Daniel Clarke

7.0k total citations · 1 hit paper
71 papers, 3.2k citations indexed

About

Daniel Clarke is a scholar working on Molecular Biology, Soil Science and Economics and Econometrics. According to data from OpenAlex, Daniel Clarke has authored 71 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 27 papers in Soil Science and 20 papers in Economics and Econometrics. Recurrent topics in Daniel Clarke's work include Agricultural risk and resilience (27 papers), Bioinformatics and Genomic Networks (16 papers) and Insurance and Financial Risk Management (13 papers). Daniel Clarke is often cited by papers focused on Agricultural risk and resilience (27 papers), Bioinformatics and Genomic Networks (16 papers) and Insurance and Financial Risk Management (13 papers). Daniel Clarke collaborates with scholars based in United States, United Kingdom and France. Daniel Clarke's co-authors include Avi Ma’ayan, John Erol Evangelista, Alexander Lachmann, Zhuorui Xie, Maxim V. Kuleshov, Kathleen M. Jagodnik, Minji Jeon, Eryk Kropiwnicki, Megan L. Wojciechowicz and Sherry L. Jenkins and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Daniel Clarke

67 papers receiving 3.1k citations

Hit Papers

Gene Set Knowledge Discovery with Enrichr 2021 2026 2022 2024 2021 500 1000 1.5k
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. Gene Set Knowledge Discovery with Enrichr
    2021 1.7k citations Zhuorui Xie, Allison Bailey et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Clarke United States 18 1.4k 540 370 361 338 71 3.2k
Steven W. Martin United States 27 1.1k 0.8× 145 0.3× 79 0.2× 169 0.5× 352 1.0× 106 3.0k
Hans Jansen Netherlands 42 1.7k 1.2× 138 0.3× 529 1.4× 242 0.7× 346 1.0× 197 7.0k
Markus Brückner Germany 29 229 0.2× 161 0.3× 83 0.2× 1.0k 2.8× 221 0.7× 103 3.3k
Chen Ye China 33 1.3k 1.0× 92 0.2× 607 1.6× 33 0.1× 96 0.3× 259 4.4k
Ying Lin China 25 880 0.6× 37 0.1× 186 0.5× 89 0.2× 202 0.6× 119 2.1k
Utz Johann Pape United States 19 3.8k 2.8× 33 0.1× 280 0.8× 180 0.5× 200 0.6× 87 5.3k
Shan Shan China 35 1.6k 1.2× 21 0.0× 503 1.4× 684 1.9× 408 1.2× 202 4.8k
Yichen Wang China 33 1.4k 1.0× 30 0.1× 281 0.8× 66 0.2× 423 1.3× 223 3.8k
Biplab Dasgupta United States 31 1.9k 1.4× 48 0.1× 467 1.3× 62 0.2× 229 0.7× 72 4.4k
Yunqiang Liu China 26 686 0.5× 47 0.1× 208 0.6× 598 1.7× 46 0.1× 139 2.5k

Countries citing papers authored by Daniel Clarke

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Clarke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Clarke

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Clarke. A scholar is included among the top collaborators of Daniel Clarke 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 Daniel Clarke. Daniel Clarke 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.
Marino, Giacomo B., John Erol Evangelista, Daniel Clarke, & Avi Ma’ayan. (2025). L2S2: chemical perturbation and CRISPR KO LINCS L1000 signature search engine. Nucleic Acids Research. 53(W1). W338–W350.
2.
Marino, Giacomo B., et al.. (2025). GeneSetCart: assembling, augmenting, combining, visualizing, and analyzing gene sets. GigaScience. 14. 1 indexed citations
3.
Clarke, Daniel, et al.. (2024). Rummagene: massive mining of gene sets from supporting materials of biomedical research publications. Communications Biology. 7(1). 482–482. 11 indexed citations
4.
Marino, Giacomo B., et al.. (2024). RummaGEO: Automatic mining of human and mouse gene sets from GEO. Patterns. 5(10). 101072–101072. 5 indexed citations
5.
Clarke, Daniel, et al.. (2024). Harmonizome 3.0: integrated knowledge about genes and proteins from diverse multi-omics resources. Nucleic Acids Research. 53(D1). D1016–D1028. 24 indexed citations
6.
Evangelista, John Erol, Zhuorui Xie, Giacomo B. Marino, et al.. (2023). Enrichr-KG: bridging enrichment analysis across multiple libraries. Nucleic Acids Research. 51(W1). W168–W179. 78 indexed citations
7.
Marino, Giacomo B., et al.. (2023). GeneRanger and TargetRanger: processed gene and protein expression levels across cells and tissues for target discovery. Nucleic Acids Research. 51(W1). W213–W224. 5 indexed citations
8.
Marino, Giacomo B., Zhuorui Xie, Kathleen M. Jagodnik, et al.. (2023). D2H2: diabetes data and hypothesis hub. Bioinformatics Advances. 3(1). vbad178–vbad178. 2 indexed citations
9.
Xie, Zhuorui, et al.. (2023). Computational screen to identify potential targets for immunotherapeutic identification and removal of senescence cells. Aging Cell. 22(6). e13809–e13809. 6 indexed citations
10.
Evangelista, John Erol, Daniel Clarke, Zhuorui Xie, et al.. (2023). Toxicology knowledge graph for structural birth defects. SHILAP Revista de lepidopterología. 3(1). 98–98. 14 indexed citations
11.
Lachmann, Alexander, et al.. (2023). PrismEXP: gene annotation prediction from stratified gene-gene co-expression matrices. PeerJ. 11. e14927–e14927. 7 indexed citations
12.
Clarke, Daniel, Alison W. Rebman, Jinshui Fan, et al.. (2022). Gene set predictor for post-treatment Lyme disease. Cell Reports Medicine. 3(11). 100816–100816. 4 indexed citations
13.
Clarke, Daniel & Stefan Dercon. (2021). Directory of Open access Books (OAPEN Foundation). 13 indexed citations
14.
Borziak, Kirill, et al.. (2020). Towards Intelligent Integration and Sharing of Stem Cell Research Data. Studies in health technology and informatics. 272. 334–337. 4 indexed citations
15.
Kuleshov, Maxim V., Daniel Stein, Daniel Clarke, et al.. (2020). The COVID-19 Drug and Gene Set Library. Patterns. 1(6). 100090–100090. 48 indexed citations
16.
17.
Clarke, Daniel, Richard Carpenter, Sommarat Chantarat, et al.. (2015). Kenya - Toward a national crop and livestock insurance program : background report. 1–104. 6 indexed citations
18.
Clarke, Daniel & Ruth Vargas Hill. (2013). Insuring countries against natural disasters: Pool rules:. RePEc: Research Papers in Economics. 1 indexed citations
19.
Berhane, Guush, et al.. (2013). Insuring against the weather. RePEc: Research Papers in Economics. 4 indexed citations
20.
Werner, Aleksandra, Daniel Clarke, & Stefan Kraan. (2004). Strategic Review and the Feasibility of Seaweed Aquaculture in Ireland. Marine Institute Open Access Repository (Marine Institute). 21 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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2026