Alex Greenfield

2.3k total citations
10 papers, 603 citations indexed

About

Alex Greenfield is a scholar working on Molecular Biology, Genetics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Alex Greenfield has authored 10 papers receiving a total of 603 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Genetics and 2 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Alex Greenfield's work include Gene Regulatory Network Analysis (5 papers), Bioinformatics and Genomic Networks (4 papers) and Gene expression and cancer classification (3 papers). Alex Greenfield is often cited by papers focused on Gene Regulatory Network Analysis (5 papers), Bioinformatics and Genomic Networks (4 papers) and Gene expression and cancer classification (3 papers). Alex Greenfield collaborates with scholars based in United States and Japan. Alex Greenfield's co-authors include Richard Bonneau, Aviv Madar, Harry Ostrer, Christoph Hafemeister, Eric Vanden‐Eijnden, Christopher S. Poultney, Michael J. Garabedian, Susan K. Logan, Patrick Eichenberger and Tsutomu Sato and has published in prestigious journals such as Journal of Clinical Oncology, Bioinformatics and PLoS ONE.

In The Last Decade

Alex Greenfield

10 papers receiving 595 citations

Peers

Alex Greenfield

GENET

ECOLO

EPIDE

Anne Gleizes Switzerland

Dan Tenenbaum United States

Andrew Tikhonov United Kingdom

Sikander Hayat Germany

Avantika Lal United States

Daniele Raimondi Belgium

Marcel Turcotte Canada

Pascal Notin United Kingdom

Christina Laufer Germany

Anne Gleizes Switzerland

Alex Greenfield

581 ×1.2

82 ×0.7

GENET

22 ×0.4

25 ×0.5

ECOLO

59 ×1.3

EPIDE

Citations per year, relative to Alex Greenfield Alex Greenfield (= 1×) peers Anne Gleizes

Countries citing papers authored by Alex Greenfield

Since Specialization

Citations

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

Fields of papers citing papers by Alex Greenfield

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alex Greenfield

This figure shows the co-authorship network connecting the top 25 collaborators of Alex Greenfield. A scholar is included among the top collaborators of Alex Greenfield 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 Alex Greenfield. Alex Greenfield 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

Luo, Yi, Samir Wadhawan, Alex Greenfield, et al.. (2021). SOMAscan Proteomics Identifies Serum Biomarkers Associated With Liver Fibrosis in Patients With NASH. Hepatology Communications. 5(5). 760–773. 56 indexed citations

Jabado, Omar, Michael A. Maldonado, Michael Schiff, et al.. (2021). Differential Changes in ACPA Fine Specificity and Gene Expression in a Randomized Trial of Abatacept and Adalimumab in Rheumatoid Arthritis. Rheumatology and Therapy. 9(2). 391–409. 5 indexed citations

Szabó, Péter M., George Lee, Scott Ely, et al.. (2019). CD8+ T cells in tumor parenchyma and stroma by image analysis (IA) and gene expression profiling (GEP): Potential biomarkers for immuno-oncology (I-O) therapy.. Journal of Clinical Oncology. 37(15_suppl). 2594–2594. 4 indexed citations

Arrieta‐Ortiz, Mario L., Christoph Hafemeister, Ashley R. Bate, et al.. (2015). An experimentally supported model of the Bacillus subtilis global transcriptional regulatory network. Molecular Systems Biology. 11(11). 839–839. 131 indexed citations

Ha, Susan, Alex Greenfield, Christopher S. Poultney, et al.. (2013). A genome-wide RNA interference screen identifies new regulators of androgen receptor function in prostate cancer cells. Genome Research. 23(4). 581–591. 35 indexed citations

Greenfield, Alex, Christoph Hafemeister, & Richard Bonneau. (2013). Robust data-driven incorporation of prior knowledge into the inference of dynamic regulatory networks. Bioinformatics. 29(8). 1060–1067. 97 indexed citations

Poultney, Christopher S., Alex Greenfield, & Richard Bonneau. (2012). Integrated Inference and Analysis of Regulatory Networks from Multi-Level Measurements. Methods in cell biology. 110. 19–56. 14 indexed citations

Levine, Paul M., Eugine Lee, Alex Greenfield, et al.. (2012). Androgen Receptor Antagonism by Divalent Ethisterone Conjugates in Castrate-Resistant Prostate Cancer Cells. ACS Chemical Biology. 7(10). 1693–1701. 19 indexed citations

Madar, Aviv, Alex Greenfield, Eric Vanden‐Eijnden, & Richard Bonneau. (2010). DREAM3: Network Inference Using Dynamic Context Likelihood of Relatedness and the Inferelator. PLoS ONE. 5(3). e9803–e9803. 69 indexed citations

10.

Greenfield, Alex, Aviv Madar, Harry Ostrer, & Richard Bonneau. (2010). DREAM4: Combining Genetic and Dynamic Information to Identify Biological Networks and Dynamical Models. PLoS ONE. 5(10). e13397–e13397. 173 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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