Véra Pancaldi

4.0k total citations
47 papers, 721 citations indexed

About

Véra Pancaldi is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Véra Pancaldi has authored 47 papers receiving a total of 721 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 6 papers in Oncology and 5 papers in Computational Theory and Mathematics. Recurrent topics in Véra Pancaldi's work include Genomics and Chromatin Dynamics (17 papers), Bioinformatics and Genomic Networks (16 papers) and Epigenetics and DNA Methylation (13 papers). Véra Pancaldi is often cited by papers focused on Genomics and Chromatin Dynamics (17 papers), Bioinformatics and Genomic Networks (16 papers) and Epigenetics and DNA Methylation (13 papers). Véra Pancaldi collaborates with scholars based in Spain, France and United Kingdom. Véra Pancaldi's co-authors include Jürg Bähler, Alfonso Valencia, Simone Ecker, Falk Schubert, Daniel Rico, Stephan Beck, Charalampos Rallis, Dirk S. Paul, Teodora Georgescu and Luis López‐Maury and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Véra Pancaldi

44 papers receiving 715 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Véra Pancaldi Spain 16 518 89 86 63 58 47 721
E. Becker France 18 545 1.1× 83 0.9× 46 0.5× 54 0.9× 72 1.2× 66 934
Craig Wallin United States 4 437 0.8× 80 0.9× 23 0.3× 45 0.7× 66 1.1× 7 620
Taibo Li United States 11 451 0.9× 81 0.9× 60 0.7× 33 0.5× 55 0.9× 34 740
Hyun-Hwan Jeong United States 15 556 1.1× 104 1.2× 38 0.4× 126 2.0× 62 1.1× 30 776
Héctor Tejero Spain 13 306 0.6× 110 1.2× 83 1.0× 62 1.0× 104 1.8× 17 657
Ahmed Yousif Ali United Kingdom 7 445 0.9× 52 0.6× 56 0.7× 39 0.6× 95 1.6× 20 699
Greg Slodkowicz United Kingdom 8 553 1.1× 125 1.4× 51 0.6× 19 0.3× 58 1.0× 10 740
Demis A. Kia United Kingdom 7 377 0.7× 113 1.3× 33 0.4× 38 0.6× 68 1.2× 10 695
Minghong Ward United States 4 449 0.9× 224 2.5× 54 0.6× 32 0.5× 115 2.0× 5 711
Timofey Ivanisenko Russia 13 325 0.6× 51 0.6× 37 0.4× 69 1.1× 31 0.5× 45 501

Countries citing papers authored by Véra Pancaldi

Since Specialization
Citations

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

Fields of papers citing papers by Véra Pancaldi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Véra Pancaldi

