Ashley Cliff

449 total citations
11 papers, 227 citations indexed

About

Ashley Cliff is a scholar working on Molecular Biology, Computer Networks and Communications and Information Systems and Management. According to data from OpenAlex, Ashley Cliff has authored 11 papers receiving a total of 227 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 2 papers in Computer Networks and Communications and 2 papers in Information Systems and Management. Recurrent topics in Ashley Cliff's work include Gene Regulatory Network Analysis (2 papers), Distributed and Parallel Computing Systems (2 papers) and Bioinformatics and Genomic Networks (2 papers). Ashley Cliff is often cited by papers focused on Gene Regulatory Network Analysis (2 papers), Distributed and Parallel Computing Systems (2 papers) and Bioinformatics and Genomic Networks (2 papers). Ashley Cliff collaborates with scholars based in United States, China and Italy. Ashley Cliff's co-authors include Daniel Jacobson, Jonathon Romero, David Kainer, Angelica M. Walker, Michael R. Garvin, Piet Jones, James B. Brown, Manesh Shah, Érica T. Prates and Jared Streich and has published in prestigious journals such as Annals of Surgery, Journal of Neurophysiology and Genome biology.

In The Last Decade

Ashley Cliff

11 papers receiving 222 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ashley Cliff United States 8 53 37 33 28 24 11 227
Jonathon Romero United States 9 75 1.4× 50 1.4× 123 3.7× 30 1.1× 24 1.0× 10 382
Antonio Massaro Italy 10 32 0.6× 20 0.5× 4 0.1× 48 1.7× 38 1.6× 23 294
Valérie Defaweux Belgium 12 112 2.1× 39 1.1× 13 0.4× 12 0.4× 34 1.4× 26 345
Nilesh Kumar India 11 176 3.3× 21 0.6× 86 2.6× 39 1.4× 10 0.4× 51 382
E. V. Ignatieva Russia 11 226 4.3× 30 0.8× 36 1.1× 19 0.7× 46 412
Patrick D. Allen United States 7 104 2.0× 23 0.6× 8 0.2× 14 0.5× 3 0.1× 22 411
Liudmila S. Mainzer United States 6 139 2.6× 11 0.3× 49 1.5× 10 0.4× 12 259
Jonathan F. Russell United States 14 114 2.2× 11 0.3× 4 0.1× 12 0.4× 2 0.1× 54 819
Micah Thornton United States 7 112 2.1× 14 0.4× 51 1.5× 25 0.9× 3 0.1× 17 276
Andrei V. Konstantinov Russia 9 54 1.0× 6 0.2× 15 0.5× 6 0.2× 5 0.2× 60 213

Countries citing papers authored by Ashley Cliff

Since Specialization
Citations

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

Fields of papers citing papers by Ashley Cliff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ashley Cliff

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

All Works

11 of 11 papers shown
1.
Lee, Jaewon J., P. Chan, Ashley B. Morrison, et al.. (2024). Tumor-intrinsic and Cancer-associated Fibroblast Subtypes Independently Predict Outcomes in Pancreatic Cancer. Annals of Surgery. 280(4). 659–666. 1 indexed citations
2.
Walker, Angelica M., Kyle A. Sullivan, Ashley Cliff, et al.. (2023). Using iterative random forest to find geospatial environmental and Sociodemographic predictors of suicide attempts. Frontiers in Psychiatry. 14. 1178633–1178633. 5 indexed citations
3.
Ko, Kang I., Zhen Huang, Y Horiuchi, et al.. (2022). NF-κB perturbation reveals unique immunomodulatory functions in Prx1 + fibroblasts that promote development of atopic dermatitis. Science Translational Medicine. 14(630). eabj0324–eabj0324. 47 indexed citations
4.
Walker, Angelica M., Ashley Cliff, Jonathon Romero, et al.. (2022). Evaluating the performance of random forest and iterative random forest based methods when applied to gene expression data. Computational and Structural Biotechnology Journal. 20. 3372–3386. 30 indexed citations
5.
Cope, Kevin R., Érica T. Prates, John I. Miller, et al.. (2022). Exploring the role of plant lysin motif receptor-like kinases in regulating plant-microbe interactions in the bioenergy crop Populus. Computational and Structural Biotechnology Journal. 21. 1122–1139. 9 indexed citations
6.
Mehta, Kshitij, Ashley Cliff, Frédéric Suter, et al.. (2022). Running Ensemble Workflows at Extreme Scale: Lessons Learned and Path Forward. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 284–294. 4 indexed citations
7.
Wolf, Matthew, Jeremy Logan, Kshitij Mehta, et al.. (2021). Reusability First: Toward FAIR Workflows. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 444–455. 10 indexed citations
8.
Streich, Jared, Jonathon Romero, David Kainer, et al.. (2020). Can exascale computing and explainable artificial intelligence applied to plant biology deliver on the United Nations sustainable development goals?. Current Opinion in Biotechnology. 61. 217–225. 39 indexed citations
9.
Garvin, Michael R., Érica T. Prates, Piet Jones, et al.. (2020). Potentially adaptive SARS-CoV-2 mutations discovered with novel spatiotemporal and explainable AI models. Genome biology. 21(1). 304–304. 43 indexed citations
10.
Zhang, Xiaoying, Joshua Price, Piet Jones, et al.. (2020). Neurotransmitter networks in mouse prefrontal cortex are reconfigured by isoflurane anesthesia. Journal of Neurophysiology. 123(6). 2285–2296. 16 indexed citations
11.
Cliff, Ashley, Jonathon Romero, David Kainer, et al.. (2019). A High-Performance Computing Implementation of Iterative Random Forest for the Creation of Predictive Expression Networks. Genes. 10(12). 996–996. 23 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