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The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 800 workflows registered.
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http://dx.doi.org/10.1038/s41597-025-04786-3 | DOI Listing |
J Chem Inf Model
September 2025
Department of Chemistry, Delaware State University, Dover, Delaware 19901, United States.
The calculation of the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap for chemical molecules is computationally intensive using quantum mechanics (QM) methods, while experimental determination is often costly and time-consuming. Machine Learning (ML) offers a cost-effective and rapid alternative, enabling efficient predictions of HOMO-LUMO gap values across large data sets without the need for extensive QM computations or experiments. ML models facilitate the screening of diverse molecules, providing valuable insights into complex chemical spaces and integrating seamlessly into high-throughput workflows to prioritize candidates for experimental validation.
View Article and Find Full Text PDFInt J Surg
September 2025
Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
Background: Percutaneous transthoracic lung biopsy (PTNB) guided by Computed Tomography (CT) greatly depends on the operators' skill for accuracy. This study aimed to evaluate whether three-dimensionally(3D) printed navigational templates for percutaneous transthoracic lung biopsy achieve diagnostic yield comparable to conventional computed tomography guidance.
Materials And Methods: Conducted from 1 November 2020, to 27 July 2023, this noninferiority randomized clinical trial included 159 patients with peripheral lung masses (≥30 mm).
J Chem Theory Comput
September 2025
Institute of Theoretical Chemistry, Faculty of Chemistry, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria.
We present a novel, flexible framework for electronic structure interfaces designed for nonadiabatic dynamics simulations, implemented in Python 3 using concepts of object-oriented programming. This framework streamlines the development of new interfaces by providing a reusable and extendable code base. It supports the computation of energies, gradients, various couplings─like spin-orbit couplings, nonadiabatic couplings, and transition dipole moments─and other properties for an arbitrary number of states with any multiplicities and charges.
View Article and Find Full Text PDFBackground: Transforming Clinical Practice Guideline (CPG) recommendations into computer readable language is a complex and ongoing process that requires significant resources, including time, expertise, and funds. The objective is to provide an extension of the widely used GIN-McMaster Guideline Development Checklist (GDC) and Tool for the development of computable guidelines (CGs).
Methods: Based on an outcome from the Human Centered Design (HCD) workshop hosted by the Guidelines International Network North America (GIN-NA), a team was formed to develop the checklist extension.
Adv Radiat Oncol
October 2025
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology and Radiotherapy, Augustenburger Platz 1, 13353 Berlin, Germany.
Purpose: To evaluate the impact of an optimized online adaptive radiation therapy workflow on physician involvement.
Methods And Materials: Data from a prospective phase 2 trial involving 34 prostate cancer patients treated with cone beam computed tomography (CBCT)-based online adaptive radiation therapy (62 Gy in 20 fractions) were analyzed. Manual interventions were required for 2 steps in the workflow: radiation therapy technologist review and adjustment of automatically segmented organs, guiding target segmentation, so-called "influencer," while physicians reviewed and refined the targets.