Debora Mancini‐DiNardo

2.2k total citations · 1 hit paper
23 papers, 1.7k citations indexed

About

Debora Mancini‐DiNardo is a scholar working on Genetics, Molecular Biology and Pathology and Forensic Medicine. According to data from OpenAlex, Debora Mancini‐DiNardo has authored 23 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Genetics, 12 papers in Molecular Biology and 8 papers in Pathology and Forensic Medicine. Recurrent topics in Debora Mancini‐DiNardo's work include Genetic factors in colorectal cancer (7 papers), Cancer Genomics and Diagnostics (7 papers) and Genomic variations and chromosomal abnormalities (6 papers). Debora Mancini‐DiNardo is often cited by papers focused on Genetic factors in colorectal cancer (7 papers), Cancer Genomics and Diagnostics (7 papers) and Genomic variations and chromosomal abnormalities (6 papers). Debora Mancini‐DiNardo collaborates with scholars based in United States, Canada and United Kingdom. Debora Mancini‐DiNardo's co-authors include Stefan Enroth, Radha Raman Pandey, Takashi Nagano, Chandrasekhar Kanduri, Tanmoy Mondal, Faizaan Mohammad, Jan Komorowski, Shirley M. Tilghman, John M. Levorse and Scott J. Steele and has published in prestigious journals such as Journal of Clinical Oncology, Genes & Development and Molecular Cell.

In The Last Decade

Debora Mancini‐DiNardo

23 papers receiving 1.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Kcnq1ot1 Antisense Noncoding RNA Mediates Lineage-Specific Transcriptional Silencing through Chromatin-Level Regulation

2008 926 citations Radha Raman Pandey, Tanmoy Mondal et al. Molecular Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Debora Mancini‐DiNardo United States	12	1.5k	917	545	181	126	23	1.7k
Paul Monnier France	5	887 0.6×	778 0.8×	214 0.4×	113 0.6×	25 0.2×	7	1.1k
Tomomi Yoshimizu Japan	6	865 0.6×	333 0.4×	304 0.6×	93 0.5×	11 0.1×	7	978
Heather Pierce United States	11	512 0.3×	134 0.1×	247 0.5×	24 0.1×	23 0.2×	16	728
Franck Court France	19	888 0.6×	196 0.2×	416 0.8×	257 1.4×	5 0.0×	37	1.0k
Izuho Hatada Japan	15	866 0.6×	94 0.1×	607 1.1×	346 1.9×	9 0.1×	25	1.0k
Ivan Raimondi United States	14	1.2k 0.8×	1.1k 1.2×	56 0.1×	6 0.0×	28 0.2×	19	1.5k
Alberto Corradin Italy	11	459 0.3×	251 0.3×	207 0.4×	91 0.5×	13 0.1×	16	1.0k
Marieke Levitus Netherlands	10	973 0.7×	338 0.4×	307 0.6×	22 0.1×	5 0.0×	12	1.1k
Alayne Brunner United States	10	573 0.4×	359 0.4×	99 0.2×	11 0.1×	12 0.1×	16	828

Countries citing papers authored by Debora Mancini‐DiNardo

Since Specialization

Citations

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

Fields of papers citing papers by Debora Mancini‐DiNardo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Debora Mancini‐DiNardo. 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 Debora Mancini‐DiNardo. The network helps show where Debora Mancini‐DiNardo may publish in the future.

Co-authorship network of co-authors of Debora Mancini‐DiNardo

This figure shows the co-authorship network connecting the top 25 collaborators of Debora Mancini‐DiNardo. A scholar is included among the top collaborators of Debora Mancini‐DiNardo 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 Debora Mancini‐DiNardo. Debora Mancini‐DiNardo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Pan, Shujuan, Hannah C. Cox, Erin Mundt, et al.. (2023). Discordance between germline genetic findings and abnormal tumor immunohistochemistry staining of mismatch repair proteins in individuals with suspected Lynch syndrome. Frontiers in Oncology. 13. 1069467–1069467. 5 indexed citations

2.

Jones, Melanie A., Kirsten M. Timms, Elizabeth S. Cogan, et al.. (2023). The landscape of BRCA1 and BRCA2 large rearrangements in an international cohort of over 20 000 ovarian tumors identified using next‐generation sequencing. Genes Chromosomes and Cancer. 62(10). 589–596. 3 indexed citations

3.

Clegg, Benjamin A., Elizabeth S. Cogan, M. D. Perry, et al.. (2022). Rates of homologous recombination deficiency across different subtypes of ovarian cancer and in pre- and post-neoadjuvant chemotherapy tumor samples (139.5). Gynecologic Oncology. 166. S86–S87. 6 indexed citations

4.

