Sumana Narayanan

1.0k citations
26 papers · 720 · h-index 16

Impact in

  • Oncology top 10%
    • Cancer Immunotherapy and Biomarkers
    • Cancer-related Molecular Pathways
    • Cancer Genomics and Diagnostics

Papers in

    • Cancer Immunotherapy and Biomarkers 3
    • Cancer-related Molecular Pathways 3
    • Esophageal Cancer Research and Treatment 2
    • Thyroid and Parathyroid Surgery 2

Sumana Narayanan

26 papers receiving 711 citations

Peers

Sumana Narayanan
Comparison fields: 5 of 82
  • Oncology 392
  • Cancer Research 147
  • Pulmonary and Respiratory Medicine 218
  • Immunology 105
  • Hepatology 34
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Citations per year

Countries citing papers authored by Sumana Narayanan

Since Specialization
Citations

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

Fields of papers citing papers by Sumana Narayanan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sumana Narayanan, 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 Sumana Narayanan Line = papers co-authored together Sumana Narayanan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018117
2 201988
3 201482
4 201455
5 201844
6
High expression of polo-like kinase 1 is associated with TP53 inactivation, DNA repair deficiency, and worse prognosis in ER positive Her2 negative breast cancer.
201943
7 202042
8 202038
9 201429
10 201824
11 201522
12 201522
13 201821
14
Immune cytolytic activity is associated with reduced intra-tumoral genetic heterogeneity and with better clinical outcomes in triple negative breast cancer.
202120
15 202017
16 199716
17 201711
18 201710
19 20206
20 20204

About Sumana Narayanan

Sumana Narayanan is a scholar working on Oncology, Surgery, Pulmonary and Respiratory Medicine, Cancer Research and Pathology and Forensic Medicine, having authored 26 papers that have together received 720 indexed citations. Recurring topics across this work include Genetic factors in colorectal cancer (3 papers), Cancer Immunotherapy and Biomarkers (3 papers), Cancer Genomics and Diagnostics (3 papers), Cancer-related Molecular Pathways (3 papers), Gastric Cancer Management and Outcomes (3 papers), Ferroptosis and cancer prognosis (3 papers), Esophageal Cancer Research and Treatment (2 papers) and Thyroid and Parathyroid Surgery (2 papers). The work is most often cited by research in Oncology (392 citations), Cancer Research (147 citations), Pulmonary and Respiratory Medicine (218 citations), Immunology (105 citations) and Hepatology (34 citations). Sumana Narayanan has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Kazuaki Takabe, Li Yan, Xuan Peng, Tsutomu Kawaguchi, Qianya Qi, Darren R. Carpizo, Xin Yu, Alexei Vázquez, Song Liu and Kristopher Attwood. Their work appears in journals such as Annals of Surgical Oncology, Journal of Surgical Oncology, Scientific Reports, British Journal of Haematology and Journal of Surgical 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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