David Martínez-Enguita

684 total citations
7 papers, 296 citations indexed

About

David Martínez-Enguita is a scholar working on Molecular Biology, Epidemiology and Genetics. According to data from OpenAlex, David Martínez-Enguita has authored 7 papers receiving a total of 296 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Epidemiology and 3 papers in Genetics. Recurrent topics in David Martínez-Enguita's work include Genetic Associations and Epidemiology (3 papers), Bioinformatics and Genomic Networks (3 papers) and Mycobacterium research and diagnosis (3 papers). David Martínez-Enguita is often cited by papers focused on Genetic Associations and Epidemiology (3 papers), Bioinformatics and Genomic Networks (3 papers) and Mycobacterium research and diagnosis (3 papers). David Martínez-Enguita collaborates with scholars based in Sweden, Peru and Kenya. David Martínez-Enguita's co-authors include Mika Gustafsson, Xinxiu Li, Margaretha Stenmarker, Sandra Lilja, Per Sandström, Huan Zhang, Samuel Schäfer, Thomas Gasslander, Oleg Sysoev and Xiao‐Feng Sun and has published in prestigious journals such as Bioinformatics, Scientific Reports and The Journal of Infectious Diseases.

In The Last Decade

David Martínez-Enguita

7 papers receiving 287 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 Martínez-Enguita Sweden 4 90 78 60 50 29 7 296
Samuel Schäfer Sweden 7 104 1.2× 92 1.2× 79 1.3× 52 1.0× 28 1.0× 14 371
Sandra Lilja Sweden 7 104 1.2× 94 1.2× 82 1.4× 52 1.0× 28 1.0× 12 366
Margaretha Stenmarker Sweden 4 90 1.0× 78 1.0× 58 1.0× 50 1.0× 28 1.0× 7 309
Danuta R. Gawel Sweden 8 104 1.2× 94 1.2× 160 2.7× 52 1.0× 31 1.1× 14 472
Mona Malekzadeh Iran 9 28 0.3× 20 0.3× 32 0.5× 19 0.4× 17 0.6× 30 393
Adam Knapp United States 8 41 0.5× 47 0.6× 41 0.7× 10 0.2× 12 0.4× 21 263
Mark McConnell United States 9 17 0.2× 27 0.3× 78 1.3× 12 0.2× 50 1.7× 13 368
Jinwei Liu United States 6 51 0.6× 60 0.8× 21 0.3× 34 0.7× 74 2.6× 12 364
Seyed Abolghasem Mirroshandel Iran 12 12 0.1× 34 0.4× 19 0.3× 26 0.5× 200 6.9× 41 568
Weizhi Liu China 9 8 0.1× 15 0.2× 89 1.5× 85 1.7× 79 2.7× 12 391

Countries citing papers authored by David Martínez-Enguita

Since Specialization
Citations

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

Fields of papers citing papers by David Martínez-Enguita

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Martínez-Enguita

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

All Works

7 of 7 papers shown
1.
Sayyab, Shumaila, David Martínez-Enguita, Mika Gustafsson, et al.. (2024). A DNA Methylation Signature From Buccal Swabs to Identify Tuberculosis Infection. The Journal of Infectious Diseases. 231(1). e47–e58. 2 indexed citations
2.
Sayyab, Shumaila, Jakob Paues, David Martínez-Enguita, et al.. (2024). A DNA methylation signature identified in the buccal mucosa reflecting active tuberculosis is changing during tuberculosis treatment. Scientific Reports. 14(1). 29552–29552. 1 indexed citations
3.
Martínez-Enguita, David, et al.. (2023). NCAE: data-driven representations using a deep network-coherent DNA methylation autoencoder identify robust disease and risk factor signatures. Briefings in Bioinformatics. 24(5). 2 indexed citations
4.
Martínez-Enguita, David, Jan Ernerudh, Lennart Nilsson, et al.. (2021). Combined prenatal Lactobacillus reuteri and ω-3 supplementation synergistically modulates DNA methylation in neonatal T helper cells. Clinical Epigenetics. 13(1). 135–135. 14 indexed citations
5.
Martínez-Enguita, David, Tomas Olsson, Lars Alfredsson, et al.. (2021). A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis. BMC Genomics. 22(1). 631–631. 6 indexed citations
6.
Martínez-Enguita, David, et al.. (2020). MODifieR: an Ensemble R Package for Inference of Disease Modules from Transcriptomics Networks. Bioinformatics. 36(12). 3918–3919. 13 indexed citations
7.
Björnsson, Bergþór, Carl Borrebaeck, Nils Elander, et al.. (2019). Digital twins to personalize medicine. Genome Medicine. 12(1). 258 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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