Michelle K. Greene

68 total papers · 724 total citations
24 papers, 462 citations indexed

About

Michelle K. Greene is a scholar working on Molecular Biology, Oncology and Biomaterials. According to data from OpenAlex, Michelle K. Greene has authored 24 papers receiving a total of 462 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 9 papers in Oncology and 8 papers in Biomaterials. Recurrent topics in Michelle K. Greene's work include Nanoparticle-Based Drug Delivery (8 papers), Pancreatic and Hepatic Oncology Research (5 papers) and Monoclonal and Polyclonal Antibodies Research (5 papers). Michelle K. Greene is often cited by papers focused on Nanoparticle-Based Drug Delivery (8 papers), Pancreatic and Hepatic Oncology Research (5 papers) and Monoclonal and Polyclonal Antibodies Research (5 papers). Michelle K. Greene collaborates with scholars based in United Kingdom, United States and Argentina. Michelle K. Greene's co-authors include Christopher J. Scott, Peter Smyth, Vijay Chudasama, Daniel A. Richards, Daniel B. Longley, Katrina Campbell, Marcos Fernández, Donna M. Small, Kirsty M. McLaughlin and Sandra Van Schaeybroeck and has published in prestigious journals such as Nature Nanotechnology, Chemical Communications and Biochemical Journal.

In The Last Decade

Michelle K. Greene

24 papers receiving 459 citations

Author Peers

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

Author						Papers	Cites
Michelle K. Greene	210	158	149	123	97	24	462
Peter Smyth	214 1.0×	133 0.8×	129 0.9×	76 0.6×	65 0.7×	21	472
Khalid Abu Ajaj	222 1.1×	155 1.0×	87 0.6×	163 1.3×	97 1.0×	16	496
Yuan-Chin Hsieh	252 1.2×	147 0.9×	100 0.7×	69 0.6×	135 1.4×	27	448
Jeffrey L. Schaal	191 0.9×	203 1.3×	126 0.8×	62 0.5×	59 0.6×	13	492
Ronny Rüger	232 1.1×	135 0.9×	194 1.3×	146 1.2×	73 0.8×	22	503
Shuxian Song	243 1.2×	150 0.9×	159 1.1×	64 0.5×	88 0.9×	18	468
Diêgo S. Ferreira	175 0.8×	157 1.0×	133 0.9×	83 0.7×	84 0.9×	23	517
Chien-Han Kao	295 1.4×	96 0.6×	97 0.7×	50 0.4×	82 0.8×	28	490
Mandip Singh	196 0.9×	82 0.5×	173 1.2×	133 1.1×	42 0.4×	22	538
R.A. Schwendener	286 1.4×	171 1.1×	69 0.5×	71 0.6×	62 0.6×	24	521

Countries citing papers authored by Michelle K. Greene

Since Specialization

Citations

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

Fields of papers citing papers by Michelle K. Greene

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michelle K. Greene. 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 Michelle K. Greene. The network helps show where Michelle K. Greene may publish in the future.

Co-authorship network of co-authors of Michelle K. Greene

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

All Works

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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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