David Bernal‐Casas

1.2k total citations
20 papers, 334 citations indexed

About

David Bernal‐Casas is a scholar working on Cellular and Molecular Neuroscience, Neurology and Statistical and Nonlinear Physics. According to data from OpenAlex, David Bernal‐Casas has authored 20 papers receiving a total of 334 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Cellular and Molecular Neuroscience, 5 papers in Neurology and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in David Bernal‐Casas's work include Neuroscience and Neuropharmacology Research (4 papers), Neurological disorders and treatments (4 papers) and Statistical Mechanics and Entropy (4 papers). David Bernal‐Casas is often cited by papers focused on Neuroscience and Neuropharmacology Research (4 papers), Neurological disorders and treatments (4 papers) and Statistical Mechanics and Entropy (4 papers). David Bernal‐Casas collaborates with scholars based in Spain, United States and Saudi Arabia. David Bernal‐Casas's co-authors include Hyun Joo Lee, Andrew J. Weitz, Peter Kirsch, Martin Fungisai Gerchen, Jin Hyung Lee, Ben A. Duffy, Anatol C. Kreitzer, ManKin Choy, Alexxai V. Kravitz and Jin Hyung Lee and has published in prestigious journals such as Neuron, SHILAP Revista de lepidopterología and NeuroImage.

In The Last Decade

David Bernal‐Casas

18 papers receiving 333 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 Bernal‐Casas Spain 8 171 131 49 47 45 20 334
Mitchell L. de Snoo Canada 9 58 0.3× 112 0.9× 42 0.9× 104 2.2× 119 2.6× 13 365
Glen Frick United States 12 47 0.3× 64 0.5× 2 0.0× 84 1.8× 41 0.9× 28 409
Bernd J. Vorderwülbecke Germany 12 224 1.3× 92 0.7× 29 0.6× 63 1.4× 24 488
Lixin Cai China 12 101 0.6× 97 0.7× 1 0.0× 63 1.3× 37 0.8× 54 376
Guoming Luan China 10 105 0.6× 114 0.9× 43 0.9× 78 1.7× 36 353
Vivek Khatri United States 11 305 1.8× 267 2.0× 39 0.8× 75 1.7× 19 501
Tingting Xu China 10 179 1.0× 21 0.2× 2 0.0× 11 0.2× 30 0.7× 20 293
Xuyang Wang China 10 106 0.6× 62 0.5× 46 1.0× 50 1.1× 34 284
Xueping Hu China 10 75 0.4× 59 0.5× 31 0.7× 58 1.3× 39 345
Emma J. Moore United Kingdom 9 95 0.6× 35 0.3× 20 0.4× 50 1.1× 13 384

Countries citing papers authored by David Bernal‐Casas

Since Specialization
Citations

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

Fields of papers citing papers by David Bernal‐Casas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Bernal‐Casas

