Tanveer S. Batth
- Molecular Biology top 2%
- Biomedical Engineering top 5%
- Spectroscopy top 1%
- Pharmacology top 2%
- Biotechnology top 2%
- Co-authors
- Christopher J. PetzoldJay D. KeaslingJesper V. OlsenPaul D. AdamsAindrila MukhopadhyayTaek Soon LeeAlyssa M. Redding‐JohansonJorge Alonso-Gutiérrez
- Topics
- Microbial Metabolic Engineering and Bioproduction (17 papers)Advanced Proteomics Techniques and Applications (10 papers)Plant biochemistry and biosynthesis (9 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryNature Communications
- Partner nations
- United StatesDenmarkUnited Kingdom
In The Last Decade
Tanveer S. Batth
41 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Molecular Biology 3.2k
- Biomedical Engineering 709
- Spectroscopy 689
- Pharmacology 364
- Biotechnology 288
Countries citing papers authored by Tanveer S. Batth
This map shows the geographic impact of Tanveer S. Batth'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 Tanveer S. Batth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tanveer S. Batth more than expected).
Fields of papers citing papers by Tanveer S. Batth
This network shows the impact of papers produced by Tanveer S. Batth. 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 Tanveer S. Batth. The network helps show where Tanveer S. Batth may publish in the future.
Co-authorship network of co-authors of Tanveer S. Batth
This figure shows the co-authorship network connecting the top 25 collaborators of Tanveer S. Batth. A scholar is included among the top collaborators of Tanveer S. Batth 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 Tanveer S. Batth. Tanveer S. Batth is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 6 | |
| 3 | 38 | |
| 4 | 29 | |
| 5 | 43 | |
| 6 | 27 | |
| 7 | 41 | |
| 8 | 34 | |
| 9 | An Optimized Shotgun Strategy for the Rapid Generation of Comprehensive Human Proteomesbreakdown → | 353 |
| 10 | 33 | |
| 11 | 30 | |
| 12 | 37 | |
| 13 | 320 | |
| 14 | Engineering dynamic pathway regulation using stress-response promotersbreakdown → | 385 |
| 15 | 145 | |
| 16 | 85 | |
| 17 | 149 | |
| 18 | 128 | |
| 19 | 139 | |
| 20 | 106 |
About Tanveer S. Batth
Tanveer S. Batth is a scholar working on Spectroscopy, Molecular Biology and Pharmacology, having authored 41 papers that have together received 3.8k indexed citations. Recurring topics across this work include Microbial Metabolic Engineering and Bioproduction (17 papers), Advanced Proteomics Techniques and Applications (10 papers) and Plant biochemistry and biosynthesis (9 papers). The work is most often cited by research in Molecular Biology (3.2k citations), Spectroscopy (689 citations) and Biotechnology (288 citations). Tanveer S. Batth has collaborated with scholars based in United States, Denmark and United Kingdom. Frequent co-authors include Christopher J. Petzold, Jay D. Keasling, Jesper V. Olsen, Paul D. Adams, Aindrila Mukhopadhyay, Taek Soon Lee, Alyssa M. Redding‐Johanson, Jorge Alonso-Gutiérrez, Chiara Francavilla and Edward E. K. Baidoo. 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.