Daniel J. Treacy

7.9k total citations
11 papers, 903 citations indexed

About

Daniel J. Treacy is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Pathology and Forensic Medicine. According to data from OpenAlex, Daniel J. Treacy has authored 11 papers receiving a total of 903 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 2 papers in Pathology and Forensic Medicine. Recurrent topics in Daniel J. Treacy's work include Genetic Neurodegenerative Diseases (3 papers), Cancer Mechanisms and Therapy (2 papers) and Muscle Physiology and Disorders (2 papers). Daniel J. Treacy is often cited by papers focused on Genetic Neurodegenerative Diseases (3 papers), Cancer Mechanisms and Therapy (2 papers) and Muscle Physiology and Disorders (2 papers). Daniel J. Treacy collaborates with scholars based in United States, Canada and United Kingdom. Daniel J. Treacy's co-authors include Christopher B. Burge, Eric T. Wang, David E. Housman, Gary P. Schroth, Sita Reddy, Sonali P. Jog, Michela Biancolella, Éric Lécuyer, Shujun Luo and Neal Cody and has published in prestigious journals such as Cell, Journal of Clinical Oncology and Cancer Research.

In The Last Decade

Daniel J. Treacy

11 papers receiving 897 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel J. Treacy United States 9 772 261 92 81 80 11 903
Gagani Athauda United States 10 225 0.3× 143 0.5× 48 0.5× 59 0.7× 12 0.1× 27 471
Marieke Willemse Netherlands 15 398 0.5× 105 0.4× 97 1.1× 73 0.9× 24 0.3× 21 592
Marilyn Parra United States 19 1.0k 1.3× 134 0.5× 111 1.2× 38 0.5× 24 0.3× 24 1.4k
Filipe C. Lourenço United Kingdom 11 421 0.5× 158 0.6× 70 0.8× 181 2.2× 16 0.2× 15 673
Adrienne Brown United States 14 478 0.6× 228 0.9× 128 1.4× 143 1.8× 12 0.1× 26 977
T. Nagase Japan 9 533 0.7× 54 0.2× 62 0.7× 119 1.5× 29 0.4× 11 774
Beng-Ti Ang Singapore 11 390 0.5× 90 0.3× 164 1.8× 92 1.1× 15 0.2× 14 611
Alexandre Maucuer France 20 736 1.0× 85 0.3× 59 0.6× 119 1.5× 15 0.2× 27 1.0k
Thierry Horner United States 11 536 0.7× 105 0.4× 45 0.5× 54 0.7× 33 0.4× 20 674
Taryn A. Schiripo United States 7 984 1.3× 79 0.3× 64 0.7× 249 3.1× 20 0.3× 7 1.4k

Countries citing papers authored by Daniel J. Treacy

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Treacy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Treacy. 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 Daniel J. Treacy. The network helps show where Daniel J. Treacy may publish in the future.

Co-authorship network of co-authors of Daniel J. Treacy

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

All Works

11 of 11 papers shown
1.
Wang, Eric T., Daniel J. Treacy, Katy Eichinger, et al.. (2018). Transcriptome alterations in myotonic dystrophy skeletal muscle and heart. Human Molecular Genetics. 28(8). 1312–1321. 91 indexed citations
2.
Le, Xiuning, Pedram Razavi, Daniel J. Treacy, et al.. (2016). Systematic Functional Characterization of Resistance to PI3K Inhibition in Breast Cancer. Cancer Discovery. 6(10). 1134–1147. 97 indexed citations
3.
Izar, Benjamin, Sanjay M. Prakadan, Marc H. Wadsworth, et al.. (2016). Abstract 4380: Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-sequencing. Cancer Research. 76(14_Supplement). 4380–4380. 1 indexed citations
4.
Botta, Ginevra, Shuai Gao, Tiantian Li, et al.. (2015). PLZF, a Tumor Suppressor Genetically Lost in Metastatic Castration-Resistant Prostate Cancer, Is a Mediator of Resistance to Androgen Deprivation Therapy. Cancer Research. 75(10). 1944–1948. 46 indexed citations
5.
Wang, Eric T., Amanda J. Ward, Jennifer M. Cherone, et al.. (2015). Antagonistic regulation of mRNA expression and splicing by CELF and MBNL proteins. Genome Research. 25(6). 858–871. 150 indexed citations
6.
Goetz, Eva M., Mahmoud Ghandi, Daniel J. Treacy, Nikhil Wagle, & Levi A. Garraway. (2014). ERK Mutations Confer Resistance to Mitogen-Activated Protein Kinase Pathway Inhibitors. Cancer Research. 74(23). 7079–7089. 80 indexed citations
7.
Wagle, Nikhil, Eliezer M. Van Allen, Dennie T. Frederick, et al.. (2013). Whole exome and whole transcriptome sequencing in melanoma patients to identify mechanisms of resistance to combined RAF/MEK inhibition.. Journal of Clinical Oncology. 31(15_suppl). 9015–9015. 4 indexed citations
8.
Wang, Eric T., Neal Cody, Sonali P. Jog, et al.. (2012). Transcriptome-wide Regulation of Pre-mRNA Splicing and mRNA Localization by Muscleblind Proteins. Cell. 150(4). 710–724. 383 indexed citations
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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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2026