David Becerra
Impact in
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- Computational Drug Discovery Methods
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- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Microbial Metabolic Engineering and Bioproduction
Papers in
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- Protein Structure and Dynamics 5
- Machine Learning in Bioinformatics 4
- Genomics and Phylogenetic Studies 3
- RNA and protein synthesis mechanisms 2
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- Algorithms and Data Compression 3
- AI in cancer detection 3
- Co-authors
- Philip M. Kim (3 shared papers)Carles Corbi‐Verge (2 shared papers)Albert Perez‐Riba (2 shared papers)Alexey Strokach (2 shared papers)Jérôme Waldispühl (3 shared papers)Luís Fernando Niño (4 shared papers)Luis F. G. Sarmenta (1 shared paper)Pedro A. Valiente (1 shared paper)
- Journals
- Pattern Analysis and Applications (1 paper)Neuro-Oncology (1 paper)The Journal of Organic Chemistry (1 paper)Nature Communications (1 paper)Genome biology (1 paper)
- Partner nations
- ColombiaUnited StatesCanada
In The Last Decade
David Becerra
15 papers receiving 202 citations
Peers
Comparison fields: 5 of 68
- Computational Theory and Mathematics 47
- Molecular Biology 128
- Computer Science Applications 9
- Artificial Intelligence 33
- Materials Chemistry 39
Countries citing papers authored by David Becerra
This map shows the geographic impact of David Becerra'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 Becerra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Becerra more than expected).
Fields of papers citing papers by David Becerra
This network shows the impact of papers produced by David Becerra. 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 Becerra. The network helps show where David Becerra may publish in the future.
Co-authors
The 25 scholars most cited alongside David Becerra, 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 | 2020 | 128 | |
| 2 | 2013 | 18 | |
| 3 | 2010 | 15 | |
| 4 | 2011 | 10 | |
| 5 | 2025 | 7 | |
| 6 | 2019 | 6 | |
| 7 | 2020 | 6 | |
| 8 | 2021 | 3 | |
| 9 | 2010 | 3 | |
| 10 | 2024 | 2 | |
| 11 | Un Modelo de Asignación de Recursos a Rutas en el Sistema de Transporte Masivo Transmilenio | 2008 | 2 |
| 12 | 2009 | 2 | |
| 13 | 2024 | 2 | |
| 14 | 2024 | 1 | |
| 15 | 2010 | 1 | |
| 16 | 2024 | 0 | |
| 17 | 2021 | 0 | |
| 18 | 2023 | 0 | |
| 19 | A Multiobjective Approach to the Weighted Longest Common Subsequence Problem | 2012 | 0 |
About David Becerra
David Becerra is a scholar working on Molecular Biology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computational Theory and Mathematics and Materials Chemistry, having authored 19 papers that have together received 206 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), Machine Learning in Bioinformatics (4 papers), Algorithms and Data Compression (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Genomics and Phylogenetic Studies (3 papers), AI in cancer detection (3 papers), RNA and protein synthesis mechanisms (2 papers) and Enzyme Structure and Function (2 papers). The work is most often cited by research in Computational Theory and Mathematics (47 citations), Molecular Biology (128 citations), Computer Science Applications (9 citations), Artificial Intelligence (33 citations) and Materials Chemistry (39 citations). David Becerra has collaborated with scholars based in Colombia, United States and Canada. Frequent co-authors include Philip M. Kim, Carles Corbi‐Verge, Albert Perez‐Riba, Alexey Strokach, Jérôme Waldispühl, Luís Fernando Niño, Luis F. G. Sarmenta, Pedro A. Valiente, Alexander Butyaev and Mathieu Blanchette. Their work appears in journals such as Pattern Analysis and Applications, Neuro-Oncology, The Journal of Organic Chemistry, Nature Communications and Genome biology.
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.