Fidel Ramírez

20.9k total citations · 5 hit papers
34 papers, 10.5k citations indexed

About

Fidel Ramírez is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Immunology. According to data from OpenAlex, Fidel Ramírez has authored 34 papers receiving a total of 10.5k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 6 papers in Pulmonary and Respiratory Medicine and 5 papers in Immunology. Recurrent topics in Fidel Ramírez's work include Genomics and Chromatin Dynamics (8 papers), Bioinformatics and Genomic Networks (7 papers) and Genomics and Phylogenetic Studies (7 papers). Fidel Ramírez is often cited by papers focused on Genomics and Chromatin Dynamics (8 papers), Bioinformatics and Genomic Networks (7 papers) and Genomics and Phylogenetic Studies (7 papers). Fidel Ramírez collaborates with scholars based in Germany, United States and France. Fidel Ramírez's co-authors include Thomas Manke, Björn Grüning, Friederike Dündar, Vivek Bhardwaj, Devon Ryan, Fabian Kilpert, Andreas S. Richter, Steffen Heyne, Sarah Diehl and Thomas Lengauer and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Genes & Development.

In The Last Decade

Fidel Ramírez

30 papers receiving 10.4k citations

Hit Papers

deepTools2: a next generation web server for ... 2007 2026 2013 2019 2016 2014 2007 2018 2018 1000 2.0k 3.0k 4.0k
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.

  1. deepTools2: a next generation web server for deep-sequencing data analysis
    2016 4.4k citations Fidel Ramírez, Devon Ryan et al. Nucleic Acids Research profile →
  2. deepTools: a flexible platform for exploring deep-sequencing data
    2014 2.1k citations Fidel Ramírez, Friederike Dündar et al. Nucleic Acids Research profile →
  3. Computing topological parameters of biological networks
    2007 1.4k citations Yassen Assenov, Fidel Ramírez et al. Bioinformatics profile →
  4. GOATOOLS: A Python library for Gene Ontology analyses
    2018 724 citations Liangsheng Zhang, Brent S. Pedersen et al. Scientific Reports profile →
  5. High-resolution TADs reveal DNA sequences underlying genome organization in flies
    2018 543 citations Fidel Ramírez, Vivek Bhardwaj et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fidel Ramírez Germany 21 8.2k 2.2k 1.2k 990 931 34 10.5k
Nicolas Bray United States 14 5.8k 0.7× 1.5k 0.7× 1.2k 1.0× 1.1k 1.1× 910 1.0× 17 8.9k
Joseph M. Paggi United States 13 5.5k 0.7× 2.6k 1.1× 1.1k 0.9× 802 0.8× 768 0.8× 17 9.1k
Ryan Kelley United States 8 7.3k 0.9× 2.4k 1.1× 1.5k 1.2× 1.6k 1.6× 967 1.0× 8 11.1k
Guillaume Bourque Canada 37 7.3k 0.9× 2.8k 1.2× 1.6k 1.3× 1.3k 1.3× 551 0.6× 125 9.7k
Yijun Ruan United States 43 6.4k 0.8× 1.7k 0.8× 1.3k 1.0× 1.1k 1.1× 610 0.7× 106 9.0k
Christopher Bennett United States 3 4.7k 0.6× 2.6k 1.2× 1.1k 0.9× 818 0.8× 756 0.8× 3 8.1k
Xiaowo Wang China 28 5.7k 0.7× 1.6k 0.7× 816 0.7× 1.7k 1.7× 825 0.9× 110 8.4k
Nicolas Servant France 36 6.3k 0.8× 1.7k 0.8× 1.5k 1.2× 1.4k 1.5× 1.1k 1.2× 96 8.6k
Björn Grüning Germany 32 10.5k 1.3× 2.6k 1.2× 1.6k 1.3× 1.2k 1.2× 1.0k 1.1× 110 14.4k
Yutaka Suzuki Japan 50 6.1k 0.7× 1.2k 0.5× 1.3k 1.1× 1.0k 1.0× 1.4k 1.5× 318 9.8k

Countries citing papers authored by Fidel Ramírez

Since Specialization
Citations

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

Fields of papers citing papers by Fidel Ramírez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fidel Ramírez

