Daniel Maslyar

2.8k total citations
44 papers, 1.6k citations indexed

About

Daniel Maslyar is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Molecular Biology. According to data from OpenAlex, Daniel Maslyar has authored 44 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Pulmonary and Respiratory Medicine, 21 papers in Oncology and 20 papers in Molecular Biology. Recurrent topics in Daniel Maslyar's work include Prostate Cancer Treatment and Research (10 papers), Cancer Treatment and Pharmacology (9 papers) and PI3K/AKT/mTOR signaling in cancer (8 papers). Daniel Maslyar is often cited by papers focused on Prostate Cancer Treatment and Research (10 papers), Cancer Treatment and Pharmacology (9 papers) and PI3K/AKT/mTOR signaling in cancer (8 papers). Daniel Maslyar collaborates with scholars based in United States, Spain and France. Daniel Maslyar's co-authors include Paul Moran, Luca Comai, Peter K. Vogt, Robert Dietrich, John J. Harada, Dale L. Boger, Joel Desharnais, Thorsten Berg, Joel Goldberg and Steven B. Cohen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and Blood.

In The Last Decade

Daniel Maslyar

44 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel Maslyar United States	18	864	616	381	222	212	44	1.6k
Víctor M. Villalobos United States	23	821 1.0×	423 0.7×	374 1.0×	228 1.0×	90 0.4×	70	1.5k
Wenhua Tang United States	20	1.6k 1.9×	675 1.1×	165 0.4×	104 0.5×	75 0.4×	33	2.2k
Hiroyuki Kitao Japan	32	2.1k 2.4×	1.3k 2.1×	410 1.1×	133 0.6×	71 0.3×	87	2.9k
Gennadi V. Glinsky United States	18	1.3k 1.5×	593 1.0×	123 0.3×	90 0.4×	172 0.8×	22	1.9k
Jochen Dahm‐Daphi Germany	26	1.2k 1.4×	776 1.3×	356 0.9×	81 0.4×	262 1.2×	45	1.7k
Yiyu Dong United States	16	731 0.8×	328 0.5×	220 0.6×	181 0.8×	66 0.3×	26	1.2k
Meilan Liu United States	18	995 1.2×	575 0.9×	292 0.8×	71 0.3×	66 0.3×	46	1.6k
Benjamin P. Chen United States	9	1.6k 1.8×	708 1.1×	187 0.5×	84 0.4×	122 0.6×	11	1.9k
Lynn Cawkwell United Kingdom	30	1.3k 1.6×	890 1.4×	404 1.1×	38 0.2×	111 0.5×	90	2.6k
Gianmarco Contino Italy	16	1.6k 1.9×	837 1.4×	253 0.7×	152 0.7×	35 0.2×	26	2.7k

Countries citing papers authored by Daniel Maslyar

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Maslyar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Maslyar

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

All Works

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20 of 20 papers shown

Khaki, Ali Raza, Alexander I. Spira, A.R. Abdul Razak, et al.. (2024). 1706P Efficacy, safety and PKPD of 23ME-00610, a first-in-class anti-CD200R1 antibody, in patients with advanced or metastatic clear-cell renal cell carcinoma (ccRCC): Results from a multi-center multi-country phase I/IIa expansion cohort. Annals of Oncology. 35. S1023–S1023. 1 indexed citations

Nalle, Sam C., Helen Lam, Ling Yan Leung, Spencer C. Liang, & Daniel Maslyar. (2021). 875 AL009, a fusion protein and multi-Siglec inhibitor, repolarizes suppressive myeloid cells and potentiates anti-cancer effects. Regular and Young Investigator Award Abstracts. A917–A917. 1 indexed citations

Moore, Kathleen N., Michael J. Birrer, Yulei Wang, et al.. (2020). Phase 1b study of anti-NaPi2b antibody-drug conjugate lifastuzumab vedotin (DNIB0600A) in patients with platinum-sensitive recurrent ovarian cancer. Gynecologic Oncology. 158(3). 631–639. 26 indexed citations

Bono, Johann S. de, Ugo De Giorgi, Daniel Nava Rodrigues, et al.. (2018). Randomized Phase II Study Evaluating Akt Blockade with Ipatasertib, in Combination with Abiraterone, in Patients with Metastatic Prostate Cancer with and without PTEN Loss. Clinical Cancer Research. 25(3). 928–936. 227 indexed citations

Kang, Yoon‐Koo, Matthew Chau Hsien Ng, Hyun Cheol Chung, et al.. (2018). A phase II, randomised study of mFOLFOX6 with or without the Akt inhibitor ipatasertib in patients with locally advanced or metastatic gastric or gastroesophageal junction cancer. European Journal of Cancer. 108. 17–24. 38 indexed citations

Oliveira, Mafalda, Cristina Saura, Isabel Calvo, et al.. (2018). Abstract CT041: Primary results from FAIRLANE (NCT02301988), a double-blind placebo (PBO)-controlled randomized phase II trial of neoadjuvant ipatasertib (IPAT) + paclitaxel (PAC) for early triple-negative breast cancer (eTNBC). Cancer Research. 78(13_Supplement). CT041–CT041. 3 indexed citations