This figure shows the co-authorship network connecting the top 25 collaborators of Véra Pancaldi. A scholar is included among the top collaborators of Véra Pancaldi 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 Véra Pancaldi. Véra Pancaldi 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.
Dramiński, Michał, M Łapiński, Gabriela Adriana Filip, et al.. (2025). Unveiling Epigenetic Regulatory Elements Associated with Breast Cancer Development. International Journal of Molecular Sciences. 26(14). 6558–6558. 1 indexed citations
2.
3.
Messina, Olivier, et al.. (2023). 3D chromatin interactions involving Drosophila insulators are infrequent but preferential and arise before TADs and transcription. Nature Communications. 14(1). 6678–6678. 9 indexed citations
4.
Zhao, Shilin, Jonathan M. Lehman, Jonathan M. Irish, et al.. (2023). Integrated Multi-omics Analysis of Early Lung Adenocarcinoma Links Tumor Biological Features with Predicted Indolence or Aggressiveness. Cancer Research Communications. 3(7). 1350–1365. 3 indexed citations
5.
Ysebaert, Loïc, et al.. (2023). An agent-based model of monocyte differentiation into tumour-associated macrophages in chronic lymphocytic leukemia. iScience. 26(6). 106897–106897. 4 indexed citations
6.
Pancaldi, Véra. (2023). Network models of chromatin structure. Current Opinion in Genetics & Development. 80. 102051–102051. 6 indexed citations
7.
Pancaldi, Véra, et al.. (2023). From time-series transcriptomics to gene regulatory networks: A review on inference methods. PLoS Computational Biology. 19(8). e1011254–e1011254. 19 indexed citations
8.
Rouanet, Marie, Naı̈ma Hanoun, Hubert Lulka, et al.. (2022). The antitumoral activity of TLR7 ligands is corrupted by the microenvironment of pancreatic tumors. Molecular Therapy. 30(4). 1553–1563. 4 indexed citations
9.
Pancaldi, Véra, Maria Rigau, Osvaldo Graña‐Castro, et al.. (2022). 3D chromatin connectivity underlies replication origin efficiency in mouse embryonic stem cells. Nucleic Acids Research. 50(21). 12149–12165. 9 indexed citations
10.
Bournique, Elodie, Chrystelle Maric, Laure Guitton-Sert, et al.. (2021). Low Replicative Stress Triggers Cell-Type Specific Inheritable Advanced Replication Timing. International Journal of Molecular Sciences. 22(9). 4959–4959. 3 indexed citations
11.
Richart, Laia, Eleonora Lapi, Véra Pancaldi, et al.. (2021). STAG2 loss-of-function affects short-range genomic contacts and modulates the basal-luminal transcriptional program of bladder cancer cells. Nucleic Acids Research. 49(19). 11005–11021. 21 indexed citations
12.
Pancaldi, Véra, et al.. (2021). Tysserand—fast and accurate reconstruction of spatial networks from bioimages. Bioinformatics. 37(21). 3989–3991. 3 indexed citations
13.
Jurman, Giuseppe, et al.. (2020). CovMulNet19, Integrating Proteins, Diseases, Drugs, and Symptoms: A Network Medicine Approach to COVID-19. SHILAP Revista de lepidopterología. 3(1). 130–141. 12 indexed citations
14.
Ysebaert, Loïc, et al.. (2020). Insights on TAM Formation from a Boolean Model of Macrophage Polarization Based on In Vitro Studies. Cancers. 12(12). 3664–3664. 9 indexed citations
15.
Sánchez-Valle, Jon, Héctor Tejero, José M. Fernández, et al.. (2020). Interpreting molecular similarity between patients as a determinant of disease comorbidity relationships. Nature Communications. 11(1). 2854–2854. 23 indexed citations
16.
Greco, Alessandro, Jon Sánchez-Valle, Véra Pancaldi, et al.. (2019). Molecular Inverse Comorbidity between Alzheimer’s Disease and Lung Cancer: New Insights from Matrix Factorization. International Journal of Molecular Sciences. 20(13). 3114–3114. 11 indexed citations
17.
Gurard‐Levin, Zachary A., Natalie A. Twine, Véra Pancaldi, et al.. (2016). Chromatin Regulators as a Guide for Cancer Treatment Choice. Molecular Cancer Therapeutics. 15(7). 1768–1777. 15 indexed citations
18.
Ecker, Simone, Véra Pancaldi, Daniel Rico, & Alfonso Valencia. (2015). Higher gene expression variability in the more aggressive subtype of chronic lymphocytic leukemia. Genome Medicine. 7(1). 8–8. 39 indexed citations
19.
Lehtinen, Sonja, Sandra Codlin, Alexander Schmidt, et al.. (2013). Stress induces remodelling of yeast interaction and co-expression networks. Molecular BioSystems. 9(7). 1697–1707. 18 indexed citations
20.
Pancaldi, Véra, Falk Schubert, & Jürg Bähler. (2009). Meta-analysis of genome regulation and expression variability across hundreds of environmental and genetic perturbations in fission yeast. Molecular BioSystems. 6(3). 543–552. 32 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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