Dylan Conklin

2.6k total citations · 1 hit paper
32 papers, 1.8k citations indexed

About

Dylan Conklin is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Molecular Biology. According to data from OpenAlex, Dylan Conklin has authored 32 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Oncology, 16 papers in Pulmonary and Respiratory Medicine and 13 papers in Molecular Biology. Recurrent topics in Dylan Conklin's work include Advanced Breast Cancer Therapies (12 papers), Cancer-related Molecular Pathways (10 papers) and HER2/EGFR in Cancer Research (7 papers). Dylan Conklin is often cited by papers focused on Advanced Breast Cancer Therapies (12 papers), Cancer-related Molecular Pathways (10 papers) and HER2/EGFR in Cancer Research (7 papers). Dylan Conklin collaborates with scholars based in United States, Switzerland and Ireland. Dylan Conklin's co-authors include Dennis J. Slamon, Ondrej Kalous, Richard S. Finn, Amrita Desai, Charles Ginther, David J. Cohen, Judy Dering, Mohammad Atefi, Camilla Fowst and Isan Chen and has published in prestigious journals such as Science, Journal of Clinical Oncology and Blood.

In The Last Decade

Dylan Conklin

32 papers receiving 1.8k citations

Hit Papers

PD 0332991, a selective cyclin D kinase 4/6 inhibitor, pr... 2009 2026 2014 2020 2009 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. PD 0332991, a selective cyclin D kinase 4/6 inhibitor, preferentially inhibits proliferation of luminal estrogen receptor-positive human breast cancer cell lines in vitro
    2009 1.0k citations Richard S. Finn, Judy Dering et al. Breast Cancer Research profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dylan Conklin United States 12 1.2k 1.1k 636 401 272 32 1.8k
Ondrej Kalous United States 14 1.2k 1.0× 958 0.9× 731 1.1× 339 0.8× 253 0.9× 24 1.8k
Luigi Formisano Italy 25 1.1k 0.9× 772 0.7× 1.1k 1.8× 494 1.2× 236 0.9× 73 2.2k
Barbara A. Helfrich United States 23 1.3k 1.0× 959 0.9× 1.7k 2.7× 478 1.2× 153 0.6× 35 2.7k
Seth A. Wander United States 25 1.5k 1.3× 1.1k 1.0× 1.3k 2.1× 791 2.0× 389 1.4× 108 2.9k
Mónica V. Estrada United States 16 1.4k 1.1× 677 0.6× 1.3k 2.0× 925 2.3× 181 0.7× 25 2.5k
Cornelia Quadt Switzerland 25 756 0.6× 591 0.5× 1.4k 2.2× 273 0.7× 301 1.1× 53 2.2k
Olga Rodríguez Spain 5 821 0.7× 615 0.6× 683 1.1× 235 0.6× 224 0.8× 8 1.4k
Kristen E. Mengwasser United States 7 1.1k 0.9× 1.1k 1.0× 1.5k 2.4× 523 1.3× 89 0.3× 8 2.4k
Rosa Caputo Italy 20 1.3k 1.1× 906 0.8× 1.0k 1.6× 355 0.9× 135 0.5× 21 2.3k
Stephen Leong United States 23 1.1k 0.9× 471 0.4× 842 1.3× 606 1.5× 167 0.6× 73 2.3k

Countries citing papers authored by Dylan Conklin

Since Specialization
Citations

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

Fields of papers citing papers by Dylan Conklin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dylan Conklin

