Woodrow E. Lomas

463 total citations
10 papers, 331 citations indexed

About

Woodrow E. Lomas is a scholar working on Molecular Biology, Immunology and Infectious Diseases. According to data from OpenAlex, Woodrow E. Lomas has authored 10 papers receiving a total of 331 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Immunology and 2 papers in Infectious Diseases. Recurrent topics in Woodrow E. Lomas's work include Single-cell and spatial transcriptomics (6 papers), Immune Cell Function and Interaction (3 papers) and HIV Research and Treatment (2 papers). Woodrow E. Lomas is often cited by papers focused on Single-cell and spatial transcriptomics (6 papers), Immune Cell Function and Interaction (3 papers) and HIV Research and Treatment (2 papers). Woodrow E. Lomas collaborates with scholars based in United States and Canada. Woodrow E. Lomas's co-authors include Yi Liu, Emily Park, Xiaoming Zhan, Minke E. Binnerts, Sejal M. Patel, Michaël D. Lévy, Mei Zhou, J.C. Williams, Nenad Tomas̆ević and Arie Abo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Immunology and PLoS ONE.

In The Last Decade

Woodrow E. Lomas

8 papers receiving 317 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Woodrow E. Lomas United States	6	255	72	56	48	22	10	331
Aimee Stablewski United States	12	300 1.2×	98 1.4×	51 0.9×	36 0.8×	20 0.9×	18	379
Virginie Mournetas France	8	350 1.4×	111 1.5×	59 1.1×	43 0.9×	28 1.3×	13	435
Hirofumi Higuchi Japan	8	222 0.9×	39 0.5×	56 1.0×	62 1.3×	21 1.0×	10	357
Salomé Adam France	11	584 2.3×	65 0.9×	119 2.1×	36 0.8×	23 1.0×	14	641
Matthew J. Renda United States	8	291 1.1×	121 1.7×	42 0.8×	32 0.7×	13 0.6×	11	393
Sabine Laurent‐Chabalier France	6	563 2.2×	64 0.9×	56 1.0×	35 0.7×	40 1.8×	15	644
Courtney M. Tate United States	11	428 1.7×	86 1.2×	52 0.9×	33 0.7×	12 0.5×	15	495
Nicolas Strauli United States	7	218 0.9×	32 0.4×	47 0.8×	71 1.5×	16 0.7×	13	334
Dennis Zerby United States	9	289 1.1×	66 0.9×	119 2.1×	40 0.8×	9 0.4×	11	421
Yeguang Hu United States	6	289 1.1×	55 0.8×	39 0.7×	36 0.8×	21 1.0×	7	381

Countries citing papers authored by Woodrow E. Lomas

Since Specialization

Citations

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

Fields of papers citing papers by Woodrow E. Lomas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Woodrow E. Lomas. 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 Woodrow E. Lomas. The network helps show where Woodrow E. Lomas may publish in the future.

Co-authorship network of co-authors of Woodrow E. Lomas

This figure shows the co-authorship network connecting the top 25 collaborators of Woodrow E. Lomas. A scholar is included among the top collaborators of Woodrow E. Lomas 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 Woodrow E. Lomas. Woodrow E. Lomas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Lomas, Woodrow E., et al.. (2024). Evaluation of single‐cell sorting accuracy using antibody‐derived tag‐based qPCR. Cytometry Part A. 105(10). 772–785.

Lomas, Woodrow E., et al.. (2021). Co-staining human PBMCs with fluorescent antibodies and antibody-oligonucleotide conjugates for cell sorting prior to single-cell CITE-Seq. STAR Protocols. 2(4). 100893–100893. 3 indexed citations

Corselli, Mirko, Suraj Saksena, Margaret Nakamoto, et al.. (2021). Single cell multiomic analysis of T cell exhaustion in vitro. Cytometry Part A. 101(1). 27–44. 17 indexed citations

Korber, Bette, Woodrow E. Lomas, Bhavna Hora, et al.. (2021). Cross-reactive monoclonal antibodies to multiple HIV-1 subtype and SIVcpz envelope glycoproteins. UNC Libraries.

Corselli, Mirko, Suraj Saksena, Margaret Nakamoto, et al.. (2020). Deep characterization of in vitro chronically stimulated T cells via single-cell multiomic analysis. The Journal of Immunology. 204(1_Supplement). 159.23–159.23. 1 indexed citations

Chattopadhyay, Pratip K., Aidan Winters, Woodrow E. Lomas, Andressa S. Laino, & David Woods. (2019). High-Parameter Single-Cell Analysis. Annual Review of Analytical Chemistry. 12(1). 411–430. 19 indexed citations

Hoof, Dennis Van, Woodrow E. Lomas, Mary Beth Hanley, & Emily Park. (2014). Simultaneous flow cytometric analysis of IFN‐γ and CD4 mRNA and protein expression kinetics in human peripheral blood mononuclear cells during activation. Cytometry Part A. 85(10). 894–900. 14 indexed citations

Hanley, Mary Beth, et al.. (2013). Detection of Low Abundance RNA Molecules in Individual Cells by Flow Cytometry. PLoS ONE. 8(2). e57002–e57002. 38 indexed citations

Gao, Feng, Richard M. Scearce, S. Munir Alam, et al.. (2009). Cross-reactive monoclonal antibodies to multiple HIV-1 subtype and SIVcpz envelope glycoproteins. Virology. 394(1). 91–98. 20 indexed citations

10.

Binnerts, Minke E., Kyung-Ah Kim, Jessica Bright, et al.. (2007). R-Spondin1 regulates Wnt signaling by inhibiting internalization of LRP6. Proceedings of the National Academy of Sciences. 104(37). 14700–14705. 219 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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