14 papers · ranked by Valyu relevance
Saleh Amareen, Arif Rahman, Sazzadur Rahaman, Amiangshu Bosu
GraphQL provides a schema-based, strongly typed query language that enables highly efficient client-server communication. This paper introduces GraphQLify, an automated framework designed to migrate existing REST APIs to GraphQL. Unlike prior approaches that rely on relational databases, resource description frameworks…
Johannes Graf
Graph databases offer unparalleled flexibility for managing interconnected data, yet the lack of strict schema enforcement often leads to runtime uncertainties and complex query development. This paper introduces Graphify, an end-to-end framework that enables developers to visually model graph data schemas and…
Shaolun Liu, Sina Marefat, O. D. Tsai, Yu Chen + 3 more
GraphQL's flexible query model and nested data dependencies expose APIs to complex, context-dependent vulnerabilities that are difficult to uncover using conventional testing tools. Existing fuzzers either rely on random payload generation or rigid mutation heuristics, failing to adapt to the dynamic structures of…
Lars Schimmelpfennig, Matthew Cannon, Quentin Cody, Joshua McMichael + 6 more
Title: Summary: The druggable genome encompasses the genes that are known or predicted to interact with drugs. The Drug-Gene Interaction Database (DGIdb) provides an integrated resource for discovering and contextualizing these interactions, supporting a broad range of research and clinical applications. DGIdb is…
Hadar Rotschield, Liat Peterfreund
SQL/PGQ is the emerging ISO standard for querying property graphs defined as views over relational data. We formalize its expressive power across three fragments: the read-only core, the read-write extension, and an extended variant with richer view definitions. Our results show that graph creation plays a central role…
Zhen Xie, Wenzhe Hou, Feiyang Wu, Hao Xu + 1 more
Graphs are a representative type of fundamental data structures. They are capable of representing complex association relationships in diverse domains. For large-scale graph processing, the stream graphs have become efficient tools to process dynamically evolving graph data. When processing stream graphs, the subgraph…
Matthias Ley, Kinga Kęska-Izworska, Lucas Fillinger, Samuel M Walter + 8 more
Biological network visualization together with graph-based analyses are key techniques in systems biology and network medicine to detect patterns and generate hypotheses regarding disease pathobiology, drug target identification, biomarker prioritization, and digital drug discovery. Network representations provide an…
Yuxuan Xu
Open neuroscience repositories support reuse by making datasets accessible, but event level reuse also depends on whether task and stimulus annotations can be interpreted by software. I audited public latest OpenNeuro BIDS snapshots using public GraphQL metadata, recursive file trees, small events.json sidecars, and…
Authors not listed
Pharmacophores are widely used to describe protein-ligand interactions, and the Grids of Pharmacophore Interaction Fields (GRAIL) method extends this concept by representing binding pockets as interpretable sets of interaction type-specific pharmacophoric maps. In this work, we propose a hybrid framework for binding…
Marcelo Arenas, Leonid Libkin, Wim Martens
A major shortcoming of the recently standardized graph query languages GQL and SQL/PGQ is their lack of compositionality. Given the importance of these languages in querying knowledge graphs, we address this shortcoming and propose both theoretical solutions and a path to adding them to the new standards. The highlight…
Authors not listed
Computational methods for predictive modeling have been increasingly utilized in the early stages of drug discovery to supplement high-throughput screening. The advent of highly efficient and complex machine learning architectures necessitates new methods of collating the plethora of topological, geometrical, and…
Phanindra Reddy Madduru, Bijo Thomas
This paper proposes a preprocessing framework for optimizing large-scale graph database ingestion through intelligent edge filtering based on value ranking. We combine adapted PageRank algorithms with business-specific metrics and edge type importance to evaluate and rank edges, enabling selective retention of…
Herbert George, Gowtham Baratam, DS Dhyaneesh
Drug repurposing has become a crucial strategy to accelerate drug discovery and reduce development costs. Conventional drug development is time consuming and expensive; it often takes more than a decade and billions of dollars to bring a new drug into the market. To address these challenges, this work puts forward a…
Akira R. Kinjo, Yasunori Yamamoto, Samuel Bustamante-Larriet, Jose-Emilio Labra-Gayo + 1 more
Querying the RDF Portal knowledge graph maintained by DBCLS—which aggregates approximately 60 life-science databases—requires proficiency in both SPARQL and database-specific RDF schemas, placing this resource beyond the reach of most researchers. Large Language Models (LLMs) can, in principle, translate…