Eva Huala
- Plant Science top 0.2%
- Plant nutrient uptake and metabolism 9
- Plant Molecular Biology Research 7
- Molecular Biology top 1%
- Genomics and Phylogenetic Studies 14
- Biomedical Text Mining and Ontologies 8
- Photosynthetic Processes and Mechanisms 6
- Bioinformatics and Genomic Networks 5
- Machine Learning in Bioinformatics 3
- Horticulture top 5%
- Endocrinology top 5%
- Genetics top 5%
-
- Semantic Web and Ontologies 5
- Co-authors
- Tanya BerardiniDonghui LiWinslow R. BriggsM. Garcia-HernandezFrederick M. AusubelDavid SwarbreckLeonore ReiserI. M. Sussex
- Partner nations
- United StatesUnited KingdomSaudi Arabia
In The Last Decade
Eva Huala
33 papers receiving 6.1k citations
Hit Papers
Peers
Comparison fields: 5 of 135
- Plant Science 4.2k
- Molecular Biology 4.6k
- Horticulture 33
- Endocrinology 127
- Genetics 648
Countries citing papers authored by Eva Huala
This map shows the geographic impact of Eva Huala'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 Eva Huala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eva Huala more than expected).
Fields of papers citing papers by Eva Huala
This network shows the impact of papers produced by Eva Huala. 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 Eva Huala. The network helps show where Eva Huala may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Eva Huala, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 32 | |
| 2 | 2015 | 38 | |
| 3 | 2013 | 7 | |
| 4 | 2012 | 74 | |
| 5 | 2012 | 2 | |
| 6 | 2012 | 28 | |
| 7 | 2012 | 116 | |
| 8 | 2012 | 13 | |
| 9 | 2012 | 1 | |
| 10 | 2012 | 14 | |
| 11 | The Arabidopsis Information Resource (TAIR): improved gene annotation and new toolsbreakdown → | 2011 | 1676 |
| 12 | 2010 | 33 | |
| 13 | The Arabidopsis Information Resource (TAIR): gene structure and function annotationbreakdown → | 2007 | 774 |
| 14 | 2004 | 13 | |
| 15 | 2004 | 18 | |
| 16 | 2001 | 430 | |
| 17 | Arabidopsis NPH1: A Protein Kinase with a Putative Redox-Sensing Domainbreakdown → | 1997 | 581 |
| 18 | 1993 | 55 | |
| 19 | 1993 | 17 | |
| 20 | 1984 | 33 |
About Eva Huala
Eva Huala is a scholar working on Plant Science, Molecular Biology, Pollution, Biochemistry and Artificial Intelligence, having authored 33 papers that have together received 6.3k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (14 papers), Plant nutrient uptake and metabolism (9 papers), Biomedical Text Mining and Ontologies (8 papers), Plant Molecular Biology Research (7 papers), Photosynthetic Processes and Mechanisms (6 papers), Bioinformatics and Genomic Networks (5 papers), Semantic Web and Ontologies (5 papers) and Machine Learning in Bioinformatics (3 papers). The work is most often cited by research in Plant Science (4.2k citations), Molecular Biology (4.6k citations), Horticulture (33 citations), Endocrinology (127 citations) and Genetics (648 citations). Eva Huala has collaborated with scholars based in United States, United Kingdom and Saudi Arabia. Frequent co-authors include Tanya Berardini, Donghui Li, Winslow R. Briggs, M. Garcia-Hernandez, Frederick M. Ausubel, David Swarbreck, Leonore Reiser, I. M. Sussex, Christopher Wilks and Robert Müller. Their work appears in journals such as Database, The Plant Cell, Nucleic Acids Research, Journal of Bacteriology and PLANT PHYSIOLOGY.
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.