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Improved RNA virus understanding is critical to studying animal and plant health, and environmental processes. However, the continuous and rapid RNA virus evolution makes their identification and characterization challenging. While recent sequence-based advances have led to extensive RNA virus discovery, there is growing variation in how RNA viruses are identified, analyzed, characterized, and reported. To this end, an RdRp Summit was organized and a hybrid meeting took place in Valencia, Spain in May 2023 to convene leading experts with emphasis on early career researchers (ECRs) across diverse scientific communities. Here we synthesize key insights and recommendations and offer these as a first effort to establish a consensus framework for advancing RNA virus discovery. First, we need interoperability through standardized methodologies, data-sharing protocols, metadata provision and interdisciplinary collaborations and offer specific examples as starting points. Second, as an emergent field, we recognize the need to incorporate cutting-edge technologies and knowledge early and often to improve omic-based viral detection and annotation as novel capabilities reveal new biology. Third, we underscore the significance of ECRs in fostering international partnerships to promote inclusivity and equity in virus discovery efforts. The proposed consensus framework serves as a roadmap for the scientific community to collectively contribute to the tremendous challenge of unveiling the RNA virosphere. 

iCn3D was initially developed as a web-based 3D molecular viewer. It then evolved from visualization into a full-featured interactive structural analysis software. It became a collaborative research instrument through the sharing of permanent, shortened URLs that encapsulate not only annotated visual molecular scenes, but also all underlying data and analysis scripts in a FAIR manner. More recently, with the growth of structural databases, the need to analyze large structural datasets systematically led us to use Python scripts and convert the code to be used in Node. js scripts. We showed a few examples of Python scripts at https://github.com/ncbi/icn3d/tree/master/icn3dpython to export secondary structures or PNG images from iCn3D. Users just need to replace the URL in the Python scripts to export other annotations from iCn3D. Furthermore, any interactive iCn3D feature can be converted into a Node. js script to be run in batch mode, enabling an interactive analysis performed on one or a handful of protein complexes to be scaled up to analysis features of large ensembles of structures. Currently available Node. js analysis scripts examples are available at https://github.com/ncbi/icn3d/tree/master/icn3dnode . This development will enable ensemble analyses on growing structural databases such as AlphaFold or RoseTTAFold on one hand and Electron Microscopy on the other. In this paper, we also review new features such as DelPhi electrostatic potential, 3D view of mutations, alignment of multiple chains, assembly of multiple structures by realignment, dynamic symmetry calculation, 2D cartoons at different levels, interactive contact maps, and use of iCn3D in Jupyter Notebook as described at https://pypi.org/project/icn3dpy . 

In October 2021, 59 scientists from 14 countries and 13 U.S. states collaborated virtually in the Third Annual Baylor College of Medicine & DNANexus Structural Variation hackathon. The goal of the hackathon was to advance research on structural variants (SVs) by prototyping and iterating on open-source software. This led to nine hackathon projects focused on diverse genomics research interests, including various SV discovery and genotyping methods, SV sequence reconstruction, and clinically relevant structural variation, including SARS-CoV-2 variants. Repositories for the projects that participated in the hackathon are available at https://github.com/collaborativebioinformatics.