Lloyd M. Smith

30.7k total citations · 4 hit papers
349 papers, 21.8k citations indexed

About

Lloyd M. Smith is a scholar working on Molecular Biology, Spectroscopy and Biomedical Engineering. According to data from OpenAlex, Lloyd M. Smith has authored 349 papers receiving a total of 21.8k indexed citations (citations by other indexed papers that have themselves been cited), including 216 papers in Molecular Biology, 110 papers in Spectroscopy and 46 papers in Biomedical Engineering. Recurrent topics in Lloyd M. Smith's work include Mass Spectrometry Techniques and Applications (87 papers), Advanced Proteomics Techniques and Applications (71 papers) and Advanced biosensing and bioanalysis techniques (61 papers). Lloyd M. Smith is often cited by papers focused on Mass Spectrometry Techniques and Applications (87 papers), Advanced Proteomics Techniques and Applications (71 papers) and Advanced biosensing and bioanalysis techniques (61 papers). Lloyd M. Smith collaborates with scholars based in United States, Italy and Switzerland. Lloyd M. Smith's co-authors include William R. Morrison, Mark Scalf, Michael R. Shortreed, Brian L. Frey, Robert J. Hamers, Timothy J. Griffin, Michael S. Westphall, Leroy Hood, Todd Strother and John A. Luckey and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Lloyd M. Smith

341 papers receiving 20.7k citations

Hit Papers

Preparation of fatty acid... 1964 2026 1984 2005 1964 1986 2002 2024 1000 2.0k 3.0k 4.0k 5.0k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Lloyd M. Smith 10.8k 3.7k 3.6k 3.3k 1.9k 349 21.8k
René Kizek 6.1k 0.6× 945 0.3× 3.7k 1.0× 3.0k 0.9× 2.4k 1.2× 596 19.8k
Jagannathan 13.4k 1.2× 1.1k 0.3× 1.4k 0.4× 884 0.3× 455 0.2× 4 24.3k
D. Chapman 13.8k 1.3× 2.7k 0.7× 784 0.2× 1.3k 0.4× 597 0.3× 303 20.2k
Pier Giorgio Righetti 12.8k 1.2× 8.2k 2.2× 827 0.2× 8.7k 2.6× 1.7k 0.9× 719 25.9k
Mary Osborn 27.5k 2.6× 1.3k 0.4× 1.8k 0.5× 1.4k 0.4× 376 0.2× 315 48.2k
Ernesto Carafoli 24.4k 2.3× 1.4k 0.4× 2.2k 0.6× 715 0.2× 700 0.4× 493 33.3k
Charles Tanford 21.6k 2.0× 5.2k 1.4× 949 0.3× 2.3k 0.7× 755 0.4× 212 34.2k
K. Weber 22.0k 2.0× 1.2k 0.3× 1.4k 0.4× 1.1k 0.3× 302 0.2× 231 38.0k
Serge N. Timasheff 14.9k 1.4× 2.5k 0.7× 843 0.2× 1.4k 0.4× 478 0.2× 217 22.8k
Stanford Moore 17.0k 1.6× 2.8k 0.8× 2.4k 0.7× 884 0.3× 374 0.2× 90 32.3k

Countries citing papers authored by Lloyd M. Smith

Since Specialization
Citations

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

Fields of papers citing papers by Lloyd M. Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lloyd M. Smith. 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 Lloyd M. Smith. The network helps show where Lloyd M. Smith may publish in the future.

