Mila Lamb

742 citations
5 papers · 84 · h-index 5

Impact in

    • Protein Structure and Dynamics
    • Chemical Synthesis and Analysis
    • RNA and protein synthesis mechanisms
    • Machine Learning in Bioinformatics
    • Biochemical and Structural Characterization
    • Supramolecular Self-Assembly in Materials

Papers in

    • Protein Structure and Dynamics 3
    • Chemical Synthesis and Analysis 2
    • RNA and protein synthesis mechanisms 2
    • Glycosylation and Glycoproteins Research 1
    • Peptidase Inhibition and Analysis 2

Mila Lamb

5 papers receiving 79 citations

Peers

Mila Lamb
Comparison fields: 5 of 37
  • Molecular Biology 56
  • Biomaterials 10
  • Computational Theory and Mathematics 6
  • Biotechnology 3
  • Materials Chemistry 11
Replace Liang Fang with:
Liang Fang United States
Kathryn Tunyasuvunakool United Kingdom
Ana O. Tiroli‐Cepeda Brazil
Nadia Znassi Canada
Evans Brackenbrough United States
Lydia L. Good United States
Tongchuan Zhang China
Bin Ren China
Maoying Wu China
Merrick Pierson Smela United States
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Citations per field
00.5×5.3×
Liang Fang · 1×
Citations per year

Countries citing papers authored by Mila Lamb

Since Specialization
Citations

This map shows the geographic impact of Mila Lamb'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 Mila Lamb with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mila Lamb more than expected).

Fields of papers citing papers by Mila Lamb

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mila Lamb. 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 Mila Lamb. The network helps show where Mila Lamb may publish in the future.

Co-authors

The 25 scholars most cited alongside Mila Lamb, 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 Mila Lamb Line = papers co-authored together Mila Lamb links everyone, so they are left out of the graph.

All Works

5 of 5 papers shown
#Work
1 202525
2 202420
3 202318
4 202416
5 20225

About Mila Lamb

Mila Lamb is a scholar working on Molecular Biology, Oncology, Organic Chemistry, Ecology and Physiology, having authored 5 papers that have together received 84 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (3 papers), Peptidase Inhibition and Analysis (2 papers), Chemical Synthesis and Analysis (2 papers), RNA and protein synthesis mechanisms (2 papers), Alzheimer's disease research and treatments (1 paper), Glycosylation and Glycoproteins Research (1 paper), Click Chemistry and Applications (1 paper) and Enzyme Structure and Function (1 paper). The work is most often cited by research in Molecular Biology (56 citations), Biomaterials (10 citations), Computational Theory and Mathematics (6 citations), Biotechnology (3 citations) and Materials Chemistry (11 citations). Mila Lamb has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include David Baker, Asim K. Bera, Xinting Li, Alex Kang, Maggie Ahlrichs, TJ Brunette, Lauren Carter, Paul M. Levine, Hannah Nguyen and Lance Stewart. Their work appears in journals such as Nature Chemical Biology, Nature Communications, ACS Chemical Biology and Nature Chemistry.

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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