bioeconomics Featured in Wall Street Journal
A collaboration between a biologist and an economist led to a new framework for describing how bacteria exchange metabolic resources. It offers a new lens for studying microbial communities based on economic theories.
InterviewHow Genomic Data Are Changing Population Genetics
Statistical analysis of large data sets enables new kinds of insights into the forces that drive genetic variation among individuals and species. Molly Przeworski describes how the field is evolving and some of her lab's recent findings.
Research NewsShort Tandem Repeats Shown to Regulate Gene Expression
A study led by Yaniv Erlich indicates that repeating short motifs in DNA called expression STRs can expand and contract in ways that modulate nearby gene expression. They are also associated with a range of medical conditions.
Awards and GrantsFour Columbia Systems Biology Papers Named among Top Publications
The ISCB/RECOMB Conference on Regulatory and Systems Genomics has announced its top 10 papers of 2014-2015. Four of them involve investigators from the Columbia University Department of Systems Biology.
Events and Seminars
May 25, 2016 - 3:00pm
Jef Boeke(NYU Langone Medical Center)
May 23, 2016 - 4:00pm
Jeremiah Faith(Icahn School of Medicine at Mount Sinai)
Prognosis of Clinical Outcomes with Temporal Patterns and Experiences with One Class Feature Selection. IEEE/ACM Trans Comput Biol Bioinform