Philip Ma

1.1k total citations
9 papers, 392 citations indexed

About

Philip Ma is a scholar working on Molecular Biology, Public Health, Environmental and Occupational Health and Economics and Econometrics. According to data from OpenAlex, Philip Ma has authored 9 papers receiving a total of 392 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Public Health, Environmental and Occupational Health and 3 papers in Economics and Econometrics. Recurrent topics in Philip Ma's work include Advanced Proteomics Techniques and Applications (2 papers), Pharmaceutical industry and healthcare (2 papers) and Health and Medical Research Impacts (2 papers). Philip Ma is often cited by papers focused on Advanced Proteomics Techniques and Applications (2 papers), Pharmaceutical industry and healthcare (2 papers) and Health and Medical Research Impacts (2 papers). Philip Ma collaborates with scholars based in United States, Italy and Iran. Philip Ma's co-authors include Rodney W. Zemmel, Jerel C. Davis, Amar A. Desai, Bruce L Booth, Robert H. Glassman, Roberto Molinaro, Shahed Behzadi, Vivek F. Farias, Róbert Langer and J. F. Smith and has published in prestigious journals such as Nature Reviews Drug Discovery, International Journal of Radiation Oncology*Biology*Physics and Journal of Proteome Research.

In The Last Decade

Philip Ma

9 papers receiving 359 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Philip Ma United States	8	179	84	60	52	37	9	392
Katarzyna Śmietana United States	8	267 1.5×	77 0.9×	38 0.6×	59 1.1×	41 1.1×	12	543
Jamie Munro United Kingdom	3	160 0.9×	28 0.3×	26 0.4×	113 2.2×	67 1.8×	4	411
Ellen Rohde United States	12	257 1.4×	11 0.1×	28 0.5×	28 0.5×	89 2.4×	21	550
Kate M. O’Neill United States	8	205 1.1×	17 0.2×	63 1.1×	21 0.4×	57 1.5×	11	503
Vidula Sukhatme United States	8	353 2.0×	22 0.3×	38 0.6×	125 2.4×	45 1.2×	17	751
Bruce L Booth United States	6	121 0.7×	78 0.9×	5 0.1×	106 2.0×	20 0.5×	9	308
Marinus W. Lobbezoo United States	8	85 0.5×	33 0.4×	18 0.3×	22 0.4×	8 0.2×	13	280
Sarah A. Dugger United States	5	199 1.1×	8 0.1×	21 0.3×	54 1.0×	38 1.0×	5	349
Yeonhee Park United States	14	174 1.0×	16 0.2×	13 0.2×	8 0.2×	9 0.2×	41	411
David Xu United States	14	318 1.8×	7 0.1×	18 0.3×	58 1.1×	27 0.7×	30	637

Countries citing papers authored by Philip Ma

Since Specialization

Citations

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

Fields of papers citing papers by Philip Ma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philip Ma

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

All Works

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9 of 9 papers shown

1.

Vitko, Dijana, Joon‐Yong Lee, Chinmay Belthangady, et al.. (2024). timsTOF HT Improves Protein Identification and Quantitative Reproducibility for Deep Unbiased Plasma Protein Biomarker Discovery. Journal of Proteome Research. 23(3). 929–938. 21 indexed citations

2.

Corbo, Claudia, Andrew A. Li, Hossein Poustchi, et al.. (2020). Analysis of the Human Plasma Proteome Using Multi‐Nanoparticle Protein Corona for Detection of Alzheimer's Disease. Advanced Healthcare Materials. 10(2). e2000948–e2000948. 35 indexed citations

3.

Mattes, Malcolm D., Timothy D. Eubank, Aldesia Provenzano, et al.. (2019). Outcomes from a Phase II Clinical Trial Evaluating the Systemic (Abscopal) Response from the Addition of Local Radiation to Standard-of-Care Immunotherapy for Metastatic Non-Small Cell Lung Cancer. International Journal of Radiation Oncology*Biology*Physics. 105(1). E519–E519. 3 indexed citations

4.

Smith, J. F., et al.. (2012). FDA advisory committee meeting outcomes. Nature Reviews Drug Discovery. 11(7). 513–514. 12 indexed citations

5.

Davis, Jerel C., et al.. (2009). The microeconomics of personalized medicine: today's challenge and tomorrow's promise. Nature Reviews Drug Discovery. 8(4). 279–286. 122 indexed citations

6.

Ma, Philip, et al.. (2008). What drives success for specialty pharmaceuticals?. Nature Reviews Drug Discovery. 7(7). 563–567. 15 indexed citations

7.

Booth, Bruce L, Robert H. Glassman, & Philip Ma. (2003). Oncology's trials. Nature Reviews Drug Discovery. 2(8). 609–610. 44 indexed citations

8.

Ma, Philip & Rodney W. Zemmel. (2002). Value of novelty?. Nature Reviews Drug Discovery. 1(8). 571–572. 132 indexed citations

9.

Ma, Philip, et al.. (2002). Drug life-cycle technologies. Nature Reviews Drug Discovery. 1(10). 751–752. 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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