Daniel Hurley
Impact in
- Neurology top 10%
- Barrier Structure and Function Studies
- Obstetrics and Gynecology top 10%
- Pregnancy and preeclampsia studies
Papers in
-
- Gene Regulatory Network Analysis 4
- Genomics and Chromatin Dynamics 3
- Bioinformatics and Genomic Networks 2
-
- MicroRNA in disease regulation 2
- Co-authors
- Edmund J. Crampin (13 shared papers)Cristin Gregor Print (10 shared papers)David Budden (5 shared papers)Joe Cursons (6 shared papers)Justin Rustenhoven (1 shared paper)Robyn L. Oldfield (1 shared paper)Deidre Jansson (1 shared paper)Sheryl Xia Feng (1 shared paper)
- Journals
- PLoS ONE (3 papers)Briefings in Bioinformatics (2 papers)Epigenetics & Chromatin (2 papers)Reproduction (1 paper)Journal of Neurochemistry (1 paper)
- Partner nations
- New ZealandAustraliaJapan
In The Last Decade
Daniel Hurley
25 papers receiving 790 citations
Peers
Comparison fields: 5 of 57
- Neurology 61
- Obstetrics and Gynecology 46
- Molecular Biology 188
- Oncology 52
- Cancer Research 29
Countries citing papers authored by Daniel Hurley
This map shows the geographic impact of Daniel Hurley'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 Hurley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Hurley more than expected).
Fields of papers citing papers by Daniel Hurley
This network shows the impact of papers produced by Daniel Hurley. 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 Hurley. The network helps show where Daniel Hurley may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Hurley, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 140 | |
| 2 | 2017 | 97 | |
| 3 | 2011 | 65 | |
| 4 | 2018 | 44 | |
| 5 | 2015 | 43 | |
| 6 | 2021 | 43 | |
| 7 | 2015 | 40 | |
| 8 | 2013 | 36 | |
| 9 | 2016 | 36 | |
| 10 | 2012 | 30 | |
| 11 | 2014 | 30 | |
| 12 | 2016 | 30 | |
| 13 | 2014 | 29 | |
| 14 | 2012 | 25 | |
| 15 | 2014 | 23 | |
| 16 | 2016 | 21 | |
| 17 | 2014 | 18 | |
| 18 | 2013 | 15 | |
| 19 | 2014 | 10 | |
| 20 | 2015 | 6 |
About Daniel Hurley
Daniel Hurley is a scholar working on Molecular Biology, Cancer Research, Toxicology, Information Systems and Management and Neurology, having authored 25 papers that have together received 795 indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (4 papers), Genomics and Chromatin Dynamics (3 papers), MicroRNA in disease regulation (2 papers), Bioinformatics and Genomic Networks (2 papers), Bioactive Compounds and Antitumor Agents (1 paper), Plant Molecular Biology Research (1 paper), Neuroinflammation and Neurodegeneration Mechanisms (1 paper) and Lymphatic System and Diseases (1 paper). The work is most often cited by research in Neurology (61 citations), Obstetrics and Gynecology (46 citations), Molecular Biology (188 citations), Oncology (52 citations) and Cancer Research (29 citations). Daniel Hurley has collaborated with scholars based in New Zealand, Australia and Japan. Frequent co-authors include Edmund J. Crampin, Cristin Gregor Print, David Budden, Joe Cursons, Justin Rustenhoven, Robyn L. Oldfield, Deidre Jansson, Sheryl Xia Feng, Mike Dragunow and Richard L. M. Faull. Their work appears in journals such as PLoS ONE, Briefings in Bioinformatics, Epigenetics & Chromatin, Reproduction and Journal of Neurochemistry.
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.