Lora Mak
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
- Molecular Biology top 10%
- Bioinformatics and Genomic Networks
- Protein Structure and Dynamics
- Receptor Mechanisms and Signaling
- Chemical Synthesis and Analysis
- Metabolomics and Mass Spectrometry Studies
Papers in
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- Computational Drug Discovery Methods 7
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- Metabolomics and Mass Spectrometry Studies 4
- Bioinformatics and Genomic Networks 3
- Co-authors
- George Papadatos (1 shared paper)Anne Hersey (1 shared paper)Michał Nowotka (1 shared paper)Yvonne Light (1 shared paper)Mark Davies (1 shared paper)Louisa J. Bellis (1 shared paper)Jon Chambers (1 shared paper)John P. Overington (1 shared paper)
- Journals
- Current Pharmaceutical Design (3 papers)Journal of Cheminformatics (1 paper)Journal of Molecular Graphics and Modelling (1 paper)Nucleic Acids Research (1 paper)Molecular Plant-Microbe Interactions (1 paper)
- Partner nations
- United KingdomUnited StatesNetherlands
In The Last Decade
Lora Mak
7 papers receiving 1.3k citations
Lora Mak's Hit Papers
Peers
Comparison fields: 5 of 114
- Computational Theory and Mathematics 865
- Molecular Biology 817
- Pharmacology 179
- Pharmacology 90
- Spectroscopy 83
Countries citing papers authored by Lora Mak
This map shows the geographic impact of Lora Mak'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 Lora Mak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lora Mak more than expected).
Fields of papers citing papers by Lora Mak
This network shows the impact of papers produced by Lora Mak. 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 Lora Mak. The network helps show where Lora Mak may publish in the future.
Co-authors
The 25 scholars most cited alongside Lora Mak, 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 | The ChEMBL bioactivity database: an update Hit paper breakdown → | 2013 | 1183 |
| 2 | 2007 | 52 | |
| 3 | 2015 | 48 | |
| 4 | 2012 | 26 | |
| 5 | 2005 | 12 | |
| 6 | 2009 | 5 | |
| 7 | 2012 | 2 | |
| 8 | 2012 | 0 |
About Lora Mak
Lora Mak is a scholar working on Computational Theory and Mathematics, Molecular Biology, Pharmacology, Computer Vision and Pattern Recognition and Oncology, having authored 8 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Metabolomics and Mass Spectrometry Studies (4 papers), Bioinformatics and Genomic Networks (3 papers), Pharmacogenetics and Drug Metabolism (1 paper), Molecular spectroscopy and chirality (1 paper), Image Retrieval and Classification Techniques (1 paper), Plant nutrient uptake and metabolism (1 paper) and Enzyme Structure and Function (1 paper). The work is most often cited by research in Computational Theory and Mathematics (865 citations), Molecular Biology (817 citations), Pharmacology (179 citations), Pharmacology (90 citations) and Spectroscopy (83 citations). Lora Mak has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include George Papadatos, Anne Hersey, Michał Nowotka, Yvonne Light, Mark Davies, Louisa J. Bellis, Jon Chambers, John P. Overington, A. Patrícia Bento and Rita Santos. Their work appears in journals such as Current Pharmaceutical Design, Journal of Cheminformatics, Journal of Molecular Graphics and Modelling, Nucleic Acids Research and Molecular Plant-Microbe Interactions.
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.