Daniel Domingo‐Fernándéz

1.5k total citations · 1 hit paper
50 papers, 698 citations indexed

About

Daniel Domingo‐Fernándéz is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Daniel Domingo‐Fernándéz has authored 50 papers receiving a total of 698 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 13 papers in Computational Theory and Mathematics and 11 papers in Artificial Intelligence. Recurrent topics in Daniel Domingo‐Fernándéz's work include Bioinformatics and Genomic Networks (27 papers), Computational Drug Discovery Methods (13 papers) and Biomedical Text Mining and Ontologies (10 papers). Daniel Domingo‐Fernándéz is often cited by papers focused on Bioinformatics and Genomic Networks (27 papers), Computational Drug Discovery Methods (13 papers) and Biomedical Text Mining and Ontologies (10 papers). Daniel Domingo‐Fernándéz collaborates with scholars based in Germany, United States and Spain. Daniel Domingo‐Fernándéz's co-authors include Martin Hofmann‐Apitius, Charles Tapley Hoyt, Sarah Mubeen, Alpha Tom Kodamullil, Holger Fröhlich, Yojana Gadiya, Reagon Karki, Tamara Raschka, Colin Birkenbihl and Christian Ebeling and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and Scientific Reports.

In The Last Decade

Daniel Domingo‐Fernándéz

46 papers receiving 682 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Multi-omics data integration identifies novel biomarkers and patient subgroups in inflammatory bowel disease

2025 13 citations António J. Preto, Shaurya Chanana et al. Journal of Crohn s and Colitis profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel Domingo‐Fernándéz Germany	15	427	145	135	66	64	50	698
Erfan Younesi Germany	14	365 0.9×	131 0.9×	109 0.8×	58 0.9×	121 1.9×	35	643
Alpha Tom Kodamullil Germany	15	348 0.8×	129 0.9×	108 0.8×	19 0.3×	123 1.9×	39	583
P. K. Vinod India	22	754 1.8×	248 1.7×	209 1.5×	24 0.4×	62 1.0×	67	1.6k
Giulia Fiscon Italy	23	1.1k 2.5×	89 0.6×	274 2.0×	44 0.7×	90 1.4×	62	1.6k
Kristina Hettne Netherlands	20	570 1.3×	195 1.3×	125 0.9×	12 0.2×	101 1.6×	52	991
Francesco Napolitano Italy	15	515 1.2×	57 0.4×	322 2.4×	14 0.2×	42 0.7×	41	912
Ju Xiang China	21	543 1.3×	82 0.6×	151 1.1×	15 0.2×	65 1.0×	91	1.2k
Sergei Egorov United States	5	699 1.6×	145 1.0×	94 0.7×	12 0.2×	37 0.6×	5	949
Michael Farnum United States	12	233 0.5×	61 0.4×	125 0.9×	223 3.4×	143 2.2×	20	683
Chien‐Ming Li Taiwan	18	221 0.5×	40 0.3×	57 0.4×	20 0.3×	46 0.7×	41	892

Countries citing papers authored by Daniel Domingo‐Fernándéz

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Domingo‐Fernándéz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Domingo‐Fernándéz. 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 Daniel Domingo‐Fernándéz. The network helps show where Daniel Domingo‐Fernándéz may publish in the future.

Co-authorship network of co-authors of Daniel Domingo‐Fernándéz

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Gadiya, Yojana, et al.. (2025). Defining the limits of plant chemical space: challenges and estimations. GigaScience. 14. 1 indexed citations

Preto, António J., Shaurya Chanana, Daniel Ence, et al.. (2025). Multi-omics data integration identifies novel biomarkers and patient subgroups in inflammatory bowel disease. Journal of Crohn s and Colitis. 19(1). 13 indexed citations breakdown →

Preto, António J., et al.. (2024). Evaluating the generalizability of graph neural networks for predicting collision cross section. Journal of Cheminformatics. 16(1). 105–105. 1 indexed citations

Russo, Maria Francesca, Daniel Domingo‐Fernándéz, Andrea Zaliani, et al.. (2024). Curating, Collecting, and Cataloguing Global COVID-19 Datasets for the Aim of Predicting Personalized Risk. Data. 9(2). 25–25.

