Lora Mak

3.9k citations
6 papers · 1.2k · 1 hit paper · h-index 5

Impact in

    • Computational Drug Discovery Methods
    • Bioinformatics and Genomic Networks
    • Protein Structure and Dynamics
    • Receptor Mechanisms and Signaling
    • Chemical Synthesis and Analysis
    • Metabolomics and Mass Spectrometry Studies

Papers in

Lora Mak

6 papers receiving 1.2k citations

Hit Papers

The ChEMBL bioactivity database: an update 2013 · 1.1k citations
1.1k0+4+8Years since publication2505007501000

Peers

Lora Mak
Comparison fields: 5 of 116
  • Computational Theory and Mathematics 836
  • Molecular Biology 829
  • Pharmacology 179
  • Pharmacology 91
  • Biophysics 28
Replace George Nicola with:
George Nicola United States
Felix Krüger United Kingdom
María José Ojeda Spain
Michael Baitaluk United States
Adrià Cereto‐Massagué Spain
Andrea Zaliani Germany
Gavin Harper United Kingdom
Brian Clarke United Kingdom
Christian Lemmen Germany
Andrea Volkamer Germany
Lora Mak relative to George Nicola United States George Nicola's profile →
Citations per field
00.5×3.9×
George Nicola · 1×
Citations per year

Countries citing papers authored by Lora Mak

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Lora Mak Line = papers co-authored together Lora Mak links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown
#Work
1
The ChEMBL bioactivity database: an update
Hit paper breakdown →
20131117
2 200747
3 201546
4 201224
5 200512
6 20122

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 6 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Bioinformatics and Genomic Networks (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Plant-Microbe Interactions and Immunity (1 paper), Molecular spectroscopy and chirality (1 paper), Plant nutrient uptake and metabolism (1 paper), Microbial Natural Products and Biosynthesis (1 paper) and Cancer, Hypoxia, and Metabolism (1 paper). The work is most often cited by research in Computational Theory and Mathematics (836 citations), Molecular Biology (829 citations), Pharmacology (179 citations), Pharmacology (91 citations) and Biophysics (28 citations). Lora Mak has collaborated with scholars based in United Kingdom, Netherlands and United States. Frequent co-authors include Mark Davies, Michał Nowotka, A. Patrícia Bento, Anne Hersey, Louisa J. Bellis, Felix Krüger, Yvonne Light, Rita Santos, Jon Chambers and Anna Gaulton. Their work appears in journals such as Current Pharmaceutical Design, Journal of Molecular Graphics and Modelling, Molecular Plant-Microbe Interactions, Nucleic Acids Research and Journal of Cheminformatics.

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.

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