David González

167 papers receiving 4.6k citations

Peers

David González
Comparison fields: 5 of 148
  • Hematology 1.3k
  • Statistical and Nonlinear Physics 985
  • Statistics, Probability and Uncertainty 445
  • Genetics 360
  • Computational Mathematics 19
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Citations per year

Countries citing papers authored by David González

Since Specialization
Citations

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

Fields of papers citing papers by David González

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David González, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David González Line = papers co-authored together David González links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 170 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010273
2 2013239
3 2013210
4 2012184
5 2016176
6 2006151
7 2007139
8
Minimal residual disease monitoring in multiple myeloma: a comparison between allelic-specific oligonucleotide real-time quantitative polymerase chain reaction and flow cytometry.
2005131
9 2009107
10 2013105
11 2009101
12 196494
13 201091
14 201383
15 200882
16 201279
17 201875
18 201874
19 201870
20 202166

About David González

David González is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics, Hematology, Mechanics of Materials and Genetics, having authored 170 papers that have together received 4.7k indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (45 papers), Multiple Myeloma Research and Treatments (19 papers), Numerical methods in engineering (19 papers), Chronic Lymphocytic Leukemia Research (19 papers), Advanced Numerical Methods in Computational Mathematics (12 papers), Elasticity and Material Modeling (12 papers), Probabilistic and Robust Engineering Design (11 papers) and Solid-state spectroscopy and crystallography (10 papers). The work is most often cited by research in Hematology (1.3k citations), Statistical and Nonlinear Physics (985 citations), Statistics, Probability and Uncertainty (445 citations), Genetics (360 citations) and Computational Mathematics (19 citations). David González has collaborated with scholars based in Spain, France and United Kingdom. Frequent co-authors include Elías Cueto, Francisco Chinesta, Gareth J. Morgan, Faith E. Davies, Brian A. Walker, José Vicente Aguado, Icíar Alfaro, Amine Ammar, M. Doblaré and Emmanuelle Abisset‐Chavanne. Their work appears in journals such as Blood, International Journal for Numerical Methods in Engineering, Computer Methods in Applied Mechanics and Engineering, Journal of Magnetism and Magnetic Materials and Archives of Computational Methods in Engineering.

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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