June 28, 2024. Dr. Sarabipour’s article on the benefits of preprints for the academic enterprise has been cited on the White House Office of Science and Technology Policy (OSTP) report to the U.S. Congress on financial mechanisms for open access publishing of federally funded research. The report details developments in the open access publishing landscape including potential and anticipated impacts of a Memorandum to Executive Departments and Agencies titled, “Ensuring Free, Immediate, and Equitable Access to Federally Funded Research” on federal research investments, research integrity, and the peer review process.

09-07-2023. Congratulations to the Yu lab on a new publication, Point-supervised Single-cell Segmentation via Collaborative Knowledge Sharing. The article describes a new deep learning algorithm for training convolutional neural nets (CNN) to perform the single-cell segmentation task using point-label or no human label. (Yu J. Point-supervised Single-cell Segmentation via Collaborative Knowledge Sharing. IEEE Trans Med Imaging. 2023 Sep 7;PP. doi: 10.1109/TMI.2023.3312988. Epub ahead of print. PMID: 37676808.)

06-16-2023. Dr. Eran Agmon has published a pioneering paper that explores antibiotic resistance in E. coli by implementing a multiscale whole-cell model. Developed with Dr. Agmon‘s model integration software, Vivarium, the study encompasses single-cell dynamics and population-level heterogeneity to provide a mechanistic understanding of antibiotic resistance, furthering the fight against the rise of multidrug-resistant bacterial strains.

Skalnik, C. J., Cheah, S. Y., Yang, M. Y., Wolff, M. B., Spangler, R. K., … Agmon, E., & Covert, M. W. (2023). Whole-cell modeling of E. coli colonies enables quantification of single-cell heterogeneity in antibiotic responses. PLOS Computational Biology, 19(6), e1011232.

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1011232

06-01-2023. Drs. Michael Blinov and Leslie Loew together with a former student Aniruddha Chattaraj (currently a PostDoc at Harvard) published a paper introducing a novel software, MolClustPy, to characterize and visualize the distribution of cluster sizes, molecular composition, and bonds across biomolecular clusters.

Chattaraj, A., Nalagandla, I., Loew, L. M., & Blinov, M. L. (2023). MolClustPy: a Python package to characterize multivalent biomolecular clusters. Bioinformatics, 39(6), btad385.

https://academic.oup.com/bioinformatics/article/39/6/btad385/7199581

Dr. Vera-Licona will be giving an invited talk on Model Checking during the thematic workshop on networks and biological model inference in the context of the CNRS Bioss working group on symbolic systems biology (https://www.bioss-cnrs.fr). The aim is to gather people working on this topic to present recent results and discuss challenges and perspectives. The workshop will take place on July 3-4 2023 at CIRM in Marseille, France