David Aparício

553 total citations
14 papers, 303 citations indexed

About

David Aparício is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Molecular Biology. According to data from OpenAlex, David Aparício has authored 14 papers receiving a total of 303 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Statistical and Nonlinear Physics and 3 papers in Molecular Biology. Recurrent topics in David Aparício's work include Complex Network Analysis Techniques (5 papers), Advanced Graph Neural Networks (3 papers) and Expert finding and Q&A systems (2 papers). David Aparício is often cited by papers focused on Complex Network Analysis Techniques (5 papers), Advanced Graph Neural Networks (3 papers) and Expert finding and Q&A systems (2 papers). David Aparício collaborates with scholars based in Portugal, United States and Spain. David Aparício's co-authors include Marı́a Domercq, Elena Alberdi, Alberto Pérez-Samartı́n, Olatz Pampliega, Carlos Matute, Fernando Silva, Pedro Ribeiro, Tijana Milenković, Pedro Bizarro and Juan José Álvarez Rubio and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

David Aparício

14 papers receiving 296 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David Aparício Portugal 6 96 76 70 56 54 14 303
Linyu Wei China 13 149 1.6× 61 0.8× 72 1.0× 5 0.1× 15 0.3× 34 432
Lizheng Wang China 8 81 0.8× 152 2.0× 6 0.1× 43 0.8× 15 0.3× 16 480
You Cai China 16 139 1.4× 63 0.8× 8 0.1× 35 0.6× 59 1.1× 21 575
D-S Choi United States 6 67 0.7× 7 0.1× 18 0.3× 83 1.5× 42 0.8× 8 270
Lei Niu China 14 55 0.6× 18 0.2× 8 0.1× 51 0.9× 24 0.4× 38 463
Kazuo Ushijima Japan 14 191 2.0× 103 1.4× 61 0.9× 2 0.0× 66 1.2× 75 704
Xiaojuan Sun China 16 166 1.7× 42 0.6× 9 0.1× 602 10.8× 54 1.0× 65 997
Kathryn Dempsey United States 6 89 0.9× 189 2.5× 12 0.2× 18 0.3× 8 0.1× 22 324
Fuchen Liu China 13 251 2.6× 13 0.2× 4 0.1× 61 1.1× 20 0.4× 31 538
Hengli Zhao China 19 321 3.3× 163 2.1× 54 0.8× 2 0.0× 14 0.3× 33 878

Countries citing papers authored by David Aparício

Since Specialization
Citations

This map shows the geographic impact of David Aparício's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Aparício with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Aparício more than expected).

Fields of papers citing papers by David Aparício

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Aparício. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Aparício. The network helps show where David Aparício may publish in the future.

Co-authorship network of co-authors of David Aparício

This figure shows the co-authorship network connecting the top 25 collaborators of David Aparício. A scholar is included among the top collaborators of David Aparício based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David Aparício. David Aparício is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Aparício, David, et al.. (2024). Automated test generation to evaluate tool-augmented LLMs as conversational AI agents. 54–68. 1 indexed citations
2.
3.
Aparício, David, et al.. (2023). Role of choledochotomy after mechanical lithotripsy‐related adverse event in endoscopic retrograde cholangiopancreatography. SHILAP Revista de lepidopterología. 11(4). e7248–e7248. 1 indexed citations
4.
Aparício, David, et al.. (2023). The GANfather: Controllable generation of malicious activity to improve defence systems. 133–140. 1 indexed citations
5.
Aparício, David, et al.. (2023). Synchronous mixed medullary‐papillary carcinoma and papillary multifocal carcinoma of the thyroid with cervical lymph node metastases. SHILAP Revista de lepidopterología. 11(6). e7433–e7433. 2 indexed citations
6.
Aparício, David, et al.. (2022). T5QL: Taming language models for SQL generation. 276–286. 3 indexed citations
7.
Ribeiro, Pedro, et al.. (2021). A Survey on Subgraph Counting. ACM Computing Surveys. 54(2). 1–36. 54 indexed citations
8.
Aparício, David, et al.. (2020). FOCAS. 1852–1860. 2 indexed citations
9.
Aparício, David, Pedro Ribeiro, Tijana Milenković, & Fernando Silva. (2019). Temporal network alignment via GoT-WAVE. Bioinformatics. 35(18). 3527–3529. 16 indexed citations
10.
Aparício, David, et al.. (2019). Feature-enriched author ranking in incomplete networks. Applied Network Science. 4(1). 2 indexed citations
11.
Aparício, David, Pedro Ribeiro, & Fernando Silva. (2018). Graphlet-orbit Transitions (GoT): A fingerprint for temporal network comparison. PLoS ONE. 13(10). e0205497–e0205497. 13 indexed citations
12.
Aparício, David, Pedro Ribeiro, & Fernando Silva. (2016). Extending the Applicability of Graphlets to Directed Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 14(6). 1302–1315. 11 indexed citations
13.
Aparício, David, Pedro Ribeiro, & Fernando Silva. (2014). Parallel Subgraph Counting for Multicore Architectures. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 25. 34–41. 15 indexed citations
14.
Domercq, Marı́a, Alberto Pérez-Samartı́n, David Aparício, et al.. (2009). P2X7 receptors mediate ischemic damage to oligodendrocytes. Glia. 58(6). 730–740. 181 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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