Julia Grigorieva

1.2k total citations
38 papers, 579 citations indexed

About

Julia Grigorieva is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Julia Grigorieva has authored 38 papers receiving a total of 579 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Oncology, 21 papers in Pulmonary and Respiratory Medicine and 13 papers in Cancer Research. Recurrent topics in Julia Grigorieva's work include Lung Cancer Treatments and Mutations (19 papers), Cancer Genomics and Diagnostics (11 papers) and Lung Cancer Research Studies (8 papers). Julia Grigorieva is often cited by papers focused on Lung Cancer Treatments and Mutations (19 papers), Cancer Genomics and Diagnostics (11 papers) and Lung Cancer Research Studies (8 papers). Julia Grigorieva collaborates with scholars based in United States, Italy and Netherlands. Julia Grigorieva's co-authors include Heinrich Röder, Joanna Roder, David P. Carbone, Krista Meyer, Lesley Seymour, Keyue Ding, Frances A. Shepherd, Ming‐Sound Tsao, Richard M. Caprioli and Carlos Oliveira and has published in prestigious journals such as Journal of Clinical Oncology, Journal of Geophysical Research Atmospheres and Cancer Research.

In The Last Decade

Julia Grigorieva

36 papers receiving 529 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Julia Grigorieva United States 13 336 293 208 133 124 38 579
Joanna Roder United States 13 260 0.8× 219 0.7× 145 0.7× 97 0.7× 81 0.7× 36 466
Emma Niméus Sweden 16 268 0.8× 118 0.4× 378 1.8× 216 1.6× 310 2.5× 40 816
Tijl Vermassen Belgium 14 285 0.8× 142 0.5× 183 0.9× 55 0.4× 59 0.5× 36 543
Jianzhong Cao China 15 253 0.8× 277 0.9× 232 1.1× 23 0.2× 150 1.2× 58 620
Shalini Makawita United States 11 242 0.7× 113 0.4× 238 1.1× 117 0.9× 103 0.8× 22 545
Srinivasan Senthamizhchelvan United States 14 160 0.5× 581 2.0× 102 0.5× 83 0.6× 113 0.9× 26 1.1k
Y. H. Fan China 14 98 0.3× 72 0.2× 366 1.8× 84 0.6× 283 2.3× 34 607
Megan Crumbaker Australia 15 234 0.7× 714 2.4× 188 0.9× 101 0.8× 172 1.4× 54 909
Brett Mahon United States 11 142 0.4× 162 0.6× 127 0.6× 32 0.2× 121 1.0× 35 494

Countries citing papers authored by Julia Grigorieva

Since Specialization
Citations

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

Fields of papers citing papers by Julia Grigorieva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julia Grigorieva

