Diana Resetca

1.4k citations
12 papers · 840 · 1 hit paper · h-index 9

Impact in

Papers in

    • Genomics and Chromatin Dynamics 4
    • Ubiquitin and proteasome pathways 4
    • Protein Degradation and Inhibitors 3
    • Cytokine Signaling Pathways and Interactions 3

Diana Resetca

11 papers receiving 835 citations

Hit Papers

MYC protein interactors in gene transcription and cancer 2021 · 209 citations
2090+1+3Years since publication50100150200

Peers

Diana Resetca
Comparison fields: 5 of 77
  • Cancer Research 144
  • Oncology 260
  • Molecular Biology 646
  • Cell Biology 71
  • Hematology 38
Replace Aparna Mani with:
Aparna Mani United States
Fumi Kinose United States
Kevin Hudson United Kingdom
Johanne Bentley United Kingdom
David James VanderWeele United States
Ruth Ruddle United Kingdom
Jason De Melo Canada
Margarita Maurer‐Granofszky Austria
Ashutosh Pal United States
Bram Thijssen Netherlands
Diana Resetca relative to Aparna Mani United States Aparna Mani's profile →
Citations per field
00.5×6.4×
Aparna Mani · 1×
Citations per year

Countries citing papers authored by Diana Resetca

Since Specialization
Citations

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

Fields of papers citing papers by Diana Resetca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 2017285
2
MYC protein interactors in gene transcription and cancer
Hit paper breakdown →
2021209
3 2018120
4 201844
5 201643
6 201939
7 201439
8 201329
9 201117
10 20168
11 20177
12 20210

About Diana Resetca

Diana Resetca is a scholar working on Molecular Biology, Oncology, Pathology and Forensic Medicine, Pharmacology and Spectroscopy, having authored 12 papers that have together received 840 indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (4 papers), Ubiquitin and proteasome pathways (4 papers), Protein Degradation and Inhibitors (3 papers), Cytokine Signaling Pathways and Interactions (3 papers), Cancer Mechanisms and Therapy (2 papers), Mass Spectrometry Techniques and Applications (2 papers), Medicinal Plant Pharmacodynamics Research (1 paper) and Chronic Myeloid Leukemia Treatments (1 paper). The work is most often cited by research in Cancer Research (144 citations), Oncology (260 citations), Molecular Biology (646 citations), Cell Biology (71 citations) and Hematology (38 citations). Diana Resetca has collaborated with scholars based in Canada, Sweden and Italy. Frequent co-authors include Linda Z. Penn, Corey Lourenco, Manpreet Kalkat, Jason De Melo, Derek J. Wilson, William B. Tu, Brian Raught, Yong Wei, Maria Sunnerhagen and Patrick T. Gunning. Their work appears in journals such as Nature reviews. Cancer, Oncotarget, Nature Structural & Molecular Biology, Nature Communications and Journal of Biological Chemistry.

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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