Daniel Mailo

967 total citations
11 papers, 669 citations indexed

About

Daniel Mailo is a scholar working on Oncology, Molecular Biology and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Daniel Mailo has authored 11 papers receiving a total of 669 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Oncology, 7 papers in Molecular Biology and 2 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Daniel Mailo's work include Cancer Risks and Factors (6 papers), Cancer-related Molecular Pathways (3 papers) and Cancer Cells and Metastasis (3 papers). Daniel Mailo is often cited by papers focused on Cancer Risks and Factors (6 papers), Cancer-related Molecular Pathways (3 papers) and Cancer Cells and Metastasis (3 papers). Daniel Mailo collaborates with scholars based in United States, Italy and Argentina. Daniel Mailo's co-authors include José Russo, Gabriela Balogh, Irma H. Russo, Raquel Moral, Fathima Sheriff, Yun‐Fu Hu, Patrícia A. Russo, Coral A. Lamartiniere, Federica Perrone and Antonella De Luca and has published in prestigious journals such as Clinical Cancer Research, BMC Genomics and Breast Cancer Research.

In The Last Decade

Daniel Mailo

10 papers receiving 640 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Daniel Mailo United States	9	449	226	187	118	84	11	669
D.S. Allen United Kingdom	14	225 0.5×	69 0.3×	132 0.7×	109 0.9×	78 0.9×	19	485
A. Joan Levine United States	14	237 0.5×	488 2.2×	135 0.7×	145 1.2×	90 1.1×	23	962
Kari Hemminki Sweden	12	205 0.5×	146 0.6×	176 0.9×	212 1.8×	29 0.3×	16	594
Lihua Wu China	11	163 0.4×	357 1.6×	124 0.7×	65 0.6×	223 2.7×	39	828
Anita Chudecka-Głaz Poland	17	232 0.5×	227 1.0×	120 0.6×	155 1.3×	43 0.5×	85	863
Douglas F. Easton United Kingdom	5	325 0.7×	159 0.7×	421 2.3×	145 1.2×	22 0.3×	8	671
Hiroshi Toyoki Japan	16	136 0.3×	251 1.1×	161 0.9×	99 0.8×	44 0.5×	27	567
Jessica Clague United States	13	183 0.4×	396 1.8×	255 1.4×	269 2.3×	42 0.5×	18	775
Nur Zeinomar United States	11	211 0.5×	76 0.3×	96 0.5×	116 1.0×	21 0.3×	29	439
C. A. Haiman United States	3	105 0.2×	197 0.9×	162 0.9×	70 0.6×	57 0.7×	3	388

Countries citing papers authored by Daniel Mailo

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Mailo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Mailo

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Mailo. A scholar is included among the top collaborators of Daniel Mailo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Mailo. Daniel Mailo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

1.

Balogh, Gabriela, et al.. (2010). Serological levels of mutated p53 protein are highly detected at early stages in breast cancer patients. Experimental and Therapeutic Medicine. 1(2). 357–361. 16 indexed citations

2.

Russo, José, et al.. (2007). The Genomic Signature of Breast Cancer Prevention. PubMed. 174. 131–150. 9 indexed citations

3.

Moral, Raquel, et al.. (2007). The plasticizer butyl benzyl phthalate induces genomic changes in rat mammary gland after neonatal/prepubertal exposure. BMC Genomics. 8(1). 453–453. 39 indexed citations

4.

Balogh, Gabriela, et al.. (2007). Methodological approach to study the genomic profile of the human breast. International Journal of Oncology. 31(2). 253–60. 8 indexed citations

5.

Russo, Irma H., Fathima Sheriff, Peter A. Morrison, et al.. (2007). The breast of parous women without cancer has a different genomic profile compared to those with cancer. International Journal of Oncology. 31(5). 1165–75. 11 indexed citations

6.

Russo, José, Gabriela Balogh, Daniel Mailo, et al.. (2006). Molecular basis of pregnancy-induced breast cancer protection. European Journal of Cancer Prevention. 15(4). 306–342. 56 indexed citations

7.

Balogh, Gabriela, Daniel Mailo, Patrícia A. Russo, et al.. (2006). Genomic signature induced by pregnancy in the human breast. International Journal of Oncology. 28(2). 399–410. 50 indexed citations

8.

Bianco, Caterina, Luigi Strizzi, Mario Mancino, et al.. (2006). Identification of Cripto-1 as a Novel Serologic Marker for Breast and Colon Cancer. Clinical Cancer Research. 12(17). 5158–5164. 74 indexed citations

9.

Moral, Raquel, et al.. (2005). Review The protective role of pregnancy in breast cancer.

10.

Russo, José, Raquel Moral, Gabriela Balogh, Daniel Mailo, & Irma H. Russo. (2005). The protective role of pregnancy in breast cancer. Breast Cancer Research. 7(3). 131–42. 292 indexed citations

11.

Russo, José, Daniel Mailo, Yun‐Fu Hu, et al.. (2005). Breast Differentiation and Its Implication in Cancer Prevention. Clinical Cancer Research. 11(2). 931s–936s. 114 indexed citations

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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