Bono, Johann S. de, Sergio Bracarda, K.N. Chi, et al.. (2017). Randomized phase III trial of ipatasertib vs. placebo, plus abiraterone and prednisone/prednisolone, in men with asymptomatic or mildly symptomatic previously untreated metastatic castrate-resistant prostate cancer (mCRPC). Annals of Oncology. 28. v290–v290. 3 indexed citations

Bono, Johann S. de, Ugo De Giorgi, Christophe Massard, et al.. (2016). PTEN loss as a predictive biomarker for the Akt inhibitor ipatasertib combined with abiraterone acetate in patients with metastatic castration-resistant prostate cancer (mCRPC). Annals of Oncology. 27. vi243–vi243. 40 indexed citations

Lamberts, Laetitia E., C. Willemien Menke‐van der Houven van Oordt, Frederike Bensch, et al.. (2015). ImmunoPET with Anti-Mesothelin Antibody in Patients with Pancreatic and Ovarian Cancer before Anti-Mesothelin Antibody–Drug Conjugate Treatment. Clinical Cancer Research. 22(7). 1642–1652. 77 indexed citations

10.

Danila, Daniel C., Howard I. Scher, Edith Szafer‐Glusman, et al.. (2015). Abstract 4310: Predictive biomarkers of tumor sensitivity to STEAP1 antibody-drug conjugate (ADC) in patients (pts) with metastatic castration-resistant prostate cancer (mCRPC). Cancer Research. 75(15_Supplement). 4310–4310. 1 indexed citations

11.

Danila, Daniel C., Martin Fleisher, Jorge A. Carrasquillo, et al.. (2015). STEAP1 as a predictive biomarker for antibody-drug conjugate (ADC) activity in metastatic castration resistant prostate cancer (mCRPC).. Journal of Clinical Oncology. 33(15_suppl). 5029–5029. 4 indexed citations

12.

Liu, Joyce, Kathleen N. Moore, Michael J. Birrer, et al.. (2013). Abstract LB-290: Targeting MUC16 with the antibody-drug conjugate (ADC) DMUC5754A in patients with platinum-resistant ovarian cancer: A phase I study of safety and pharmacokinetics.. Cancer Research. 73(8_Supplement). LB–290. 8 indexed citations

13.

Senzer, Neil, John Nemunaitis, Michael J. Goldstein, et al.. (2006). 52. A Phase 1 Dose-Escalation Trial of Intravesical CG0070 for Superficial Transitional Cell Carcinoma (TCC) of the Bladder after Bacillus Calmette-Guerin (BCG) Failure. Molecular Therapy. 13. S22–S22. 2 indexed citations

14.

Maslyar, Daniel, Thierry Jahan, & David M. Jablons. (2004). Mechanisms of and potential treatment strategies for metastatic disease in non-small cell lung cancer. Seminars in Thoracic and Cardiovascular Surgery. 16(1). 40–50. 10 indexed citations

15.

Aoki, Masahiro, Vera Sobek, Daniel Maslyar, Andreas Hecht, & Peter K. Vogt. (2002). Oncogenic transformation by β-catenin: deletion analysis and characterization of selected target genes. Oncogene. 21(46). 6983–6991. 27 indexed citations

16.

Berg, Thorsten, Steven B. Cohen, Joel Desharnais, et al.. (2002). Small-molecule antagonists of Myc/Max dimerization inhibit Myc-induced transformation of chicken embryo fibroblasts. Proceedings of the National Academy of Sciences. 99(6). 3830–3835. 261 indexed citations

17.

Maslyar, Daniel, Masahiro Aoki, & Peter K. Vogt. (2001). The growth-promoting activity of the Bad protein in chicken embryo fibroblasts requires binding to protein 14-3-3. Oncogene. 20(37). 5087–5092. 20 indexed citations

18.

Comai, Luca, Paul Moran, & Daniel Maslyar. (1990). Novel and useful properties of a chimeric plant promoter combining CaMV 35S and MAS elements. Plant Molecular Biology. 15(3). 373–381. 145 indexed citations

19.

Dietrich, Robert, Daniel Maslyar, Rick C. Heupel, & John J. Harada. (1989). Spatial patterns of gene expression in Brassica napus seedlings: identification of a cortex-specific gene and localization of mRNAs encoding isocitrate lyase and a polypeptide homologous to proteinases.. The Plant Cell. 1(1). 73–80. 48 indexed citations

20.

Dietrich, Robert, Daniel Maslyar, Rick C. Heupel, & John J. Harada. (1989). Spatial Patterns of Gene Expression in Brassica napus Seedlings: Identification of a Cortex-Specific Gene and Localization of mRNAs Encoding Isocitrate Lyase and a Polypeptide Homologous to Proteinases. The Plant Cell. 1(1). 73–73. 3 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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