Daniel R. Hyduke
- Molecular Biology top 2%
- Biomedical Engineering top 2%
- Physiology top 5%
- Cancer Research top 5%
- Genetics top 5%
- Co-authors
- Bernhard Ø. PalssonJoshua A. LermanAli EbrahimNathan E. LewisAarash BordbarJeffrey D. OrthDaniel C. ZielinskiAdam M. Feist
- Topics
- Bioinformatics and Genomic Networks (12 papers)Microbial Metabolic Engineering and Bioproduction (9 papers)Gene expression and cancer classification (8 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryNature Communications
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Daniel R. Hyduke
35 papers receiving 4.7k citations
Hit Papers
Peers
Comparison fields: 5 of 151
- Molecular Biology 3.8k
- Biomedical Engineering 1.2k
- Physiology 481
- Cancer Research 380
- Genetics 363
Countries citing papers authored by Daniel R. Hyduke
This map shows the geographic impact of Daniel R. Hyduke'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 R. Hyduke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel R. Hyduke more than expected).
Fields of papers citing papers by Daniel R. Hyduke
This network shows the impact of papers produced by Daniel R. Hyduke. 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 R. Hyduke. The network helps show where Daniel R. Hyduke may publish in the future.
Co-authorship network of co-authors of Daniel R. Hyduke
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel R. Hyduke. A scholar is included among the top collaborators of Daniel R. Hyduke 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 R. Hyduke. Daniel R. Hyduke is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 31 | |
| 2 | 72 | |
| 3 | 18 | |
| 4 | 128 | |
| 5 | 55 | |
| 6 | 43 | |
| 7 | 337 | |
| 8 | COBRApy: COnstraints-Based Reconstruction and Analysis for Pythonbreakdown → | 841 |
| 9 | 10 | |
| 10 | 137 | |
| 11 | 28 | |
| 12 | 204 | |
| 13 | 15 | |
| 14 | Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0breakdown → | 1340 |
| 15 | 31 | |
| 16 | 93 | |
| 17 | 13 | |
| 18 | 31 | |
| 19 | 117 | |
| 20 | 7 |
About Daniel R. Hyduke
Daniel R. Hyduke is a scholar working on Cancer Research, Biological Psychiatry and Molecular Biology, having authored 35 papers that have together received 4.7k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (12 papers), Microbial Metabolic Engineering and Bioproduction (9 papers) and Gene expression and cancer classification (8 papers). The work is most often cited by research in Molecular Biology (3.8k citations), Biomedical Engineering (1.2k citations) and Cancer Research (380 citations). Daniel R. Hyduke has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Bernhard Ø. Palsson, Joshua A. Lerman, Ali Ebrahim, Nathan E. Lewis, Aarash Bordbar, Jeffrey D. Orth, Daniel C. Zielinski, Adam M. Feist, Richard Que and Ronan M. T. Fleming. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.
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.