David Delano

2.5k total citations · 1 hit paper
9 papers, 1.8k citations indexed

About

David Delano is a scholar working on Molecular Biology, Physiology and Genetics. According to data from OpenAlex, David Delano has authored 9 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Physiology and 2 papers in Genetics. Recurrent topics in David Delano's work include Adenosine and Purinergic Signaling (2 papers), RNA modifications and cancer (2 papers) and Epigenetics and DNA Methylation (2 papers). David Delano is often cited by papers focused on Adenosine and Purinergic Signaling (2 papers), RNA modifications and cancer (2 papers) and Epigenetics and DNA Methylation (2 papers). David Delano collaborates with scholars based in United States and Switzerland. David Delano's co-authors include Kevin L. Gunderson, Vincent Ho, Richard Shen, Marina Bibikova, Brandy Klotzle, Gary P. Schroth, Lu Zhang, Bret Barnes, Jennie Le and Jian‐Bing Fan and has published in prestigious journals such as Journal of Neuroscience, The Journal of Immunology and Cancer Research.

In The Last Decade

David Delano

9 papers receiving 1.8k citations

Hit Papers

High density DNA methylation array with single CpG site r... 2011 2026 2016 2021 2011 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Delano United States 8 1.2k 433 255 198 178 9 1.8k
Ester Lara Spain 12 803 0.7× 168 0.4× 89 0.3× 94 0.5× 154 0.9× 15 1.3k
Joanne Wang United States 21 495 0.4× 90 0.2× 149 0.6× 64 0.3× 260 1.5× 47 1.8k
Tomáš Honzík Czechia 23 1.1k 0.9× 225 0.5× 56 0.2× 57 0.3× 170 1.0× 102 1.6k
Jolanta Sykut‐Cegielska Poland 24 998 0.8× 336 0.8× 40 0.2× 78 0.4× 188 1.1× 77 1.7k
Mirko Pinotti Italy 30 1.1k 0.9× 272 0.6× 61 0.2× 73 0.4× 49 0.3× 122 3.1k
Marcela Covic Germany 15 1.1k 1.0× 178 0.4× 38 0.1× 203 1.0× 88 0.5× 23 1.6k
Tingting Yu China 19 651 0.5× 350 0.8× 30 0.1× 117 0.6× 76 0.4× 108 1.3k
Majid Alfadhel Saudi Arabia 28 1.4k 1.1× 920 2.1× 30 0.1× 82 0.4× 301 1.7× 157 2.5k
Ulrika von Döbeln Sweden 31 1.3k 1.1× 456 1.1× 43 0.2× 44 0.2× 235 1.3× 79 2.4k
Thomas C. Markello United States 28 943 0.8× 695 1.6× 30 0.1× 93 0.5× 428 2.4× 68 2.5k

Countries citing papers authored by David Delano

Since Specialization
Citations

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

Fields of papers citing papers by David Delano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Delano

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

All Works

9 of 9 papers shown
1.
Bibikova, Marina, Bret Barnes, Vincent Ho, et al.. (2011). High density DNA methylation array with single CpG site resolution. Genomics. 98(4). 288–295. 1177 indexed citations breakdown →
2.
Bibikova, Marina, Bret Barnes, Vincent Ho, et al.. (2011). Abstract LB-176: A novel high density DNA methylation array with single CpG site resolution. Cancer Research. 71(8_Supplement). LB–176. 4 indexed citations
3.
Schwander, Martin, Vanda S. Lopes, Anna Sczaniecka, et al.. (2009). A Novel Allele of Myosin VIIa Reveals a Critical Function for the C-Terminal FERM Domain for Melanosome Transport in Retinal Pigment Epithelial Cells. Journal of Neuroscience. 29(50). 15810–15818. 32 indexed citations
4.
Wu, Chunlei, David Delano, Nico Mitro, et al.. (2008). Gene Set Enrichment in eQTL Data Identifies Novel Annotations and Pathway Regulators. PLoS Genetics. 4(5). e1000070–e1000070. 74 indexed citations
5.
Janes, Jeff, Chunlei Wu, David Delano, et al.. (2007). Genomewide Association Analysis in Diverse Inbred Mice: Power and Population Structure. Genetics. 176(1). 675–683. 60 indexed citations
6.
Chan, Edwin S. L., M. Carmen Montesinos, Patricia Fernández, et al.. (2006). Adenosine A2Areceptors play a role in the pathogenesis of hepatic cirrhosis. British Journal of Pharmacology. 148(8). 1144–1155. 194 indexed citations
7.
Delano, David, M. Carmen Montesinos, Avani Desai, et al.. (2005). Genetically based resistance to the antiinflammatory effects of methotrexate in the air‐pouch model of acute inflammation. Arthritis & Rheumatism. 52(8). 2567–2575. 25 indexed citations
8.
Delano, David, M. Carmen Montesinos, Peter D’Eustachio, Tim Wiltshire, & Bruce N. Cronstein. (2005). An Interaction Between Genetic Factors and Gender Determines the Magnitude of the Inflammatory Response in the Mouse Air Pouch Model of Acute Inflammation. Inflammation. 29(1). 1–7. 17 indexed citations
9.
Nguyen, Khoa, et al.. (2001). Inflammatory Cytokines Regulate Function and Expression of Adenosine A2A Receptors in Human Monocytic THP-1 Cells. The Journal of Immunology. 167(7). 4026–4032. 205 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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