This Figshare record provides the current executable releases of neuroVIISAS for Microsoft Windows and Linux.neuroVIISAS is a Java-based software environment for the construction, visualization, and quantitative analysis of neuroanatomical connectivity networks. The software supports the integration of anatomically defined regions and directed connections within a hierarchical neuroanatomical framework and provides a broad range of graph-theoretical analysis functions for connectome research.Available functionality includes network construction and exploration, global and local network metrics, centrality analyses, modular and hierarchical organization, connectivity similarity, network robustness analyses, cycle and recurrence analyses, and directed network motif analysis. Motif-related functionality includes efficient motif enumeration using the Kavosh algorithm as well as a separate subgraph-isomorphism-based procedure for identifying individual motif instances and anatomical node participation.The software is distributed as executable application packages for Windows and Linux. A compatible Java Runtime Environment (JRE) must be installed on the host system before neuroVIISAS can be executed.The deposited versions are provided to support reproducibility of analyses performed with neuroVIISAS and to enable independent inspection and further analysis of anatomical connectivity datasets.These software releases accompany the manuscript “Network analysis reveals recurrent circuit architectures linking the rat peripheral nervous system with central neural interfaces and peripheral targets.”
Agile methods continue to gain popularity. In particular, the Scrum method appears to be on the verge of becoming a de-facto standard in the industry, leading the so called Agile movement. While there are success stories and recommendations, there is little scientifically valid evidence of the challenges in the adoptio...
A. Marchenko, P. Abrahamsson· Agile Conference· 59 citations· ⚡11
A comprehensive taxonomy of the challenges faced when a medium-scale organization decided to adopt software platforms is provided, namely: business challenges, organizational challenges, technical challenges, and people challenges.
Yaser Ghanam, F. Maurer, P. Abrahamsson· Information and Software Tec...· 41 citations· ⚡3
It is shown that high article processing charges are not sufficiently justified by the publishers, which often lack transparency and may prevent authors from adopting OA.
D. Graziotin, Xiaofeng Wang, P. Abrahamsson· Scientometrics· 21 citations· ⚡1
MCGLPPI, a novel geometric representation learning framework that combines graph neural networks (GNNs) with the MARTINI molecular coarse-grained (CG) model to predict overall PPI properties accurately and efficiently, offers an effective and efficient solution for PPI overall property predictions.
Yang Yue, Shu Li, Yihua Cheng et al.· bioRxiv· 15 citations
PepPCBench enables a robust evaluation of PFNN-based methods and supports their continued development for peptide-protein structure prediction, and highlights the influence of peptide length, conformational flexibility, and training set similarity on prediction accuracy.
Si-Long Zhai, Huifeng Zhao, Ji-Ke Wang et al.· Journal of Chemical Informat...· 13 citations· ⚡1
Abstract Predicting properties from coordinate–category data—sets of vectors paired with categorical information—is fundamental to computational science, manifesting in materials science as predicting formation energies or elastic moduli from crystal structures. While large language models (LLMs) have increasingly been...
Nawaf Alampara, Santiago Miret, Kevin Maik Jablonka· Nature Computational Science· 13 citations
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