Daniela S. Gerhard

45.8k total citations · 2 hit papers
82 papers, 3.9k citations indexed

About

Daniela S. Gerhard is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Daniela S. Gerhard has authored 82 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 23 papers in Cancer Research and 18 papers in Genetics. Recurrent topics in Daniela S. Gerhard's work include Cancer Genomics and Diagnostics (13 papers), Genomic variations and chromosomal abnormalities (11 papers) and Acute Myeloid Leukemia Research (10 papers). Daniela S. Gerhard is often cited by papers focused on Cancer Genomics and Diagnostics (13 papers), Genomic variations and chromosomal abnormalities (11 papers) and Acute Myeloid Leukemia Research (10 papers). Daniela S. Gerhard collaborates with scholars based in United States, Canada and Germany. Daniela S. Gerhard's co-authors include David E. Housman, Janice A. Egeland, David L. Pauls, Kenneth K. Kídd, Abram M. Hostetter, Jon Sussex, T Gingeras, Antonio Piccolboni, Hari Tammana and David L. Stern and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Daniela S. Gerhard

81 papers receiving 3.8k 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.

Transcriptional Maps of 10 Human Chromosomes at 5-Nucleotide Resolution

2005 881 citations Jill Cheng, Philipp Kapranov et al. Science profile →
Bipolar affective disorders linked to DNA markers on chromosome 11

1987 565 citations Daniela S. Gerhard, David E. Housman et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniela S. Gerhard United States	30	2.3k	1.1k	777	404	322	82	3.9k
Samuel S. Chong Singapore	35	2.1k 0.9×	1.2k 1.1×	422 0.5×	665 1.6×	592 1.8×	167	4.8k
Giulio Genovese United States	33	2.6k 1.1×	1.8k 1.6×	434 0.6×	207 0.5×	305 0.9×	67	6.8k
Torben A. Kruse Denmark	39	2.7k 1.2×	1.1k 1.0×	979 1.3×	565 1.4×	441 1.4×	214	5.2k
Michael J. Higgins United States	31	3.1k 1.3×	1.9k 1.7×	585 0.8×	220 0.5×	125 0.4×	104	4.2k
Jutta Gärtner Germany	49	3.6k 1.6×	944 0.8×	315 0.4×	506 1.3×	362 1.1×	217	7.6k
Hossein Najmabadi Iran	41	3.5k 1.5×	1.7k 1.5×	493 0.6×	231 0.6×	865 2.7×	292	6.5k
R S Sparkes United States	37	2.9k 1.3×	2.1k 1.8×	265 0.3×	374 0.9×	274 0.9×	142	5.1k
Michel Guipponi Switzerland	32	2.1k 0.9×	931 0.8×	286 0.4×	274 0.7×	94 0.3×	87	3.7k
Stacey B. Gabriel United States	11	1.7k 0.7×	1.6k 1.4×	418 0.5×	235 0.6×	78 0.2×	13	3.6k
Batsheva Kerem Israel	48	4.2k 1.8×	1.8k 1.6×	441 0.6×	553 1.4×	66 0.2×	98	8.0k

Countries citing papers authored by Daniela S. Gerhard

Since Specialization

Citations

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

Fields of papers citing papers by Daniela S. Gerhard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniela S. Gerhard

This figure shows the co-authorship network connecting the top 25 collaborators of Daniela S. Gerhard. A scholar is included among the top collaborators of Daniela S. Gerhard 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 Daniela S. Gerhard. Daniela S. Gerhard 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

Xu, Gufeng, John Hicks, Manjula Nakka, et al.. (2023). The Role of FAS Receptor Methylation in Osteosarcoma Metastasis. International Journal of Molecular Sciences. 24(15). 12155–12155. 1 indexed citations

López, Gonzalo, Karina L. Conkrite, Komal S. Rathi, et al.. (2020). Somatic structural variation targets neurodevelopmental genes and identifies SHANK2 as a tumor suppressor in neuroblastoma. Genome Research. 30(9). 1228–1242. 14 indexed citations

Whalley, Justin P., Ivo Buchhalter, Esther Rheinbay, et al.. (2020). Framework for quality assessment of whole genome cancer sequences. Nature Communications. 11(1). 5040–5040. 4 indexed citations

Wei, Jun S., Igor B. Kuznetsov, Shile Zhang, et al.. (2018). Clinically Relevant Cytotoxic Immune Cell Signatures and Clonal Expansion of T-Cell Receptors in High-Risk MYCN -Not-Amplified Human Neuroblastoma. Clinical Cancer Research. 24(22). 5673–5684. 76 indexed citations