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

All Works

20 of 20 papers shown
1.
O’Brien, Neil A., Martina S.J. McDermott, Dylan Conklin, et al.. (2020). Targeting activated PI3K/mTOR signaling overcomes acquired resistance to CDK4/6-based therapies in preclinical models of hormone receptor-positive breast cancer. Breast Cancer Research. 22(1). 89–89. 87 indexed citations
2.
O’Brien, Neil A., Dylan Conklin, Alex Gaither, et al.. (2019). Abstract 3825: Targeting activated PI3K/mTOR signaling overcomes resistance to CDK4/6-based therapies in preclinical ER+ breast cancer models. 3825–3825. 1 indexed citations
3.
Welin, Eric R., Aurapat Ngamnithiporn, Guillaume Lapointe, et al.. (2018). Concise total syntheses of (–)-jorunnamycin A and (–)-jorumycin enabled by asymmetric catalysis. Science. 363(6424). 270–275. 94 indexed citations
4.
Campos, Maira P., Erika von Euw, Victor E. Velculescu, et al.. (2018). BRAF Mutations Occur Infrequently in Ovarian Cancer but Suggest Responsiveness to BRAF and MEK Inhibition. JCO Precision Oncology. 2(2). 1–6. 6 indexed citations
5.
Papp, Eniko, Dorothy Hallberg, Gottfried E. Konecny, et al.. (2018). Integrated Genomic, Epigenomic, and Expression Analyses of Ovarian Cancer Cell Lines. Cell Reports. 25(9). 2617–2633. 78 indexed citations
6.
O’Brien, Neil A., Dylan Conklin, Richard P. Beckmann, et al.. (2018). Preclinical Activity of Abemaciclib Alone or in Combination with Antimitotic and Targeted Therapies in Breast Cancer. Molecular Cancer Therapeutics. 17(5). 897–907. 80 indexed citations
7.
Fejzo, Marlena S., Lee Anderson, Hsiao‐Wang Chen, et al.. (2017). Proteasome ubiquitin receptor PSMD4 is an amplification target in breast cancer and may predict sensitivity to PARPi. Genes Chromosomes and Cancer. 56(8). 589–597. 27 indexed citations
8.
Larson, Sarah M., Monica Mead, Andrae Vandross, et al.. (2017). Abstract 136: Phospho-S6 levels correlate with response to Copanlisib (BAY 80-6946) in multiple myeloma. Cancer Research. 77(13_Supplement). 136–136. 1 indexed citations
9.
Kalous, Ondrej, Dylan Conklin, Kanthinh Manivong, et al.. (2016). Abstract 3008: Preclinical characterization of AMG 900, a pan-aurora kinase inhibitor, alone and in combination with taxanes in ovarian cancer. Cancer Research. 76(14_Supplement). 3008–3008. 3 indexed citations
10.
Hurvitz, Sara A., Ondrej Kalous, Dylan Conklin, et al.. (2015). In vitro activity of the mTOR inhibitor everolimus, in a large panel of breast cancer cell lines and analysis for predictors of response. Breast Cancer Research and Treatment. 149(3). 669–680. 46 indexed citations
11.
Mullooly, Maeve, Dylan Conklin, Patricia M. McGowan, et al.. (2015). Neratinib to inhibit the growth of triple-negative breast cancer cells.. Journal of Clinical Oncology. 33(15_suppl). 1099–1099. 8 indexed citations
12.
O’Brien, Neil A., Tong Luo, Erika von Euw, et al.. (2014). Targeting PI3K/mTOR Overcomes Resistance to HER2-Targeted Therapy Independent of Feedback Activation of AKT. Clinical Cancer Research. 20(13). 3507–3520. 93 indexed citations
13.
Kalous, Ondrej, Dylan Conklin, Amrita Desai, et al.. (2013). AMG 900, pan-Aurora kinase inhibitor, preferentially inhibits the proliferation of breast cancer cell lines with dysfunctional p53. Breast Cancer Research and Treatment. 141(3). 397–408. 22 indexed citations
14.
Wainberg, Zev A., Adrian Anghel, Amrita Desai, et al.. (2013). Inhibition of HSP90 with AUY922 Induces Synergy in HER2-Amplified Trastuzumab-Resistant Breast and Gastric Cancer. Molecular Cancer Therapeutics. 12(4). 509–519. 58 indexed citations
15.
Conklin, Dylan. (2013). Identification of Genomic Predictors of Response to the CDK4/6 Inhibitor Palbociclib using the UCLATORL Panel of Human Cancer Cell Lines. eScholarship (California Digital Library). 1 indexed citations
16.
Euw, Erika M. von, Hong-Mei Rong, Neil A. O’Brien, et al.. (2013). Abstract 2437: MEK162 (ARRY 438162), a MEK1/2 inhibitor, has activity in melanoma cells independent of BRAF and NRAS mutation status.. Cancer Research. 73(8_Supplement). 2437–2437. 1 indexed citations
17.
Desai, Amrita, Erika von Euw, Dylan Conklin, et al.. (2013). PD-0332991, a potent and selective inhibitor of cyclin-dependent kinase 4/6, demonstrates inhibition of proliferation in renal cell carcinoma at nanomolar concentrations and molecular markers predict for sensitivity.. PubMed. 33(8). 2997–3004. 88 indexed citations
18.
Kalous, Ondrej, Dylan Conklin, Amrita Desai, et al.. (2012). Dacomitinib (PF-00299804), an Irreversible Pan-HER Inhibitor, Inhibits Proliferation of HER2-Amplified Breast Cancer Cell Lines Resistant to Trastuzumab and Lapatinib. Molecular Cancer Therapeutics. 11(9). 1978–1987. 58 indexed citations
19.
Knights, Charlotte, Lucy C. Riches, Alan Lau, et al.. (2009). Abstract #5494: Pre-clinical evaluation of single-agent activity of the PARP inhibitor olaparib (AZD2281) in homologous recombination deficient triple-negative breast cancer. Cancer Research. 69. 5494–5494. 1 indexed citations
20.
Finn, Richard S., Judy Dering, Dylan Conklin, et al.. (2009). PD 0332991, a selective cyclin D kinase 4/6 inhibitor, preferentially inhibits proliferation of luminal estrogen receptor-positive human breast cancer cell lines in vitro. Breast Cancer Research. 11(5). R77–R77. 1044 indexed citations breakdown →

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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