Daniel Maslyar

2.9k citations
44 papers · 1.7k · h-index 18

Impact in

Papers in

Daniel Maslyar

44 papers receiving 1.7k citations

Peers

Daniel Maslyar
Comparison fields: 5 of 88
  • Oncology 574
  • Biotechnology 176
  • Molecular Biology 856
  • Pulmonary and Respiratory Medicine 345
  • Cancer Research 160
Replace Gur Pines with:
Gur Pines Israel
Wenhua Tang United States
Lynn Cawkwell United Kingdom
Hiroyuki Kitao Japan
Pedro P. López‐Casas Spain
Lawrence H. Cheung United States
David V. Gold United States
S. Biade United States
Gennadi V. Glinsky United States
Imayavaramban Lakshmanan United States
Daniel Maslyar relative to Gur Pines Israel Gur Pines's profile →
Citations per field
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Citations per year

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-authors

The 25 scholars most cited alongside Daniel Maslyar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Maslyar Line = papers co-authored together Daniel Maslyar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002273
2 2018231
3 2012197
4 1990165
5 1989125
6 201692
7 200985
8 201581
9 201963
10 198951
11 201640
12 201839
13 202027
14 200227
15 201424
16 201823
17 200120
18 201017
19 201616
20 201415

About Daniel Maslyar

Daniel Maslyar is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology, Oncology, Reproductive Medicine and Pathology and Forensic Medicine, having authored 44 papers that have together received 1.7k indexed citations. Recurring topics across this work include Prostate Cancer Treatment and Research (10 papers), Cancer Treatment and Pharmacology (9 papers), PI3K/AKT/mTOR signaling in cancer (7 papers), Ovarian cancer diagnosis and treatment (6 papers), Advanced Breast Cancer Therapies (4 papers), Photosynthetic Processes and Mechanisms (4 papers), Lung Cancer Treatments and Mutations (4 papers) and Peptidase Inhibition and Analysis (3 papers). The work is most often cited by research in Oncology (574 citations), Biotechnology (176 citations), Molecular Biology (856 citations), Pulmonary and Respiratory Medicine (345 citations) and Cancer Research (160 citations). Daniel Maslyar has collaborated with scholars based in United States, France and Spain. Frequent co-authors include Luca Comai, Paul Moran, Peter K. Vogt, John J. Harada, Robert Dietrich, Dale L. Boger, Thorsten Berg, Steven B. Cohen, Joel Desharnais and Joel Goldberg. Their work appears in journals such as Journal of Clinical Oncology, Annals of Oncology, The Plant Cell, Cancer Research and Clinical Cancer Research.

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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