Armstrong, Amy E., Samantha Gadd, Vicki Huff, et al.. (2018). A unique subset of low-risk Wilms tumors is characterized by loss of function of TRIM28 (KAP1), a gene critical in early renal development: A Children’s Oncology Group study. PLoS ONE. 13(12). e0208936–e0208936. 30 indexed citations

Farrar, Jason E., Rhonda E. Ries, Daniel Wai, et al.. (2016). Genomic Profiling of Pediatric Acute Myeloid Leukemia Reveals a Changing Mutational Landscape from Disease Diagnosis to Relapse. Cancer Research. 76(8). 2197–2205. 104 indexed citations

Farrar, Jason E., Hamid Bolouri, Rhonda E. Ries, et al.. (2016). Marked Differences in the Genomic Landscape of Pediatric Compared to Adult Acute Myeloid Leukemia: A Report from the Children's Oncology Group and NCI/COG Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Initiative. Blood. 128(22). 595–595. 2 indexed citations

García‐Closas, Montserrat, Vessela N. Kristensen, Anita Langerød, et al.. (2007). Common genetic variation in TP53 and its flanking genes, WDR79 and ATP1B2, and susceptibility to breast cancer. International Journal of Cancer. 121(11). 2532–2538. 46 indexed citations

Klein, Steven L., Daniela S. Gerhard, Lukas Wagner, et al.. (2006). Resources for Genetic and Genomic Studies of Xenopus. Methods in molecular biology. 322. 1–16. 10 indexed citations

10.

Cheng, Jill, Philipp Kapranov, Jörg Drenkow, et al.. (2005). Transcriptional Maps of 10 Human Chromosomes at 5-Nucleotide Resolution. Science. 308(5725). 1149–1154. 881 indexed citations breakdown →

11.

O’Sullivan, Maureen J., Janet S. Rader, Daniela S. Gerhard, et al.. (2001). Loss of heterozygosity at 11q23.3 in vasculoinvasive and metastatic squamous cell carcinoma of the cervix. Human Pathology. 32(5). 475–478. 13 indexed citations

12.

Stöhr, Heidi, Andreas Marquardt, Paul R. Cooper, et al.. (1998). A Gene Map of the Best’s Vitelliform Macular Dystrophy Region in Chromosome 11q12–q13.1. Genome Research. 8(1). 48–56. 20 indexed citations

13.

Huettner, Phyllis C., et al.. (1998). Loss of heterozygosity in clinical stage IB cervical carcinoma: Relationship with clinical and histopathologic features. Human Pathology. 29(4). 364–370. 29 indexed citations

14.

Williams, John B., Brent N. Rexer, Sutha K. John, et al.. (1997). The Human HNP36 Gene Is Localized to Chromosome 11q13 and Produces Alternative Transcripts That Are Not Mutated in Multiple Endocrine Neoplasia, Type 1 (MEN I) Syndrome. Genomics. 42(2). 325–330. 5 indexed citations

15.

Bora, Puran S., et al.. (1995). Genetic and radiation-reduced somatic cell hybrid sublocalization of the human GSTP1 gene. Cytogenetic and Genome Research. 71(3). 235–239. 11 indexed citations

16.

Bascom, R.A., Jaime Garcia‐Heras, C L Hsieh, et al.. (1992). Localization of the photoreceptor gene ROM1 to human chromosome 11 and mouse chromosome 19: sublocalization to human 11q13 between PGA and PYGM.. Europe PMC (PubMed Central). 51(5). 1028–35. 31 indexed citations

17.

Collier, Ivan E., G.A.P. Bruns, Gregory I. Goldberg, & Daniela S. Gerhard. (1991). On the structure and chromosome location of the 72- and 92-kDa human type IV collagenase genes. Genomics. 9(3). 429–434. 56 indexed citations

18.

Ma, N.S.F., Daniela S. Gerhard, David E. Housman, Stuart H. Orkin, & G.A.P. Bruns. (1986). Owl monkey gene mapping: the assignment of gene loci for catalase, β-globin gene cluster, HRAS1, insulin, and parathyroid hormone. Cytogenetic and Genome Research. 43(1-2). 57–68. 7 indexed citations

19.

Elsen, Peter J. van den, G.A.P. Bruns, Daniela S. Gerhard, et al.. (1985). Assignment of the gene coding for the T3-delta subunit of the T3-T-cell receptor complex to the long arm of human chromosome 11 and to mouse chromosome 9.. Proceedings of the National Academy of Sciences. 82(9). 2920–2924. 56 indexed citations

20.

Gerhard, Daniela S., Paul Szabo, Ernest S. Kawasaki, & Frank C. Bancroft. (1984). The Prolactin Gene, but Not the Growth Hormone Gene, Is Located on Chromosome 9 in the Rat. DNA. 3(2). 139–145. 3 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.

Explore authors with similar magnitude of impact