Baldo Oliva

3.9k total citations · 1 hit paper
90 papers, 2.5k citations indexed

About

Baldo Oliva is a scholar working on Molecular Biology, Computational Theory and Mathematics and Oncology. According to data from OpenAlex, Baldo Oliva has authored 90 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Molecular Biology, 23 papers in Computational Theory and Mathematics and 10 papers in Oncology. Recurrent topics in Baldo Oliva's work include Bioinformatics and Genomic Networks (36 papers), Protein Structure and Dynamics (24 papers) and Computational Drug Discovery Methods (23 papers). Baldo Oliva is often cited by papers focused on Bioinformatics and Genomic Networks (36 papers), Protein Structure and Dynamics (24 papers) and Computational Drug Discovery Methods (23 papers). Baldo Oliva collaborates with scholars based in Spain, United Kingdom and United States. Baldo Oliva's co-authors include Emre Güney, Javier Garcı́a-Garcı́a, Ramón Aragüés, Jaume Bonet, Narcís Fernández‐Fuentes, Joan Planas-Iglesias, Harald Schmidt, Jordi Espadaler, Antonio Cuadrado and Ana I. Rojo and has published in prestigious journals such as Science, Cell and Nucleic Acids Research.

In The Last Decade

Baldo Oliva

86 papers receiving 2.5k citations

Hit Papers

Transcription Factor NRF2 as a Therapeutic Target for Chr... 2018 2026 2020 2023 2018 100 200 300 400 500

Peers

Baldo Oliva
Hao Fan Singapore
Adam Yasgar United States
Jacob de Vlieg Netherlands
Hao Fan Singapore
Baldo Oliva
Citations per year, relative to Baldo Oliva Baldo Oliva (= 1×) peers Hao Fan

Countries citing papers authored by Baldo Oliva

Since Specialization
Citations

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

Fields of papers citing papers by Baldo Oliva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Baldo Oliva

This figure shows the co-authorship network connecting the top 25 collaborators of Baldo Oliva. A scholar is included among the top collaborators of Baldo Oliva 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 Baldo Oliva. Baldo Oliva 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.
Kramer, Eric M., Markus Mund, Mercè Izquierdo-Serra, et al.. (2026). Continuum architecture dynamics of vesicle tethering in exocytosis. Cell. 189(4). 1170–1184.e22.
2.
Oliva, Baldo, et al.. (2025). How did we get there? AI applications to biological networks and sequences. Computers in Biology and Medicine. 190. 110064–110064. 2 indexed citations
3.
Vega, Montserrat Rojo de la, Isabel Alves‐Rodrigues, Roger Anglada, et al.. (2025). Nrm1 is a bistable switch connecting cell cycle progression to transcriptional control. EMBO Reports. 26(20). 5048–5069.
4.
Oliva, Baldo, et al.. (2023). A decision support system based on artificial intelligence and systems biology for the simulation of pancreatic cancer patient status. CPT Pharmacometrics & Systems Pharmacology. 12(7). 916–928. 4 indexed citations
5.
Fornés, Oriol, et al.. (2021). On the use of direct-coupling analysis with a reduced alphabet of amino acids combined with super-secondary structure motifs for protein fold prediction. NAR Genomics and Bioinformatics. 3(2). lqab027–lqab027. 2 indexed citations
6.
Defaus, Sira, et al.. (2021). Evaluation of Computationally Designed Peptides against TWEAK, a Cytokine of the Tumour Necrosis Factor Ligand Family. International Journal of Molecular Sciences. 22(3). 1066–1066. 4 indexed citations
7.
Fornés, Oriol, et al.. (2020). On the prediction of DNA-binding preferences of C2H2-ZF domains using structural models: application on human CTCF. NAR Genomics and Bioinformatics. 2(3). lqaa046–lqaa046. 7 indexed citations
8.
Segura, Joan, et al.. (2020). Galaxy InteractoMIX: An Integrated Computational Platform for the Study of Protein–Protein Interaction Data. Journal of Molecular Biology. 433(11). 166656–166656. 7 indexed citations
9.
Resa‐Infante, Patricia, Jaume Bonet, Swantje Thiele, et al.. (2019). Alternative interaction sites in the influenza A virus nucleoprotein mediate viral escape from the importin‐α7 mediated nuclear import pathway. FEBS Journal. 286(17). 3374–3388. 3 indexed citations
10.
Rubio-Pérez, Carlota, Emre Güney, Daniel Aguilar, et al.. (2017). Genetic and functional characterization of disease associations explains comorbidity. Scientific Reports. 7(1). 6207–6207. 27 indexed citations
11.
Wright, Roni H. G., Antonios Lioutas, François Le Dily, et al.. (2016). ADP-ribose–derived nuclear ATP synthesis by NUDIX5 is required for chromatin remodeling. Science. 352(6290). 1221–1225. 127 indexed citations
12.
Resa‐Infante, Patricia, Jaume Bonet, Anna Otte, et al.. (2015). Targeting Importin-α7 as a Therapeutic Approach against Pandemic Influenza Viruses. Journal of Virology. 89(17). 9010–9020. 16 indexed citations
13.
Martínez-Høyer, Sergio, Álvaro Aranguren‐Ibáñez, Javier Garcı́a-Garcı́a, et al.. (2013). Protein kinase CK2-dependent phosphorylation of the human Regulators of Calcineurin reveals a novel mechanism regulating the calcineurin–NFATc signaling pathway. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1833(10). 2311–2321. 14 indexed citations
14.
Santana-Codina, Naiara, Rafael Carretero, Rebeca Sanz‐Pamplona, et al.. (2013). A Transcriptome-proteome Integrated Network Identifies Endoplasmic Reticulum thiol oxidoreductase (ERp57) as a Hub that Mediates Bone Metastasis. Molecular & Cellular Proteomics. 12(8). 2111–2125. 33 indexed citations
15.
Garriga, Damià, Cristina Ferrer‐Orta, Jordi Querol‐Audí, Baldo Oliva, & Núria Verdaguer. (2013). Role of Motif B Loop in Allosteric Regulation of RNA-Dependent RNA Polymerization Activity. Journal of Molecular Biology. 425(13). 2279–2287. 51 indexed citations
16.
Sanz‐Pamplona, Rebeca, Javier Garcı́a-Garcı́a, Xavier Messeguer, et al.. (2012). A taxonomy of organ-specific breast cancer metastases based on a protein–protein interaction network. Molecular BioSystems. 8(8). 2085–2096. 11 indexed citations
17.
Wright, Roni H. G., Giancarlo Castellano, Jaume Bonet, et al.. (2012). CDK2-dependent activation of PARP-1 is required for hormonal gene regulation in breast cancer cells. Genes & Development. 26(17). 1972–1983. 101 indexed citations
18.
Garcı́a-Garcı́a, Javier, Jaume Bonet, Emre Güney, et al.. (2012). Networks of ProteinProtein Interactions: From Uncertainty to Molecular Details. Molecular Informatics. 31(5). 342–362. 18 indexed citations
19.
Romero‐Isart, Núria, Baldo Oliva, & Milan Vašák. (2009). Influence of $$ {\text{NH - }}{{\text{S}}^\gamma } $$ bonding interactions on the structure and dynamics of metallothioneins. Journal of Molecular Modeling. 16(3). 387–394. 7 indexed citations
20.
Aragüés, Ramón, Chris Sander, & Baldo Oliva. (2008). Predicting cancer involvement of genes from heterogeneous data. BMC Bioinformatics. 9(1). 172–172. 60 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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