Jorge M. Arevalillo

535 citations
34 papers · 340 · h-index 11

Impact in

Papers in

    • Statistical Distribution Estimation and Applications 11
    • Statistical Methods and Inference 4
    • Advanced Statistical Methods and Models 4
    • Gene expression and cancer classification 8
    • Bioinformatics and Genomic Networks 5

Jorge M. Arevalillo

32 papers receiving 337 citations

Peers

Jorge M. Arevalillo
Comparison fields: 5 of 95
  • Computational Mathematics 10
  • Statistics and Probability 58
  • Cancer Research 53
  • Statistics, Probability and Uncertainty 21
  • Finance 24
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Countries citing papers authored by Jorge M. Arevalillo

Since Specialization
Citations

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

Fields of papers citing papers by Jorge M. Arevalillo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jorge M. Arevalillo. 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 Jorge M. Arevalillo. The network helps show where Jorge M. Arevalillo may publish in the future.

Co-authors

The 25 scholars most cited alongside Jorge M. Arevalillo, 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 Jorge M. Arevalillo Line = papers co-authored together Jorge M. Arevalillo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201952
2 201542
3 201731
4 201722
5 201716
6 202015
7 201815
8 201914
9 201214
10 201814
11 201413
12 201310
13 201810
14 201810
15 20118
16 20208
17 20206
18 20235
19 20215
20 20205

About Jorge M. Arevalillo

Jorge M. Arevalillo is a scholar working on Statistics and Probability, Molecular Biology, Finance, Statistics, Probability and Uncertainty and Artificial Intelligence, having authored 34 papers that have together received 340 indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (11 papers), Gene expression and cancer classification (8 papers), Financial Risk and Volatility Modeling (6 papers), Probabilistic and Robust Engineering Design (6 papers), Bioinformatics and Genomic Networks (5 papers), Statistical Methods and Inference (4 papers), Advanced Statistical Methods and Models (4 papers) and Advanced Proteomics Techniques and Applications (3 papers). The work is most often cited by research in Computational Mathematics (10 citations), Statistics and Probability (58 citations), Cancer Research (53 citations), Statistics, Probability and Uncertainty (21 citations) and Finance (24 citations). Jorge M. Arevalillo has collaborated with scholars based in Spain, Switzerland and Germany. Frequent co-authors include Hilario Navarro, Angelo Gámez‐Pozo, Juan Ángel Fresno Vara, Mariana Díaz‐Almirón, Paloma Maı́n, Enrique Espinosa, Rocío López‐Vacas, Lucía Trilla‐Fuertes, Pilar Zamora and Jaime Feliú. Their work appears in journals such as Test, Scientific Reports, Oncotarget, BMC Cancer and Journal of Multivariate Analysis.

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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