David La
Impact in
- Structural Biology top 10%
-
- Protein Structure and Dynamics
- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
Papers in
-
- Protein Structure and Dynamics 12
- Genomics and Phylogenetic Studies 7
- RNA and protein synthesis mechanisms 4
- Machine Learning in Bioinformatics 3
- Bioinformatics and Genomic Networks 3
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- Mass Spectrometry Techniques and Applications 2
- Co-authors
- Daisuke Kihara (8 shared papers)Dennis R. Livesay (7 shared papers)Lee Sael (3 shared papers)Raif M. Rustamov (2 shared papers)Karthik Ramani (2 shared papers)Yi Fang (1 shared paper)Bin Li (1 shared paper)David Baker (2 shared papers)
- Journals
- Proteins Structure Function and Bioinformatics (6 papers)BMC Biology (1 paper)Nature Biotechnology (1 paper)Bioinformatics (1 paper)Nucleic Acids Research (1 paper)
- Partner nations
- United StatesGermanyNetherlands
In The Last Decade
David La
18 papers receiving 790 citations
Peers
Comparison fields: 5 of 95
- Structural Biology 14
- Molecular Biology 571
- Computational Theory and Mathematics 118
- Biotechnology 44
- Radiology, Nuclear Medicine and Imaging 74
Countries citing papers authored by David La
This map shows the geographic impact of David La'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 David La with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David La more than expected).
Fields of papers citing papers by David La
This network shows the impact of papers produced by David La. 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 David La. The network helps show where David La may publish in the future.
Co-authors
The 25 scholars most cited alongside David La, 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 | 2008 | 110 | |
| 2 | 2017 | 103 | |
| 3 | 2017 | 99 | |
| 4 | 2007 | 78 | |
| 5 | 2008 | 70 | |
| 6 | 2009 | 67 | |
| 7 | 2004 | 65 | |
| 8 | 2013 | 41 | |
| 9 | 2011 | 31 | |
| 10 | 2005 | 27 | |
| 11 | 2005 | 25 | |
| 12 | 2011 | 24 | |
| 13 | 2005 | 23 | |
| 14 | 2003 | 19 | |
| 15 | 2020 | 11 | |
| 16 | 2006 | 6 | |
| 17 | 2016 | 4 | |
| 18 | 2025 | 2 | |
| 19 | 2011 | 0 |
About David La
David La is a scholar working on Molecular Biology, Spectroscopy, Biotechnology, Materials Chemistry and Radiology, Nuclear Medicine and Imaging, having authored 19 papers that have together received 805 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (12 papers), Genomics and Phylogenetic Studies (7 papers), RNA and protein synthesis mechanisms (4 papers), Enzyme Structure and Function (4 papers), Machine Learning in Bioinformatics (3 papers), Bioinformatics and Genomic Networks (3 papers), Mass Spectrometry Techniques and Applications (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). The work is most often cited by research in Structural Biology (14 citations), Molecular Biology (571 citations), Computational Theory and Mathematics (118 citations), Biotechnology (44 citations) and Radiology, Nuclear Medicine and Imaging (74 citations). David La has collaborated with scholars based in United States, Germany and Netherlands. Frequent co-authors include Daisuke Kihara, Dennis R. Livesay, Lee Sael, Raif M. Rustamov, Karthik Ramani, Yi Fang, Bin Li, David Baker, Bin Li and Bin Li. Their work appears in journals such as Proteins Structure Function and Bioinformatics, BMC Biology, Nature Biotechnology, Bioinformatics and Nucleic Acids Research.
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.