Gordon Saksena

112.6k total citations · 2 hit papers
15 papers, 3.0k citations indexed

About

Gordon Saksena is a scholar working on Molecular Biology, Cancer Research and Pathology and Forensic Medicine. According to data from OpenAlex, Gordon Saksena has authored 15 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 8 papers in Cancer Research and 5 papers in Pathology and Forensic Medicine. Recurrent topics in Gordon Saksena's work include Cancer Genomics and Diagnostics (7 papers), Genetic factors in colorectal cancer (4 papers) and RNA modifications and cancer (3 papers). Gordon Saksena is often cited by papers focused on Cancer Genomics and Diagnostics (7 papers), Genetic factors in colorectal cancer (4 papers) and RNA modifications and cancer (3 papers). Gordon Saksena collaborates with scholars based in United States, United Kingdom and Sweden. Gordon Saksena's co-authors include Gad Getz, Michael S. Lawrence, Scott L. Carter, Matthew Meyerson, Stacey Gabriel, Steven E. Schumacher, Rameen Beroukhim, Craig H. Mermel, Andrew D. Cherniack and Barbara Tabak and has published in prestigious journals such as Nature Communications, Nature Genetics and Blood.

In The Last Decade

Gordon Saksena

15 papers receiving 2.9k citations

Hit Papers

align trajectories sort by overperformance

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.

Pan-cancer patterns of somatic copy number alteration

2013 1.2k citations Travis Zack, Steven E. Schumacher et al. Nature Genetics profile →
An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers

2013 832 citations Steven A. Roberts, Michael S. Lawrence et al. Nature Genetics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gordon Saksena United States	8	1.9k	1.4k	793	455	451	15	3.0k
Gavin Ha United States	22	1.7k 0.9×	1.6k 1.2×	951 1.2×	489 1.1×	407 0.9×	54	3.3k
Frank O. Fackelmayer Germany	27	2.9k 1.6×	1.5k 1.1×	772 1.0×	523 1.1×	413 0.9×	38	4.1k
Maryou B. Lambros United Kingdom	31	1.6k 0.9×	1.3k 1.0×	1.4k 1.8×	384 0.8×	669 1.5×	45	3.2k
Rajesh R. Singh United States	29	1.4k 0.8×	1.2k 0.9×	693 0.9×	386 0.8×	397 0.9×	48	2.7k
Mamoru Fukuda Japan	24	1.7k 0.9×	535 0.4×	1.1k 1.5×	566 1.2×	366 0.8×	100	3.1k
David Gentien France	29	1.4k 0.8×	868 0.6×	902 1.1×	302 0.7×	203 0.5×	83	2.7k
Rebecca Leary United States	11	2.0k 1.0×	2.6k 1.9×	1.7k 2.2×	367 0.8×	467 1.0×	18	4.0k
Cliff Meldrum Australia	24	1.0k 0.6×	789 0.6×	1.1k 1.3×	778 1.7×	619 1.4×	57	2.6k
Steven E. Schumacher United States	14	3.0k 1.6×	2.2k 1.6×	1.1k 1.4×	761 1.7×	474 1.1×	16	4.8k
Kerstin Haase Germany	11	1.1k 0.6×	1.1k 0.8×	544 0.7×	436 1.0×	255 0.6×	20	2.0k

Countries citing papers authored by Gordon Saksena

Since Specialization

Citations

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

Fields of papers citing papers by Gordon Saksena

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gordon Saksena

This figure shows the co-authorship network connecting the top 25 collaborators of Gordon Saksena. A scholar is included among the top collaborators of Gordon Saksena 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 Gordon Saksena. Gordon Saksena 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:

15 of 15 papers shown

Gao, Galen F., Coyin Oh, Gordon Saksena, et al.. (2022). Tangent normalization for somatic copy-number inference in cancer genome analysis. Bioinformatics. 38(20). 4677–4686. 4 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

Ellrott, Kyle, Gordon Saksena, Kyle R. Covington, et al.. (2018). Abstract 926: Multi-Center Mutation Calling in Multiple Cancers: The MC3 Project. Cancer Research. 78(13_Supplement). 926–926. 3 indexed citations

Schumacher, Steven E., Byoung Yong Shim, Giovanni Corso, et al.. (2017). Somatic copy number alterations in gastric adenocarcinomas among Asian and Western patients. PLoS ONE. 12(4). e0176045–e0176045. 48 indexed citations

Ajore, Ram, David M. Raiser, Marie McConkey, et al.. (2017). Deletion of ribosomal protein genes is a common vulnerability in human cancer, especially in concert with TP 53 mutations. EMBO Molecular Medicine. 9(4). 498–507. 75 indexed citations

Ajore, Ram, David M. Raiser, Marie McConkey, et al.. (2017). Deletion of ribosomal protein genes is a common vulnerability in human cancer, especially in concert with. DSpace@MIT (Massachusetts Institute of Technology). 1 indexed citations

Ramos, Alex H., Lee Lichtenstein, Manaswi Gupta, et al.. (2015). Oncotator: Cancer Variant Annotation Tool. Human Mutation. 36(4). E2423–E2429. 275 indexed citations

Brooks, Angela N., Peter S. Choi, Luc de Waal, et al.. (2014). A Pan-Cancer Analysis of Transcriptome Changes Associated with Somatic Mutations in U2AF1 Reveals Commonly Altered Splicing Events. PLoS ONE. 9(1). e87361–e87361. 126 indexed citations

Giannakis, Marios, Eran Hodis, Xinmeng Jasmine Mu, et al.. (2014). RNF43 is frequently mutated in colorectal and endometrial cancers. Nature Genetics. 46(12). 1264–1266. 332 indexed citations

10.

Zack, Travis, Steven E. Schumacher, Scott L. Carter, et al.. (2013). Pan-cancer patterns of somatic copy number alteration. Nature Genetics. 45(10). 1134–1140. 1243 indexed citations breakdown →

11.

Roberts, Steven A., Michael S. Lawrence, Leszek J. Klimczak, et al.. (2013). An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers. Nature Genetics. 45(9). 970–976. 832 indexed citations breakdown →

12.

Landau, Dan‐Avi, Kendell Clement, Peter Boyle, et al.. (2013). Increased Local Disorder of DNA Methylation Forms the Basis of High Intra-Leukemic Epigenetic Heterogeneity and Enhances CLL Evolution. Blood. 122(21). 596–596. 3 indexed citations

13.

Kotliar, Dylan, Dan‐Avi Landau, Oren Litvin, et al.. (2013). Reconstructing a Genotype-Phenotype Map In Chronic Lymphocytic Leukemia. Blood. 122(21). 2857–2857. 1 indexed citations

14.

Lin, William M., Julia M. Lewis, Renata B. Filler, et al.. (2011). Characterization of the DNA Copy-Number Genome in the Blood of Cutaneous T-Cell Lymphoma Patients. Journal of Investigative Dermatology. 132(1). 188–197. 25 indexed citations

15.

Saksena, Gordon, Craig H. Mermel, & Gad Getz. (2011). Developing Algorithms to Discover Novel Cancer Genes: A look at the challenges and approaches. IEEE Signal Processing Magazine. 29(1). 89–97. 4 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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