Daniela Intini

890 citations
23 papers · 696 · h-index 14

Impact in

  • Hematology top 5%
    • Multiple Myeloma Research and Treatments
  • Genetics top 5%
    • Chronic Lymphocytic Leukemia Research

Papers in

    • Multiple Myeloma Research and Treatments 15
    • Protein Kinase Regulation and GTPase Signaling 3
    • Glycosylation and Glycoproteins Research 3
    • PI3K/AKT/mTOR signaling in cancer 3
    • Ubiquitin and proteasome pathways 3

Daniela Intini

23 papers receiving 684 citations

Peers

Daniela Intini
Comparison fields: 5 of 63
  • Hematology 302
  • Genetics 176
  • Molecular Biology 478
  • Oncology 175
  • Pathology and Forensic Medicine 108
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Citations per field
00.5×1.5×
Nicholas Burwick · 1×
Citations per year

Countries citing papers authored by Daniela Intini

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Intini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007143
2 2005104
3 200590
4 200154
5 199949
6 200841
7 200439
8 200124
9 200021
10 200721
11 200318
12 200318
13 200817
14 200715
15
Molecular and biological characterization of three novel interleukin-6-dependent human myeloma cell lines.
200511
16 19997
17 20066
18 20126
19 20054
20 20043

About Daniela Intini

Daniela Intini is a scholar working on Hematology, Molecular Biology, Oncology, Genetics and Pathology and Forensic Medicine, having authored 23 papers that have together received 696 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (15 papers), Peptidase Inhibition and Analysis (7 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (4 papers), Protein Kinase Regulation and GTPase Signaling (3 papers), Chronic Lymphocytic Leukemia Research (3 papers), Glycosylation and Glycoproteins Research (3 papers), PI3K/AKT/mTOR signaling in cancer (3 papers) and Ubiquitin and proteasome pathways (3 papers). The work is most often cited by research in Hematology (302 citations), Genetics (176 citations), Molecular Biology (478 citations), Oncology (175 citations) and Pathology and Forensic Medicine (108 citations). Daniela Intini has collaborated with scholars based in Italy, Switzerland and Japan. Frequent co-authors include Antonino Neri, Sonia Fabris, Luca Baldini, Luigia Lombardi, Luca Agnelli, Donata Verdelli, Vincenzo Callea, Fortunato Morabito, Anna Teresa Maiolo and Michela Mattioli. Their work appears in journals such as Blood, Genes Chromosomes and Cancer, British Journal of Haematology, Leukemia and Hematological Oncology.

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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