Month: May 2024

bnglViz software developed by Blinov’s lab is published in Bioinformatics

Posted on by Mikhail Blinov

May 30, 2024 The Blinov Lab published a new software tool bnglViz, an online platform for visualizing rule-based models in BioNetGen language (BNGL) as graphical cartoons, empowering researchers to grasp the nuances of rule-based models swiftly and efficiently, and making the exploration of complex biological systems more accessible than ever before. https://doi.org/10.1093/bioinformatics/btae351 

Dr. Sarabipour at the NINDS Approaches to Prevent Publication Bias Workshop

Posted on by Mikhail Blinov

May 20-21, 2024.  Dr. Sarabipour spoke as an invited panelist at the National Institute of Neurological Disorders and Stroke’s (NINDS) Novel Approaches to Preventing Publication Bias Workshop in Bethesda, Maryland. This workshop brought together a diverse cross-section of individuals who promote scientific rigor and transparency and are invested in mitigating publication bias. Dr. Sarabipour spoke on her work highlighting the benefits of open science and preprinting and role of preprints in the faculty job search process.

NIH P41 grant for Center for Reproducible Biomedical Modeling

Posted on by Mikhail Blinov

May 15, 2024  Ion Moraru and Eran Agmon were awarded a renewed NIH P41 grant to extend Biosimulations (https://biosimulations.org) with multi-algorithmic composition through the NIH Center for Reproducible Biomedical Modeling. Nearly $6 million from the National Institute of Biomedical Imaging and Bioengineering will support this collaborative project, involving leading investigators such as Elebeoba May (University of Wisconsin-Madison), David Nickerson (University of Auckland), John Gennari (UW Department of Biomedical Informatics and Medical Education), and Joseph Hellerstein (UW eScience Institute), with Herbert M. Sauro (UW Department of Bioengineering) as director. The center aims to enhance multi-scale and integrative computer models of disease and non-disease states, making them credible, understandable, reproducible, and extensible.