Computational Biology

The Computational Biology Platform of CZ Biohub SF develops computational methods, pipelines, and software that enable Biohub’s research across infectious disease and quantitative cell science.

Our Team

 

Led by Yasin Şenbabaoğlu, the Computational Biology Platform collaborates with Biohub SF researchers on multimodal data analysis, visualization, and development of methods and software that advance our understanding of health and disease. In line with CZ Biohub’s mission, we are committed to open science and freely sharing data and code with the broader scientific community.

 

 

Our Collaborations and Projects

  • We contributed to Tabula Muris and Tabula Muris Senis, the first whole-organism aging cell atlas. These datasets are bio-molecular gold mines for medical researchers because the mouse is the most-used animal model for the development of new drugs and therapies, and therefore research in this area has a global impact.
  • We collaborate with Biohub SF’s Rapid Response group on outbreak detection and analysis of metabolic pathways in pathogens to predict candidate drug targets in humans.
  • We work with Biohub SF’s Protein Sciences group to develop predictive and analytical methods for antibody repertoire specificity, which will enable the detection of disease states and the eventual development of antibody therapeutics for emerging pathogens.
  • We build software and interactive web portals to automate the design and analysis of high-throughput in vitro CRISPR knock-in experiments. We develop workflows to streamline the analysis of CRISPR-based genetic screens, and we build interactive tools to facilitate data mining.
  • We work with Biohub SF’s cell science researchers to develop interactive image analysis tools that enable comparative phenotyping of cells.

The Computational Biology team supports CZ Biohub SF’s Tabula projects, which are developing single-cell atlases across a range of species. These rich datasets are providing new insight into evolution, cell physiology, and organismal biology in health and disease.