This figure shows the co-authorship network connecting the top 25 collaborators of Julia Grigorieva. A scholar is included among the top collaborators of Julia Grigorieva 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 Julia Grigorieva. Julia Grigorieva 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.
Mahalingam, Devalingam, Leonidas Chelis, Sunyoung S. Lee, et al.. (2021). Detection of Hepatocellular Carcinoma in a High-Risk Population by a Mass Spectrometry-Based Test. Cancers. 13(13). 3109–3109. 5 indexed citations
2.
Roder, Joanna, Carlos Oliveira, Krista Meyer, et al.. (2020). A proposal for score assignment to characterize biological processes from mass spectral analysis of serum. PubMed. 18. 13–26. 1 indexed citations
3.
Davis, Andrew A., Jonghanne Park, Wade T. Iams, et al.. (2020). Abstract 5527: Serum proteomic scores for understanding the mechanisms of immune-related adverse events (irAEs) in non-small cell lung cancer. Cancer Research. 80(16_Supplement). 5527–5527. 1 indexed citations
4.
5.
Weber, Jeffrey S., Mario Sznol, Ryan J. Sullivan, et al.. (2017). A Serum Protein Signature Associated with Outcome after Anti–PD-1 Therapy in Metastatic Melanoma. Cancer Immunology Research. 6(1). 79–86. 53 indexed citations
6.
Grossi, Francesco, Erika Rijavec, Federica Biello, et al.. (2017). P3.02c-074 Evaluation of a Pretreatment Serum Tests for Nivolumab Benefit in Patients with Non-Small Cell Lung Cancer. Journal of Thoracic Oncology. 12(1). S1322–S1322. 7 indexed citations
7.
Grossi, Francesco, Carlo Genova, Erika Rijavec, et al.. (2017). Prognostic role of the VeriStrat test in first line patients with non-small cell lung cancer treated with platinum-based chemotherapy. Lung Cancer. 117. 64–69. 12 indexed citations
8.
Grossi, Francesco, Erika Rijavec, Carlo Genova, et al.. (2016). Serum proteomic test in advanced non-squamous non-small cell lung cancer treated in first line with standard chemotherapy. British Journal of Cancer. 116(1). 36–43. 16 indexed citations
9.
Mahalingam, Devalingam, W. Kenneth Washburn, Glenn A. Halff, et al.. (2015). Abstract 1567: A mass spectrometry based serum test for the detection of hepatocellular carcinoma (HCC) in high risk patients. Cancer Research. 75(15_Supplement). 1567–1567. 2 indexed citations
10.
Weber, Jeffrey S., Alberto J. Martinez, Heinrich Röder, et al.. (2015). Pre-treatment patient selection for nivolumab benefit based on serum mass spectra. Journal for ImmunoTherapy of Cancer. 3(Suppl 2). P103–P103. 5 indexed citations
11.
Grossi, Francesco, Carlo Genova, Erika Rijavec, et al.. (2014). Serum Mass-Spectrometry Test in First Line Advanced Nsclc Patients Treated with Standard Chemotherapy Regimens. Annals of Oncology. 25. iv463–iv463. 1 indexed citations
12.
13.
Carbone, David P., Keyue Ding, Heinrich Röder, et al.. (2012). Prognostic and Predictive Role of the VeriStrat Plasma Test in Patients with Advanced Non–Small-Cell Lung Cancer Treated with Erlotinib or Placebo in the NCIC Clinical Trials Group BR.21 Trial. Journal of Thoracic Oncology. 7(11). 1653–1660. 84 indexed citations
14.
Gautschi, Oliver, Anne‐Marie C. Dingemans, Susanne Crowe, et al.. (2012). VeriStrat® has a prognostic value for patients with advanced non-small cell lung cancer treated with erlotinib and bevacizumab in the first line: Pooled analysis of SAKK19/05 and NTR528. Lung Cancer. 79(1). 59–64. 25 indexed citations
15.
Kuiper, JG, Joline S.W. Lind, Harry J.M. Groen, et al.. (2012). VeriStrat® has prognostic value in advanced stage NSCLC patients treated with erlotinib and sorafenib. British Journal of Cancer. 107(11). 1820–1825. 34 indexed citations
16.
Lazzari, Chiara, Anna Spreafico, Angela Bachi, et al.. (2011). Changes in Plasma Mass-Spectral Profile in Course of Treatment of Non-small Cell Lung Cancer Patients with Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors. Journal of Thoracic Oncology. 7(1). 40–48. 33 indexed citations
17.
Bowlus, Christopher L., Erin H. Seeley, Joanna Roder, et al.. (2011). In situ mass spectrometry of autoimmune liver diseases. Cellular and Molecular Immunology. 8(3). 237–242. 10 indexed citations
18.
Roder, Joanna, Heinrich Röder, Julia Grigorieva, et al.. (2011). S1-4: Retrospective Analysis of Study EGF30008 by Mass-Spectrometry Based Serum Assay (VeriStrat®).. Cancer Research. 71(24_Supplement). S1–4. 2 indexed citations
19.
20.
Chung, Christine H., Erin H. Seeley, Heinrich Röder, et al.. (2010). Detection of Tumor Epidermal Growth Factor Receptor Pathway Dependence by Serum Mass Spectrometry in Cancer Patients. Cancer Epidemiology Biomarkers & Prevention. 19(2). 358–365. 51 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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