Grace O. Silva

640 total citations
8 papers, 376 citations indexed

About

Grace O. Silva is a scholar working on Cancer Research, Molecular Biology and Genetics. According to data from OpenAlex, Grace O. Silva has authored 8 papers receiving a total of 376 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cancer Research, 5 papers in Molecular Biology and 4 papers in Genetics. Recurrent topics in Grace O. Silva's work include Cancer Genomics and Diagnostics (7 papers), Genomic variations and chromosomal abnormalities (4 papers) and Gene expression and cancer classification (3 papers). Grace O. Silva is often cited by papers focused on Cancer Genomics and Diagnostics (7 papers), Genomic variations and chromosomal abnormalities (4 papers) and Gene expression and cancer classification (3 papers). Grace O. Silva collaborates with scholars based in United States. Grace O. Silva's co-authors include Charles M. Perou, Joel S. Parker, Michael L. Gatza, Huihui Fan, Mengjie Chen, Gaurav Mehta, Katherine A. Hoadley, Eliane Wauthier, Michael Torbenson and Lola M. Reid and has published in prestigious journals such as Nature Genetics, Scientific Reports and Genome biology.

In The Last Decade

Grace O. Silva

8 papers receiving 373 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Grace O. Silva United States	7	275	181	100	43	36	8	376
Yuannv Zhang China	12	382 1.4×	207 1.1×	62 0.6×	43 1.0×	32 0.9×	19	478
Jian-chuan Xia China	10	342 1.2×	114 0.6×	118 1.2×	39 0.9×	19 0.5×	12	398
Huike Jiao China	8	298 1.1×	170 0.9×	92 0.9×	98 2.3×	22 0.6×	9	396
Kun Yu Singapore	10	322 1.2×	197 1.1×	192 1.9×	54 1.3×	55 1.5×	17	501
Verónica Moncho-Amor Spain	8	263 1.0×	128 0.7×	96 1.0×	35 0.8×	21 0.6×	15	366
Xun‐Xun Wan China	9	331 1.2×	165 0.9×	149 1.5×	50 1.2×	17 0.5×	9	458
Stephanie Santiago United States	3	287 1.0×	122 0.7×	150 1.5×	60 1.4×	27 0.8×	3	391
Heping Kan China	12	290 1.1×	221 1.2×	89 0.9×	72 1.7×	10 0.3×	18	425
Zheyong Liang China	9	274 1.0×	112 0.6×	99 1.0×	50 1.2×	36 1.0×	17	411
Chen‐Yang Chen Taiwan	6	278 1.0×	209 1.2×	63 0.6×	90 2.1×	29 0.8×	8	391

Countries citing papers authored by Grace O. Silva

Since Specialization

Citations

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

Fields of papers citing papers by Grace O. Silva

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Grace O. Silva. 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 Grace O. Silva. The network helps show where Grace O. Silva may publish in the future.

Co-authorship network of co-authors of Grace O. Silva

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

All Works

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8 of 8 papers shown

Carey, Lisa A., Charles M. Perou, Joel S. Parker, et al.. (2020). Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer. UNC Libraries. 2 indexed citations

Hollern, Daniel P., Cristina M. Contreras, Grace O. Silva, et al.. (2018). A mouse model featuring tissue-specific deletion of p53 and Brca1 gives rise to mammary tumors with genomic and transcriptomic similarities to human basal-like breast cancer. Breast Cancer Research and Treatment. 174(1). 143–155. 19 indexed citations

Silva, Grace O., Marni B. Siegel, Lisle E. Mose, et al.. (2017). SynthEx: a synthetic-normal-based DNA sequencing tool for copy number alteration detection and tumor heterogeneity profiling. Genome biology. 18(1). 66–66. 19 indexed citations

Mehta, Gaurav, Joel S. Parker, Grace O. Silva, et al.. (2017). Amplification of SOX4 promotes PI3K/Akt signaling in human breast cancer. Breast Cancer Research and Treatment. 162(3). 439–450. 41 indexed citations

Dinh, Timothy A., Eliane Wauthier, Rondell P. Graham, et al.. (2017). Comprehensive analysis of The Cancer Genome Atlas reveals a unique gene and non-coding RNA signature of fibrolamellar carcinoma. Scientific Reports. 7(1). 44653–44653. 63 indexed citations

Chappell, Grace A., Grace O. Silva, Takeki Uehara, Igor P. Pogribny, & Ivan Rusyn. (2016). Characterization of copy number alterations in a mouse model of fibrosis‐associated hepatocellular carcinoma reveals concordance with human disease. Cancer Medicine. 5(3). 574–585. 6 indexed citations

Silva, Grace O., Xiaping He, Joel S. Parker, et al.. (2015). Cross-species DNA copy number analyses identifies multiple 1q21-q23 subtype-specific driver genes for breast cancer. Breast Cancer Research and Treatment. 152(2). 347–356. 36 indexed citations

Gatza, Michael L., Grace O. Silva, Joel S. Parker, Huihui Fan, & Charles M. Perou. (2014). An integrated genomics approach identifies drivers of proliferation in luminal-subtype human breast cancer. Nature Genetics. 46(10). 1051–1059. 190 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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