Recent Posts

• June 02, 2022

  New BioRxiv pre-print

  Marouen Ben Guebila from the Quackenbush group developed NetZoo, multilingual package that includes various tools for network reconstruction and analysis, including PyPanda, PUMA, LIONESS, and SAMBAR. NetZoo is available on github. The BioRχiv pre-print includes analyses to demonstrate the value of the integrated toolkit and can be found here. More information on the pre-print can be found here.

• June 01, 2022

  New group member

  We are very excited to announce that Ladislav Hovan has joined the lab as a postdoctoral fellow. Ladislav has a PhD in chemistry from University College London and previously did postdoctoral research in molecular dynamics at the University of Geneva, Switzerland. Ladislav's project will focus on developing approaches to model spatially resolved gene regulation.

• April 22, 2022

  New publication

  We are happy to announce that Netbooks has been published in Nature Methods! Netbooks is a hosted collection of Jupyter notebooks that provide detailed and annotated step-by-step case studies of gene regulatory network analysis. The project is led by Marouen Ben Guebila from the Quackenbush group, with contributions from Romana. More information on the publication can be found here.

• April 15, 2022

  New BioRxiv pre-print

  We have a new BioRχiv pre-print, describing our latest tool PORCUPINE and its application to leiomyosarcoma, an aggressive soft-tissue sarcoma subtype. PORCUPINE, which was developed by Tatiana, analyzes complex, genome-wide, patient-specific regulatory networks directly on the network's edge weights. It does this by combining Principal Component Analysis (PCA) with permutations to identify pathways contributing to regulatory heterogeneity in a patient population. Importantly, instead of identifying discrete subtypes, it...

• April 04, 2022

  New BioRxiv pre-print

  We have a new BioRχiv pre-print, describing our latest tool retriever and its application to cancer. Retriever, which was developed by Daniel, integrates single-cell transcriptomes with drug response profiles to recommend drugs and drug combinations that can be used to revert disease profiles towards a more healthy-like state. In an application of retriever to triple-negative transcriptomes obtained from a large single-cell breast cancer atlas, we identified a combination...