L Marasà

32 papers receiving 1.0k citations

Peers

L Marasà
Comparison fields: 5 of 90
  • Reproductive Medicine 170
  • Genetics 186
  • Obstetrics and Gynecology 59
  • Molecular Biology 439
  • Aging 10
Replace Katsuyuki Hamada with:
Katsuyuki Hamada Japan
Travis Solley United States
Ileana Cuevas United States
Daniel Nettersheim Germany
I.-M. Shih United States
Oscar Berlanga United Kingdom
Serah Choi United States
Chiara Romani Italy
Bellinda A. Bladergroen Netherlands
Andy J.G. Pötgens Germany
L Marasà relative to Katsuyuki Hamada Japan Katsuyuki Hamada's profile →
Citations per field
00.5×5.2×
Katsuyuki Hamada · 1×
Citations per year

Countries citing papers authored by L Marasà

Since Specialization
Citations

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

Fields of papers citing papers by L Marasà

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008235
2 2008217
3 1993172
4 2005114
5 199964
6 200730
7 200925
8 200624
9 200619
10 201117
11 200916
12 200814
13 200014
14 20009
15
Collagen IV, laminin, fibronectin, vitronectin. Comparative study in basal cell carcinoma. Correlation between basement membrane molecules expression and invasive potential.
20088
16
Quantitative image analysis of estrogen and progesterone receptors as a prognostic tool for selecting breast cancer patients for therapy.
19997
17 19977
18
[Angiogenetic capacity of breast neoplasms and correlation with color-Doppler semiology].
19947
19
Cystic hydatidosis: a rare case of spine localization.
20116
20 20095

About L Marasà

L Marasà is a scholar working on Surgery, Molecular Biology, Oncology, Pathology and Forensic Medicine and Immunology, having authored 33 papers that have together received 1.0k indexed citations. Recurring topics across this work include Heat shock proteins research (4 papers), Galectins and Cancer Biology (2 papers), IL-33, ST2, and ILC Pathways (2 papers), Breast Lesions and Carcinomas (2 papers), Amoebic Infections and Treatments (2 papers), Immunotherapy and Immune Responses (2 papers), Cell Adhesion Molecules Research (2 papers) and Sarcoma Diagnosis and Treatment (1 paper). The work is most often cited by research in Reproductive Medicine (170 citations), Genetics (186 citations), Obstetrics and Gynecology (59 citations), Molecular Biology (439 citations) and Aging (10 citations). L Marasà has collaborated with scholars based in Italy, Spain and France. Frequent co-authors include Francesco Cappello, Giovanni Zummo, Everly Conway de Macario, Alberto J.L. Macario, Errico Zupi, Francesco Maneschi, Felicia Farina, Simona Corrao, Giampiero La Rocca and Rita Anzalone. Their work appears in journals such as Annals of the New York Academy of Sciences, Haematologica, Oncology Reviews, Cancer Biology & Therapy and Histopathology.

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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