Daniela Cordella

513 citations
9 papers · 367 · h-index 8

Impact in

Papers in

    • Wnt/β-catenin signaling in development and cancer 2
    • Kruppel-like factors research 1
    • TGF-β signaling in diseases 1
    • Thyroid Disorders and Treatments 3
    • Growth Hormone and Insulin-like Growth Factors 2
    • Thyroid Cancer Diagnosis and Treatment 2

Daniela Cordella

9 papers receiving 361 citations

Peers

Daniela Cordella
Comparison fields: 5 of 47
  • Endocrinology, Diabetes and Metabolism 183
  • Genetics 64
  • Hematology 31
  • Molecular Biology 178
  • Oncology 64
Replace Laura Fazzuoli with:
Laura Fazzuoli Italy
Lindsay G. Horton United States
H Jahr Germany
Yuichi Fujinaka Japan
Karen Verity Australia
Steven Schoenfeld United States
Dunyong Tan United States
Wojciech Garczorz Poland
Elisabetta Cecconi Italy
Daniela Cordella relative to Laura Fazzuoli Italy Laura Fazzuoli's profile →
Citations per field
00.5×3.5×
Laura Fazzuoli · 1×
Citations per year

Countries citing papers authored by Daniela Cordella

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Cordella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 2012123
2 201073
3 201140
4 201035
5 200832
6 201028
7 200523
8 200611
9
Prevalence of inactivating TSH receptor (TSHR) mutations in a large series of pediatric subjects with non-autoimmune mild hyper-thyrotropinemia (hyperTSH)
20072

About Daniela Cordella

Daniela Cordella is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Oncology, Genetics and Nephrology, having authored 9 papers that have together received 367 indexed citations. Recurring topics across this work include Thyroid Disorders and Treatments (3 papers), Cancer-related Molecular Pathways (3 papers), Wnt/β-catenin signaling in development and cancer (2 papers), Growth Hormone and Insulin-like Growth Factors (2 papers), Thyroid Cancer Diagnosis and Treatment (2 papers), Kruppel-like factors research (1 paper), TGF-β signaling in diseases (1 paper) and Blood groups and transfusion (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (183 citations), Genetics (64 citations), Hematology (31 citations), Molecular Biology (178 citations) and Oncology (64 citations). Daniela Cordella has collaborated with scholars based in Italy, Germany and Iran. Frequent co-authors include Luca Persani, Davide Calebiro, Marco Bonomi, Giovanna Weber, Paolo Madeddu, Costanza Emanueli, Orazio Fortunato, Domenico Libri, Gaia Spinetti and Giulia Gelmini. Their work appears in journals such as Circulation Research, Endocrine Related Cancer, European Journal of Endocrinology, Molecular and Cellular Endocrinology and Clinical Endocrinology.

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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