Mario Latendresse
- Molecular Biology top 1%
- Biomedical Engineering top 2%
- Ecology top 2%
- Plant Science top 5%
- Genetics top 5%
- Co-authors
- Peter D. KarpMarkus KrummenackerSuzanne PaleyRon CaspiIngrid M. KeselerPallavi SubhravetiAnamika KothariCarol A. Fulcher
- Topics
- Microbial Metabolic Engineering and Bioproduction (29 papers)Bioinformatics and Genomic Networks (19 papers)Gene Regulatory Network Analysis (10 papers)
- Partner nations
- United StatesCanadaAustralia
In The Last Decade
Mario Latendresse
46 papers receiving 6.9k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Molecular Biology 5.3k
- Biomedical Engineering 1.0k
- Ecology 951
- Plant Science 624
- Genetics 586
Countries citing papers authored by Mario Latendresse
This map shows the geographic impact of Mario Latendresse'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 Mario Latendresse with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mario Latendresse more than expected).
Fields of papers citing papers by Mario Latendresse
This network shows the impact of papers produced by Mario Latendresse. 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 Mario Latendresse. The network helps show where Mario Latendresse may publish in the future.
Co-authorship network of co-authors of Mario Latendresse
This figure shows the co-authorship network connecting the top 25 collaborators of Mario Latendresse. A scholar is included among the top collaborators of Mario Latendresse 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 Mario Latendresse. Mario Latendresse is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 18 | |
| 3 | 8 | |
| 4 | 4 | |
| 5 | 11 | |
| 6 | 35 | |
| 7 | The MetaCyc database of metabolic pathways and enzymesbreakdown → | 597 |
| 8 | The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databasesbreakdown → | 1906 |
| 9 | 26 | |
| 10 | The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databasesbreakdown → | 867 |
| 11 | 27 | |
| 12 | 457 | |
| 13 | 84 | |
| 14 | 23 | |
| 15 | 98 | |
| 16 | 9 | |
| 17 | 376 | |
| 18 | 136 | |
| 19 | 3 | |
| 20 | 2 |
About Mario Latendresse
Mario Latendresse is a scholar working on Software, Molecular Biology and Hardware and Architecture, having authored 46 papers that have together received 7.0k indexed citations. Recurring topics across this work include Microbial Metabolic Engineering and Bioproduction (29 papers), Bioinformatics and Genomic Networks (19 papers) and Gene Regulatory Network Analysis (10 papers). The work is most often cited by research in Molecular Biology (5.3k citations), Ecology (951 citations) and Endocrinology (125 citations). Mario Latendresse has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Peter D. Karp, Markus Krummenacker, Suzanne Paley, Ron Caspi, Ingrid M. Keseler, Pallavi Subhraveti, Anamika Kothari, Carol A. Fulcher, Quang Ong and Richard Billington. Their work appears in journals such as Nucleic Acids Research, Bioinformatics 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.