Salimi, Yahya, Daniel Domingo‐Fernándéz, Martin Hofmann‐Apitius, & Colin Birkenbihl. (2023). Data-Driven Thresholding Statistically Biases ATN Profiling across Cohort Datasets. The Journal of Prevention of Alzheimer s Disease. 11(1). 185–195. 2 indexed citations

Madan, Sumit, Daniel Domingo‐Fernándéz, Ashar Ahmad, et al.. (2023). MultiGML: Multimodal graph machine learning for prediction of adverse drug events. Heliyon. 9(9). e19441–e19441. 9 indexed citations

Domingo‐Fernándéz, Daniel, et al.. (2023). Exploring the known chemical space of the plant kingdom: insights into taxonomic patterns, knowledge gaps, and bioactive regions. Journal of Cheminformatics. 15(1). 107–107. 12 indexed citations

Raschka, Tamara, et al.. (2022). Elucidating gene expression patterns across multiple biological contexts through a large-scale investigation of transcriptomic datasets. BMC Bioinformatics. 23(1). 7 indexed citations

Hoyt, Charles Tapley, Colin Birkenbihl, Benjamin M. Gyori, et al.. (2022). STonKGs: a sophisticated transformer trained on biomedical text and knowledge graphs. Bioinformatics. 38(6). 1648–1656. 17 indexed citations

10.

Raschka, Tamara, et al.. (2021). Towards a global investigation of transcriptomic signatures through co-expression networks and pathway knowledge for the identification of disease mechanisms. Nucleic Acids Research. 49(14). 7939–7953. 4 indexed citations

11.

Mubeen, Sarah, et al.. (2021). DecoPath: a web application for decoding pathway enrichment analysis. NAR Genomics and Bioinformatics. 3(3). lqab087–lqab087. 3 indexed citations

12.

Birkenbihl, Colin, Sarah Mubeen, Jens Lehmann, et al.. (2021). CLEP: a hybrid data- and knowledge-driven framework for generating patient representations. Bioinformatics. 37(19). 3311–3318. 8 indexed citations

13.

Domingo‐Fernándéz, Daniel, Sarah Mubeen, Charles Tapley Hoyt, et al.. (2021). A Systems Biology Approach for Hypothesizing the Effect of Genetic Variants on Neuroimaging Features in Alzheimer’s Disease. Journal of Alzheimer s Disease. 80(2). 831–840. 3 indexed citations

14.

Domingo‐Fernándéz, Daniel, Shounak Baksi, Bruce Schultz, et al.. (2020). COVID-19 Knowledge Graph: a computable, multi-modal, cause-and-effect knowledge model of COVID-19 pathophysiology. Bioinformatics. 37(9). 1332–1334. 72 indexed citations

15.

Mubeen, Sarah, et al.. (2020). MultiPaths: a Python framework for analyzing multi-layer biological networks using diffusion algorithms. Bioinformatics. 37(1). 137–139. 3 indexed citations

16.

Wu, Ping, Daniel Domingo‐Fernándéz, Henri A. Vrooman, et al.. (2020). Clustering of Alzheimer’s and Parkinson’s disease based on genetic burden of shared molecular mechanisms. Scientific Reports. 10(1). 19097–19097. 12 indexed citations

17.

Hoyt, Charles Tapley, et al.. (2019). BioKEEN: a library for learning and evaluating biological knowledge graph embeddings. Bioinformatics. 35(18). 3538–3540. 15 indexed citations

18.

Domingo‐Fernándéz, Daniel, Allison C. Provost, Alpha Tom Kodamullil, et al.. (2019). PTSD Biomarker Database: deep dive metadatabase for PTSD biomarkers, visualizations and analysis tools. Database. 2019. 13 indexed citations

19.

Hoyt, Charles Tapley, et al.. (2019). Re-curation and rational enrichment of knowledge graphs in Biological Expression Language. Database. 2019. 15 indexed citations

20.

Mubeen, Sarah, et al.. (2019). The Impact of Pathway Database Choice on Statistical Enrichment Analysis and Predictive Modeling. Frontiers in Genetics. 10. 1203–1203. 71 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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