This figure shows the co-authorship network connecting the top 25 collaborators of David Bernal‐Casas. A scholar is included among the top collaborators of David Bernal‐Casas 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 Bernal‐Casas. David Bernal‐Casas 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.
Bernal‐Casas, David & Josep M. Oller. (2025). Information-Geometric Models in Data Analysis and Physics. Mathematics. 13(19). 3114–3114.
2.
Stefanini, Edson, Alberto Alvarez‐Iglesias, M Fernández, et al.. (2025). CE(20:4) and CE(22:5) cholesteryl ester levels are elevated in the plasma of Alzheimer’s disease patients with ε3/ε4 genotype. SHILAP Revista de lepidopterología. 5. 2 indexed citations
3.
Marín, Silvia, Alberto Alvarez‐Iglesias, Jaume Lillo, et al.. (2025). Novel protocol for metabolomics data normalization and biomarker discovery in human tears. Clinical Chemistry and Laboratory Medicine (CCLM). 63(8). 1599–1609. 1 indexed citations
4.
Stefanini, Edson, Alberto Alvarez‐Iglesias, Hanan Awad Alkozi, et al.. (2025). Machine Learning Approach to Select Small Compounds in Plasma as Predictors of Alzheimer’s Disease. International Journal of Molecular Sciences. 26(14). 6991–6991. 1 indexed citations
5.
Bernal‐Casas, David & Josep M. Oller. (2024). Variational Information Principles to Unveil Physical Laws. Mathematics. 12(24). 3941–3941. 2 indexed citations
6.
7.
Bernal‐Casas, David & Josep M. Oller. (2024). Intrinsic Information-Theoretic Models. Entropy. 26(5). 370–370. 2 indexed citations
8.
Bernal‐Casas, David & Josep M. Oller. (2024). Analyzing Sample Size in Information-Theoretic Models. Mathematics. 12(24). 4018–4018.
9.
Marín, Silvia, David Bernal‐Casas, Alejandro Lillo, et al.. (2023). A metabolomics study in aqueous humor discloses altered arginine metabolism in Parkinson’s disease. Fluids and Barriers of the CNS. 20(1). 90–90. 9 indexed citations
10.
Bernal‐Casas, David & Giuseppe Vitiello. (2023). Dynamical Asymmetries, the Bayes’ Theorem, Entanglement, and Intentionality in the Brain Functional Activity. Symmetry. 15(12). 2184–2184. 2 indexed citations
11.
Bernal‐Casas, David & Josep M. Oller. (2023). Information-Theoretic Models for Physical Observables. Entropy. 25(10). 1448–1448. 3 indexed citations
12.
Lillo, Alejandro, Silvia Marín, David Bernal‐Casas, et al.. (2022). Biogenic Amine Levels Markedly Increase in the Aqueous Humor of Individuals with Controlled Type 2 Diabetes. International Journal of Molecular Sciences. 23(21). 12752–12752. 5 indexed citations
13.
Fernández‐García, Sara, Esther García-García, Clara Gort‐Paniello, et al.. (2020). M2 cortex-dorsolateral striatum stimulation reverses motor symptoms and synaptic deficits in Huntington’s disease. eLife. 9. 29 indexed citations
14.
Bernal‐Casas, David, et al.. (2020). Artificial neural networks and the path to diagnosing Parkinson's Disease. Parkinsonism & Related Disorders. 79. e9–e9. 1 indexed citations
15.
Lúcia, Marc, Edoardo Melilli, Carmen Lefaucheur, et al.. (2018). Value of monitoring circulating donor-reactive memory B cells to characterize antibody-mediated rejection after kidney transplantation. American Journal of Transplantation. 19(2). 368–380. 56 indexed citations
16.
Bernal‐Casas, David, Hyun Joo Lee, Andrew J. Weitz, & Jin Hyung Lee. (2017). Studying Brain Circuit Function with Dynamic Causal Modeling for Optogenetic fMRI. Neuron. 93(3). 522–532.e5. 43 indexed citations
17.
Liu, Jia, Ben A. Duffy, David Bernal‐Casas, Zhongnan Fang, & Jin Hyung Lee. (2016). Comparison of fMRI analysis methods for heterogeneous BOLD responses in block design studies. NeuroImage. 147. 390–408. 16 indexed citations
18.
Lee, Hyun Joo, Andrew J. Weitz, David Bernal‐Casas, et al.. (2016). Activation of Direct and Indirect Pathway Medium Spiny Neurons Drives Distinct Brain-wide Responses. Neuron. 91(2). 412–424. 95 indexed citations
19.
Gerchen, Martin Fungisai, David Bernal‐Casas, & Peter Kirsch. (2014). Analyzing task‐dependent brain network changes by whole‐brain psychophysiological interactions: A comparison to conventional analysis. Human Brain Mapping. 35(10). 5071–5082. 45 indexed citations
20.
Bernal‐Casas, David, Emili Balaguer‐Ballester, Martin Fungisai Gerchen, et al.. (2013). Multi-site reproducibility of prefrontal–hippocampal connectivity estimates by stochastic DCM. NeuroImage. 82. 555–563. 18 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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