Mancini‐DiNardo, Debora, Thaddeus Judkins, John Kidd, et al.. (2019). Detection of large rearrangements in a hereditary pan-cancer panel using next-generation sequencing. BMC Medical Genomics. 12(1). 138–138. 16 indexed citations

5.

Coffee, Bradford, Hannah C. Cox, Ryan Bernhisel, et al.. (2019). A substantial proportion of apparently heterozygousTP53pathogenic variants detected with a next‐generation sequencing hereditary pan‐cancer panel are acquired somatically. Human Mutation. 41(1). 203–211. 19 indexed citations

6.

Slavin, Thomas P., Bradford Coffee, Ryan Bernhisel, et al.. (2019). Prevalence and characteristics of likely-somatic variants in cancer susceptibility genes among individuals who had hereditary pan-cancer panel testing. Cancer Genetics. 235-236. 31–38. 24 indexed citations

7.

Bowles, Karla R., Debora Mancini‐DiNardo, Bradford Coffee, et al.. (2018). Hereditary Cancer Testing Challenges: Assembling the Analytical Pieces to Solve the Patient Clinical Puzzle. Future Oncology. 15(1). 65–79. 3 indexed citations

8.

Pan, Shujuan, Hannah C. Cox, Krystal Brown, et al.. (2017). Pan-cancer panel testing in individuals with abnormal immunohistochemistry (IHC) staining of the mismatch-repair (MMR) genes.. Journal of Clinical Oncology. 35(15_suppl). e13014–e13014. 1 indexed citations

9.

Coffee, Bradford, Hannah C. Cox, John Kidd, et al.. (2017). Detection of somatic variants in peripheral blood lymphocytes using a next generation sequencing multigene pan cancer panel. Cancer Genetics. 211. 5–8. 39 indexed citations

10.

Qian, Yaping, Debora Mancini‐DiNardo, Thaddeus Judkins, et al.. (2017). Identification of pathogenic retrotransposon insertions in cancer predisposition genes. Cancer Genetics. 216-217. 159–169. 29 indexed citations

11.

Coffee, Bradford, et al.. (2016). Detection of somatic variants in peripheral blood lymphocytes using a 25-gene hereditary cancer panel.. Journal of Clinical Oncology. 34(15_suppl). 1580–1580. 1 indexed citations

12.

Mancini‐DiNardo, Debora, Thaddeus Judkins, Natalia Gutin, et al.. (2014). Design and validation of an oligonucleotide microarray for the detection of genomic rearrangements associated with common hereditary cancer syndromes. Journal of Experimental & Clinical Cancer Research. 33(1). 74–74. 5 indexed citations

13.

Mancini‐DiNardo, Debora, Thaddeus Judkins, Natalia Gutin, et al.. (2014). Design and validation of an oligonucleotide microarray for the detection of genomic rearrangements associated with common hereditary cancer syndromes. Journal of Experimental & Clinical Cancer Research. 33(1). 74–74. 1 indexed citations

14.

Zimmerman, Rebekah, Stephanie Cox, Neal K. Lakdawala, et al.. (2010). A novel custom resequencing array for dilated cardiomyopathy. Genetics in Medicine. 12(5). 268–278. 64 indexed citations

15.

Joshi, Victoria A., Elizabeth Hynes, Birgit Funke, et al.. (2009). Platform Evaluation for Rapid Genotyping of CYP2C9 and VKORC1 Alleles. Personalized Medicine. 6(4). 449–457. 1 indexed citations

16.

Joshi, Victoria A., Debora Mancini‐DiNardo, & Birgit Funke. (2008). Selection of a Platform for Mutation Detection. Current Protocols in Human Genetics. 56(1). Unit 7.15–Unit 7.15. 4 indexed citations

17.

Pandey, Radha Raman, Tanmoy Mondal, Faizaan Mohammad, et al.. (2008). Kcnq1ot1 Antisense Noncoding RNA Mediates Lineage-Specific Transcriptional Silencing through Chromatin-Level Regulation. Molecular Cell. 32(2). 232–246. 926 indexed citations breakdown →

18.

Butcher, Darci T., Debora Mancini‐DiNardo, Trevor Archer, & David I. Rodenhiser. (2004). DNA binding sites for putative methylation boundaries in the unmethylated region of the BRCA1 promoter. International Journal of Cancer. 111(5). 669–678. 54 indexed citations

19.

Mancini‐DiNardo, Debora. (2003). A differentially methylated region within the gene Kcnq1 functions as an imprinted promoter and silencer. Human Molecular Genetics. 12(3). 283–294. 6 indexed citations

20.

Mancini‐DiNardo, Debora. (2003). A differentially methylated region within the gene Kcnq1 functions as an imprinted promoter and silencer. Human Molecular Genetics. 12(3). 283–294. 106 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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