22 papers · ranked by Valyu relevance
Matteo Cinelli, Giovanna Ferraro, Antonio Iovanella
Networks are real systems modelled through mathematical objects made up of nodes and links arranged into peculiar and deliberate (or partially deliberate) topologies. Studying these real-world topologies allows for several properties of interest to be revealed. In real networks, nodes are also identified by a certain…
Rogini Runghen, Daniel B Stouffer, Giulio V Dalla Riva
Collecting network interaction data is difficult. Non-exhaustive sampling and complex hidden processes often result in an incomplete data set. Thus, identifying potentially present but unobserved interactions is crucial both in understanding the structure of large scale data, and in predicting how previously unseen…
Daniela Ballari, Monica Wachowicz, Miguel Angel Manso Callejo
Wireless Sensor Networks (WSNs) produce changes of status that are frequent, dynamic and unpredictable, and cannot be represented using a linear cause-effect approach. Consequently, a new approach is needed to handle these changes in order to support dynamic interoperability. Our approach is to introduce the notion of…
Aleix Bassolas, Anton Holmgren, Antoine Marot, Martin Rosvall + 1 more
'Vincenzo Nicosia'] Integrating structural information and metadata, such as gender, social status, or interests, enriches networks and enables a better understanding of the large-scale structure of complex systems. However, existing approaches to augment networks with metadata for community detection only consider…
Paul Billing Ross, Jina Song, Philip S. Tsao, Cuiping Pan
Biomedical studies have become larger in size and yielded large quantities of data, yet efficient data processing remains a challenge. Here we present Trellis, a cloud-based data and task management framework that completely automates the process from data ingestion to result presentation, while tracking data lineage…
Tatjana Welzer, Johann Eder, Vili Podgorelec, Robert Wrembel + 6 more
'Mirjana Ivanonvic' 'Johann Gamper' 'Mikołaj Morzy' 'Theodoros Tzouramanis' 'Jérôme Darmont' 'Aida Kamišalić Latifić'] Abstract. Over the past decade, the data lake concept has emerged as an alternative to data warehouses for storing and analyzing big data. A data lake allows storing data without any predefined schema.…
Zhengxian Wei, Min Song, Guisheng Yin, Houbing Song + 3 more
'Xuefei Ma' 'Albert M. K. Cheng'] Underwater wireless sensor networks (UWSNs) represent an area of increasing research interest, as data storage, discovery, and query of UWSNs are always challenging issues. In this paper, a data access based on a guide map (DAGM) method is proposed for UWSNs. In DAGM, the metadata…
Andrey Sobolev, Adrian Stoewer, Michael Pereira, Christian J. Kellner + 3 more
'Christian J. Kellner' 'Christian Garbers' 'Philipp L. Rautenberg' 'Thomas Wachtler'] Structured, efficient, and secure storage of experimental data and associated meta-information constitutes one of the most pressing technical challenges in modern neuroscience, and does so particularly in electrophysiology. The German…
Sepehr Sadoughi, Nikolay Yakovets, George Fletcher
and Reification Authors: ['Sepehr Sadoughi' 'Nikolay Yakovets' 'George Fletcher'] The ISO standard Property Graph model has become increasingly popular for representing complex, interconnected data. However, it lacks native support for querying metadata and reification, which limits its abilities to deal with the…
Darko Hric, Tiago P. Peixoto, Santo Fortunato
The empirical validation of community detection methods is often based on available annotations on the nodes that serve as putative indicators of the large-scale network structure. Most often, the suitability of the annotations as topological descriptors itself is not assessed, and without this it is not possible to…
Taha Mohseni Ahooyi, Benjamin Stear, J. Alan Simmons, Vincent T. Metzger + 40 more
The Data Distillery Knowledge Graph (DDKG) is a framework for semantic integration and querying of biomedical data across domains. Built for the NIH Common Fund Data Ecosystem, it supports translational research by linking clinical and experimental datasets in a unified graph model. Clinical standards such as ICD-10…
Authors not listed
Effective visualization of complex synthesis routes is critical for computeraided synthesis planning (CASP), yet current solutions are limited in scope, integration flexibility, and chemical intuition. We introduce RouteWise, a versatile, containerized web application designed to address these unmet needs. Its modular…
Lena Mangold, Camille Roth
Network analysis is often enriched by including an examination of node metadata. In the context of understanding the mesoscale of networks it is often assumed that node groups based on metadata and node groups based on connectivity patterns are intrinsically linked. This assumption is increasingly being challenged…
Spyros Blanas, Suren Byna
Advances in technology and computing hardware are enabling scientists from all areas of science to produce massive amounts of data using large-scale simulations or observational facilities. In this era of data deluge, effective coordination between the data production and the analysis phases hinges on the availability…
Chunyu Ma, Shaopeng Liu, David Koslicki
The sheer volume and variety of genomic content within microbial communities makes metagenomics a field rich in biomedical knowledge. To traverse these complex communities and their vast unknowns, metagenomic studies often depend on distinct reference databases, such as the Genome Taxonomy Database (GTDB), the Kyoto…
Pável Vázquez, Kayoko Shoji, Steffen Nøvik, Stefan Krauß + 1 more
'Simon Rayner'] GADDS: Global Accessible Distribution Data Sharing Machine: physical hardware that can execute commands. Node: machine in a network. Cluster: group of machines. Organization: group of nodes sharing a domain name. Domain: network address. Channel: permissioned network where organizations communicate.…
Fritz Lekschas, Nils Gehlenborg
The number of data sets in biomedical repositories has grown rapidly over the past decade, providing scientists in fields like genomics and other areas of high-throughput biology with tremendous opportunities to re-use data. Scientists are able to test hypotheses computationally instead of generating their own data, to…
Daniel S. Himmelstein, Michael Zietz, Vincent Rubinetti, Kyle Kloster + 8 more
Hetnets, short for “heterogeneous networks”, contain multiple node and relationship types and offer a way to encode biomedical knowledge. One such example, Hetionet connects 11 types of nodes — including genes, diseases, drugs, pathways, and anatomical structures — with over 2 million edges of 24 types. Previous work…
Michael Statt, Brian Rohr, Dan Guevarra, Ja'Nya Breeden + 2 more
Materials knowledge is inherently hierarchical. While high-level descriptors such as composition and structure are valuable for contextualizing materials data, the data must ultimately be considered in the context of its low-level acquisition details. Graph databases offer an opportunity to represent hierarchical…
Damien M. O’Halloran
Background: Node.js is an open-source and cross-platform environment that provides a JavaScript codebase for back-end server-side applications. JavaScript has been used to develop very fast, and user-friendly front-end tools for bioinformatic and phylogenetic analyses. However, no such toolkits are available using…
Authors not listed
The discoverability and reusability of data is critical for machine learning to drive new discovery in the chemical sciences, and the ‘FAIR Guiding Principles for scientific data management and stewardship’ provide a measurable set of guidelines that can be used to ensure the accessibility of reusable data. We…
Authors not listed
Natural language processing with the help of large language models such as ChatGPT has become ubiquitous in many software applications and allows users to interact even with complex hardware or software in an intuitive way. The recent concepts of Self-Driving Labs and Material Acceleration Platforms stand to benefit…