This figure shows the co-authorship network connecting the top 25 collaborators of Fidel Ramírez. A scholar is included among the top collaborators of Fidel Ramírez 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 Fidel Ramírez. Fidel Ramírez 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.
Thomas, Matthew J., Franziska Herrmann, Katja Koeppen, et al.. (2025). Nerandomilast Paves the Way for Novel Strategies in IPF Drug Discovery. American Journal of Respiratory and Critical Care Medicine. 211(Supplement_1). A4590–A4590.
2.
Pinto, Catarina, Sophie Zahalka, Barbara Thaler, et al.. (2025). Cross-disease integration of single-cell RNA sequencing data from lung myeloid cells reveals TAM signature in in vitro model. OncoImmunology. 14(1). 2502278–2502278. 1 indexed citations
3.
Mayr, Christoph H., Diana Santacruz, Sebastian Jarosch, et al.. (2024). Spatial transcriptomic characterization of pathologic niches in IPF. Science Advances. 10(32). eadl5473–eadl5473. 27 indexed citations
4.
Ansari, Meshal, Diana Santacruz, Werner Rust, et al.. (2024). JUNB O‐GlcNAcylation‐Mediated Promoter Accessibility of Metabolic Genes Modulates Distinct Epithelial Lineage in Pulmonary Fibrosis. Advanced Science. 12(5). e2406751–e2406751. 2 indexed citations
5.
Mayr, Christoph H., Katrin Fundel‐Clemens, Łukasz M. Boryń, et al.. (2023). Transcriptomic and Proteomic Changes Driving Pulmonary Fibrosis Resolution in Young and Old Mice. American Journal of Respiratory Cell and Molecular Biology. 69(4). 422–440. 8 indexed citations
6.
Fundel‐Clemens, Katrin, Praveen Baskaran, Christian T. Wohnhaas, et al.. (2022). Antifibrotic Drug Nintedanib Inhibits CSF1R to Promote IL-4–associated Tissue Repair Macrophages. American Journal of Respiratory Cell and Molecular Biology. 68(4). 366–380. 21 indexed citations
7.
Kind, David, Praveen Baskaran, Fidel Ramírez, et al.. (2022). Automation enables high-throughput and reproducible single-cell transcriptomics library preparation. SLAS TECHNOLOGY. 27(2). 135–142. 5 indexed citations
8.
Lopez‐Delisle, Lucille, Leily Rabbani, Joachim Wolff, et al.. (2020). pyGenomeTracks: reproducible plots for multivariate genomic datasets . Bioinformatics. 37(3). 422–423. 247 indexed citations
9.
Richter, Florian, Fidel Ramírez, Maria Shvedunova, et al.. (2019). CAPRI enables comparison of evolutionarily conserved RNA interacting regions. Nature Communications. 10(1). 2682–2682. 33 indexed citations
10.
Renschler, Gina, Gautier Richard, Claudia Isabelle Keller Valsecchi, et al.. (2019). Hi-C guided assemblies reveal conserved regulatory topologies on X and autosomes despite extensive genome shuffling. Genes & Development. 33(21-22). 1591–1612. 38 indexed citations
11.
Arrigoni, Laura, Fidel Ramírez, Ilaria Panzeri, et al.. (2018). RELACS nuclei barcoding enables high-throughput ChIP-seq. Communications Biology. 1(1). 22 indexed citations
12.
Ramírez, Fidel, Vivek Bhardwaj, Laura Arrigoni, et al.. (2018). High-resolution TADs reveal DNA sequences underlying genome organization in flies. Nature Communications. 9(1). 189–189. 543 indexed citations breakdown →
13.
Zhang, Liangsheng, Brent S. Pedersen, Fidel Ramírez, et al.. (2018). GOATOOLS: A Python library for Gene Ontology analyses. Scientific Reports. 8(1). 10872–10872. 724 indexed citations breakdown →
14.
Salhab, Abdulrahman, Karl Nordström, Gilles Gasparoni, et al.. (2018). A comprehensive analysis of 195 DNA methylomes reveals shared and cell-specific features of partially methylated domains. Genome biology. 19(1). 59 indexed citations
15.
Ramírez, Fidel, Sarah Toscano, Kin Chung Lam, et al.. (2015). High-Affinity Sites Form an Interaction Network to Facilitate Spreading of the MSL Complex across the X Chromosome in Drosophila. Molecular Cell. 60(1). 146–162. 58 indexed citations
16.
Ramírez, Fidel, Friederike Dündar, Sarah Diehl, Björn Grüning, & Thomas Manke. (2014). deepTools: a flexible platform for exploring deep-sequencing data. Nucleic Acids Research. 42(W1). W187–W191. 2106 indexed citations breakdown →
17.
Bulut-Karslıoğlu, Aydan, Inti A. De La Rosa-Velázquez, Fidel Ramírez, et al.. (2014). Suv39h-Dependent H3K9me3 Marks Intact Retrotransposons and Silences LINE Elements in Mouse Embryonic Stem Cells. Molecular Cell. 55(2). 277–290. 237 indexed citations
18.
Izzo, Annalisa, Kinga Kamieniarz-Gdula, Fidel Ramírez, et al.. (2013). The Genomic Landscape of the Somatic Linker Histone Subtypes H1.1 to H1.5 in Human Cells. Cell Reports. 3(6). 2142–2154. 96 indexed citations
19.
Blankenburg, Hagen, Fidel Ramírez, Joachim Büch, & M. Albrecht. (2009). DASMIweb: online integration, analysis and assessment of distributed protein interaction data. Nucleic Acids Research. 37(Web Server). W122–W128. 2 indexed citations
20.
Ramírez, Fidel, Andreas Schlicker, Yassen Assenov, Thomas Lengauer, & Mario Albrecht. (2007). Computational analysis of human protein interaction networks. PROTEOMICS. 7(15). 2541–2552. 52 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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