David Willé

1.7k total citations
31 papers, 970 citations indexed

About

David Willé is a scholar working on Information Systems, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, David Willé has authored 31 papers receiving a total of 970 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Information Systems, 11 papers in Artificial Intelligence and 9 papers in Molecular Biology. Recurrent topics in David Willé's work include Software Engineering Research (11 papers), Advanced Software Engineering Methodologies (11 papers) and Service-Oriented Architecture and Web Services (4 papers). David Willé is often cited by papers focused on Software Engineering Research (11 papers), Advanced Software Engineering Methodologies (11 papers) and Service-Oriented Architecture and Web Services (4 papers). David Willé collaborates with scholars based in Germany, United Kingdom and United States. David Willé's co-authors include Edward T. Bullmore, Ina Schaefer, Sandro Schulze, Sam Miller, Enrico Domenici, Jorge Esparza-Gordillo, Astrid McKeown, Claire Brittain, Paola G. Bronson and Emilio Merlo‐Pich and has published in prestigious journals such as Nature Communications, Nature Genetics and PLoS ONE.

In The Last Decade

David Willé

30 papers receiving 951 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 Willé Germany 15 307 166 153 146 131 31 970
Melinda Tóth Hungary 15 263 0.9× 48 0.3× 18 0.1× 57 0.4× 26 0.2× 51 631
Patrick J. Gannon United States 13 327 1.1× 63 0.4× 34 0.2× 57 0.4× 35 0.3× 19 955
Joshua C. Snyder United States 21 606 2.0× 102 0.6× 24 0.2× 41 0.3× 7 0.1× 40 1.2k
Di Zhong China 23 640 2.1× 246 1.5× 31 0.2× 13 0.1× 18 0.1× 72 1.5k
Zijing Huang China 15 345 1.1× 161 1.0× 28 0.2× 52 0.4× 144 1.1× 61 1.0k
John M. Dawes United Kingdom 18 366 1.2× 83 0.5× 9 0.1× 16 0.1× 37 0.3× 32 1.4k
Sevinç Bayram United States 18 98 0.3× 92 0.6× 42 0.3× 89 0.6× 54 0.4× 23 1.5k
Xiuwu Zhang United States 23 753 2.5× 138 0.8× 32 0.2× 40 0.3× 33 0.3× 49 1.4k
Mario Lauria Italy 18 358 1.2× 35 0.2× 43 0.3× 126 0.9× 33 0.3× 57 1.2k

Countries citing papers authored by David Willé

Since Specialization
Citations

This map shows the geographic impact of David Willé'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 Willé with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Willé more than expected).

Fields of papers citing papers by David Willé

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Willé. 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 Willé. The network helps show where David Willé may publish in the future.

Co-authorship network of co-authors of David Willé

This figure shows the co-authorship network connecting the top 25 collaborators of David Willé. A scholar is included among the top collaborators of David Willé 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 Willé. David Willé is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lewis, Alan J., et al.. (2025). Generation and preclinical assessment of depemokimab, an enhanced IL-5 antagonist monoclonal antibody. Heliyon. 12(1). e44247–e44247. 1 indexed citations
2.
Soskic, Blagoje, Eddie Cano-Gamez, Deborah J. Smyth, et al.. (2022). Immune disease risk variants regulate gene expression dynamics during CD4+ T cell activation. Nature Genetics. 54(6). 817–826. 60 indexed citations
3.
Cano-Gamez, Eddie, Blagoje Soskic, Theodoros I. Roumeliotis, et al.. (2020). Single-cell transcriptomics identifies an effectorness gradient shaping the response of CD4+ T cells to cytokines. Nature Communications. 11(1). 1801–1801. 145 indexed citations
4.
Picart‐Armada, Sergio, et al.. (2019). Benchmarking network propagation methods for disease gene identification. PLoS Computational Biology. 15(9). e1007276–e1007276. 34 indexed citations
5.
Soskic, Blagoje, Eddie Cano-Gamez, Deborah J. Smyth, et al.. (2019). Chromatin activity at GWAS loci identifies T cell states driving complex immune diseases. Nature Genetics. 51(10). 1486–1493. 63 indexed citations
6.
Willé, David, et al.. (2018). Reducing variability of technically related software systems in large-scale IT landscapes. 224–235. 1 indexed citations
7.
Iorio, Francesco, Luz García‐Alonso, Jonathan Brammeld, et al.. (2018). Pathway-based dissection of the genomic heterogeneity of cancer hallmarks’ acquisition with SLAPenrich. Scientific Reports. 8(1). 6713–6713. 17 indexed citations
8.
Willé, David, Önder Babur, Loek Cleophas, et al.. (2018). Improving custom-tailored variability mining using outlier and cluster detection. Science of Computer Programming. 163. 62–84. 12 indexed citations
9.
Willé, David, Sandro Schulze, Christoph Seidl, & Ina Schaefer. (2016). Custom-Tailored Variability Mining for Block-Based Languages. 271–282. 15 indexed citations
10.
Willé, David, Sandro Schulze, & Ina Schaefer. (2016). Variability mining of state charts. 63–73. 8 indexed citations
11.
Ripley, Tamzin L., Sandra Sanchez‐Roige, Edward T. Bullmore, et al.. (2015). The novel mu-opioid antagonist, GSK1521498, reduces ethanol consumption in C57BL/6J mice. Psychopharmacology. 232(18). 3431–3441. 13 indexed citations
12.
Teo, James, Graham Bentley, Philip Lawrence, et al.. (2014). Late cortical plasticity in motor and auditory cortex: role of met-allele in BDNF Val66Met polymorphism. The International Journal of Neuropsychopharmacology. 17(5). 705–713. 31 indexed citations
13.
Willé, David, et al.. (2014). Family model mining for function block diagrams in automation software. 36–43. 31 indexed citations
14.
Schaefer, Ina, et al.. (2013). Automatische Synthese von Familienmodellen durch Analyse von block-basierten Funktionsmodellen.. GI-Jahrestagung. 2443–2457. 2 indexed citations
15.
Giuliano, Chiara, Trevor W. Robbins, David Willé, Edward T. Bullmore, & Barry J. Everitt. (2013). Attenuation of cocaine and heroin seeking by μ-opioid receptor antagonism. Psychopharmacology. 227(1). 137–147. 44 indexed citations
16.
Willé, David, et al.. (2013). Interface variability in family model mining. 44–51. 31 indexed citations
17.
Bosnar, Martina, Francesca Michielin, David Willé, et al.. (2011). Macrolide antibiotics broadly and distinctively inhibit cytokine and chemokine production by COPD sputum cells in vitro. Pharmacological Research. 63(5). 389–397. 60 indexed citations
18.
Domenici, Enrico, David Willé, Federica Tozzi, et al.. (2010). Plasma Protein Biomarkers for Depression and Schizophrenia by Multi Analyte Profiling of Case-Control Collections. PLoS ONE. 5(2). e9166–e9166. 286 indexed citations
19.
Cecconi, Daniela, Michela Tessari, David Willé, et al.. (2008). Serum proteomic analysis during nicotine self‐administration, extinction and relapse in rats. Electrophoresis. 29(7). 1525–1533. 9 indexed citations
20.
Willé, David. (1995). Advanced scientific Fortran. CERN Document Server (European Organization for Nuclear Research). 1 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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