Hema Bye‐A‐Jee
Impact in
- Molecular Biology top 0.5%
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
- RNA and protein synthesis mechanisms
- Protein Structure and Dynamics
- Machine Learning in Bioinformatics
- RNA modifications and cancer
- RNA Research and Splicing
- Aging top 5%
Papers in
-
- Genomics and Phylogenetic Studies 6
- Biomedical Text Mining and Ontologies 5
- Bioinformatics and Genomic Networks 5
- Microbial Metabolic Engineering and Bioproduction 2
- Machine Learning in Bioinformatics 2
- Genetics, Bioinformatics, and Biomedical Research 2
-
- Advanced Proteomics Techniques and Applications 2
- Co-authors
- Dominic J. Wells (1 shared paper)Paul S. Sharp (1 shared paper)Michele Magrane (2 shared papers)Cecilia N. Arighi (1 shared paper)Zhiyong Lu (1 shared paper)Maria Livia Famiglietti (1 shared paper)Bernd Roechert (1 shared paper)Alex Bateman (1 shared paper)
- Journals
- Nucleic Acids Research (6 papers)Bioinformatics (2 papers)Molecular Therapy (1 paper)FEBS Journal (1 paper)Genetics (1 paper)
- Partner nations
- United KingdomUnited StatesSwitzerland
In The Last Decade
Hema Bye‐A‐Jee
15 papers receiving 13.5k citations
Hema Bye‐A‐Jee's Hit Papers
Peers
Comparison fields: 5 of 179
- Molecular Biology 8.0k
- Aging 89
- Genetics 1.4k
- Cancer Research 642
- Computational Theory and Mathematics 787
Countries citing papers authored by Hema Bye‐A‐Jee
This map shows the geographic impact of Hema Bye‐A‐Jee'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 Hema Bye‐A‐Jee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hema Bye‐A‐Jee more than expected).
Fields of papers citing papers by Hema Bye‐A‐Jee
This network shows the impact of papers produced by Hema Bye‐A‐Jee. 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 Hema Bye‐A‐Jee. The network helps show where Hema Bye‐A‐Jee may publish in the future.
Co-authors
The 25 scholars most cited alongside Hema Bye‐A‐Jee, 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 | UniProt: the universal protein knowledgebase in 2021 Hit paper breakdown → | 2020 | 4788 |
| 2 | UniProt: the Universal Protein Knowledgebase in 2023 Hit paper breakdown → | 2022 | 3877 |
| 3 | The Gene Ontology resource: enriching a GOld mine Hit paper breakdown → | 2020 | 2404 |
| 4 | The Gene Ontology knowledgebase in 2023 Hit paper breakdown → | 2023 | 1509 |
| 5 | UniProt: the Universal Protein Knowledgebase in 2025 Hit paper breakdown → | 2024 | 738 |
| 6 | 2017 | 97 | |
| 7 | 2018 | 93 | |
| 8 | 2010 | 65 | |
| 9 | 2020 | 54 | |
| 10 | 2021 | 43 | |
| 11 | 2018 | 25 | |
| 12 | 2025 | 12 | |
| 13 | 2020 | 4 | |
| 14 | 2017 | 1 | |
| 15 | 2023 | 1 | |
| 16 | 2024 | 1 |
About Hema Bye‐A‐Jee
Hema Bye‐A‐Jee is a scholar working on Molecular Biology, Spectroscopy, Aging, Information Systems and Biochemistry, having authored 16 papers that have together received 13.7k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (6 papers), Biomedical Text Mining and Ontologies (5 papers), Bioinformatics and Genomic Networks (5 papers), Research Data Management Practices (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers), Advanced Proteomics Techniques and Applications (2 papers), Machine Learning in Bioinformatics (2 papers) and Genetics, Bioinformatics, and Biomedical Research (2 papers). The work is most often cited by research in Molecular Biology (8.0k citations), Aging (89 citations), Genetics (1.4k citations), Cancer Research (642 citations) and Computational Theory and Mathematics (787 citations). Hema Bye‐A‐Jee has collaborated with scholars based in United Kingdom, United States and Switzerland. Frequent co-authors include Dominic J. Wells, Paul S. Sharp, Michele Magrane, Cecilia N. Arighi, Zhiyong Lu, Maria Livia Famiglietti, Bernd Roechert, Alex Bateman, Emmanuel Boutet and Chih-Hsuan Wei. Their work appears in journals such as Nucleic Acids Research, Bioinformatics, Molecular Therapy, FEBS Journal and Genetics.
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.