Co-authorship network of co-authors of Lloyd M. Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Lloyd M. Smith. A scholar is included among the top collaborators of Lloyd M. Smith based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lloyd M. Smith. Lloyd M. Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Qingyang, et al.. (2025). Chemoselective Characterization of New Extracellular Matrix Deposition in Bioengineered Tumor Tissues. Advanced Materials. 37(47). e05445–e05445.
2.
Kim, Sang Hwa, Eric N. Anderson, Nandini Ramesh, et al.. (2023). Axon guidance genes modulate neurotoxicity of ALS-associated UBQLN2. eLife. 12. 9 indexed citations
3.
Frey, Brian L., et al.. (2023). Cysteine Counting via Isotopic Chemical Labeling for Intact Mass Proteoform Identifications in Tissue. Analytical Chemistry. 95(41). 15245–15253. 1 indexed citations
4.
Scalf, Mark, et al.. (2022). Multi-step recognition of potential 5' splice sites by the Saccharomyces cerevisiae U1 snRNP. eLife. 11. 7 indexed citations
5.
Becker, Jordan T., et al.. (2021). Identification of host proteins differentially associated with HIV-1 RNA splice variants. eLife. 10. 23 indexed citations
6.
Yau, Belinda, Alexis Díaz‐Vegas, Elise J. Needham, et al.. (2021). Proteomic pathways to metabolic disease and type 2 diabetes in the pancreatic islet. iScience. 24(10). 103099–103099. 11 indexed citations
7.
Miller, Rachel, Ben T. Jordan, Erin D. Jeffery, et al.. (2021). Enhanced Protein Isoform Characterization Through Long-Read Proteogenomics - Jurkat Samples and Reference Data. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
8.
Smith, Lloyd M., Jeffrey N. Agar, Julia Chamot‐Rooke, et al.. (2021). The Human Proteoform Project: Defining the human proteome. Science Advances. 7(46). eabk0734–eabk0734. 145 indexed citations
9.
Cesnik, Anthony J., Rachel Miller, Lei Lü, et al.. (2020). Spritz: A Proteogenomic Database Engine. Journal of Proteome Research. 20(4). 1826–1834. 22 indexed citations
10.
Mehta, Subina, Robert J. Millikin, Ignacio Eguinoa, et al.. (2020). Precursor Intensity-Based Label-Free Quantification Software Tools for Proteomic and Multi-Omic Analysis within the Galaxy Platform. Proteomes. 8(3). 15–15. 10 indexed citations
11.
Schaffer, Leah V., Rachel Miller, Robert J. Millikin, et al.. (2019). Constructing Human Proteoform Families Using Intact-Mass and Top-Down Proteomics with a Multi-Protease Global Post-Translational Modification Discovery Database. Journal of Proteome Research. 18(10). 3671–3680. 21 indexed citations
12.
Gemperline, David C, Richard S. Marshall, Kwanghee Lee, et al.. (2019). Proteomic analysis of affinity-purified 26S proteasomes identifies a suite of assembly chaperones in Arabidopsis. Journal of Biological Chemistry. 294(46). 17570–17592. 16 indexed citations
13.
Schaffer, Leah V., Robert J. Millikin, Rachel Miller, et al.. (2019). Identification and Quantification of Proteoforms by Mass Spectrometry. PMC.
14.
LeDuc, Richard D., Veit Schwämmle, Michael R. Shortreed, et al.. (2018). ProForma: A Standard Proteoform Notation. Journal of Proteome Research. 17(3). 1321–1325. 28 indexed citations
15.
Kennedy‐Darling, Julia, et al.. (2017). Multiplexed Sequence-Specific Capture of Chromatin and Mass Spectrometric Discovery of Associated Proteins. Analytical Chemistry. 89(15). 7841–7846. 8 indexed citations
16.
Shortreed, Michael R., Mark Scalf, Brian L. Frey, et al.. (2017). Elucidating Escherichia coli Proteoform Families Using Intact-Mass Proteomics and a Global PTM Discovery Database. Journal of Proteome Research. 16(11). 4156–4165. 27 indexed citations
17.
Kim, Do‐Young, et al.. (2017). Mass Spectrometric Analyses Reveal a Central Role for Ubiquitylation in Remodeling the Arabidopsis Proteome during Photomorphogenesis. Molecular Plant. 10(6). 846–865. 32 indexed citations
18.
Chen, Xiangsong, Li Lü, Mark Scalf, et al.. (2016). POWERDRESS interacts with HISTONE DEACETYLASE 9 to promote aging in Arabidopsis. eLife. 5. 134 indexed citations
19.
Book, Adam J., et al.. (2010). Affinity Purification of the Arabidopsis 26 S Proteasome Reveals a Diverse Array of Plant Proteolytic Complexes. Journal of Biological Chemistry. 285(33). 25554–25569. 112 indexed citations
20.
Liu, Qinghua, Zhen Guo, Zhengdong Fei, et al.. (1998). A surface-based approach to DNA computation. 123–132. 8 indexed citations

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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