Marella Maroder

35 papers receiving 1.7k citations

Peers

Marella Maroder
Comparison fields: 5 of 96
  • Cancer Research 270
  • Developmental Neuroscience 69
  • Molecular Biology 1.1k
  • Immunology 340
  • Oncology 360
Replace Daniela Meco with:
Daniela Meco Italy
María Pía Felli Italy
J N Wilcox United States
Joshua D. Stender United States
Robert Signer United States
Klaus‐Dieter Fischer Germany
Kanji Yoshida Japan
Helena Selawry United States
Christina Jamieson United States
Hagar Kalinski Israel
Marella Maroder relative to Daniela Meco Italy Daniela Meco's profile →
Citations per field
00.5×1.5×2.3×
Daniela Meco · 1×
Citations per year

Countries citing papers authored by Marella Maroder

Since Specialization
Citations

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

Fields of papers citing papers by Marella Maroder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006224
2 1992200
3 2004135
4
Transcriptional up-regulation of matrix metalloproteinase-9 expression during spontaneous epithelial to neuroblast phenotype conversion by SK-N-SH neuroblastoma cells, involved in enhanced invasivity, depends upon GT-box and nuclear factor kappaB elements.
1999115
5 199685
6 201180
7 199578
8 199066
9 199661
10 200559
11 201152
12 202052
13 199152
14 200249
15 199347
16 201943
17 200841
18 199438
19 199436
20 200636

About Marella Maroder

Marella Maroder is a scholar working on Immunology, Virology, Cancer Research, Molecular Biology and Oncology, having authored 35 papers that have together received 1.8k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (12 papers), Hedgehog Signaling Pathway Studies (8 papers), NF-κB Signaling Pathways (6 papers), Pancreatic function and diabetes (4 papers), Estrogen and related hormone effects (4 papers), Signaling Pathways in Disease (3 papers), Genomics and Chromatin Dynamics (3 papers) and Retinoids in leukemia and cellular processes (3 papers). The work is most often cited by research in Cancer Research (270 citations), Developmental Neuroscience (69 citations), Molecular Biology (1.1k citations), Immunology (340 citations) and Oncology (360 citations). Marella Maroder has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Alberto Gulino, Isabella Screpanti, Alessandra Vacca, Antonietta R. Farina, Lucia Di Marcotullio, Enrico De Smaele, Daniela Meco, Elisabetta Ferretti, María Pía Felli and Stefano Martinotti. Their work appears in journals such as The Journal of Experimental Medicine, The Journal of Cell Biology, Neoplasia, Molecular Endocrinology and The Journal of Immunology.

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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