Katharine Yu

508 total citations
11 papers, 295 citations indexed

About

Katharine Yu is a scholar working on Molecular Biology, Oncology and Neurology. According to data from OpenAlex, Katharine Yu has authored 11 papers receiving a total of 295 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Oncology and 2 papers in Neurology. Recurrent topics in Katharine Yu's work include Pancreatic and Hepatic Oncology Research (2 papers), Single-cell and spatial transcriptomics (2 papers) and Mitochondrial Function and Pathology (2 papers). Katharine Yu is often cited by papers focused on Pancreatic and Hepatic Oncology Research (2 papers), Single-cell and spatial transcriptomics (2 papers) and Mitochondrial Function and Pathology (2 papers). Katharine Yu collaborates with scholars based in United States, Spain and Canada. Katharine Yu's co-authors include Marina Sirota, Laura van ‘t Veer, Denise M. Wolf, Christina Yau, Theodore C. Goldstein, Atul J. Butte, Bin Chen, Dvir Aran, Jean L. Nakamura and Alice Nakamura and has published in prestigious journals such as Nature Communications, Scientific Reports and Clinical Cancer Research.

In The Last Decade

Katharine Yu

11 papers receiving 292 citations

Peers

Katharine Yu

MB

CR

ONCOL

IMMUN

HEMAT

Luigi Alfano Italy

Moamen Bydoun Canada

Marty J. Heslin United States

Tomoko Ueda Japan

Nicole Kreuzberg Germany

Jenny Kreahling United States

Meryem Koese Australia

Yi Su China

Laia Cubells Spain

Luana D’Artista Italy

Luigi Alfano Italy

Katharine Yu

271 ×1.5

MB

45 ×0.6

CR

95 ×1.3

ONCOL

36 ×1.1

IMMUN

43 ×1.5

HEMAT

Citations per year, relative to Katharine Yu Katharine Yu (= 1×) peers Luigi Alfano

Countries citing papers authored by Katharine Yu

Since Specialization

Citations

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

Fields of papers citing papers by Katharine Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Katharine Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Katharine Yu. A scholar is included among the top collaborators of Katharine Yu 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 Katharine Yu. Katharine Yu 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.

Yu, Katharine, Amrita Basu, Christina Yau, et al.. (2023). Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes. Frontiers in Oncology. 13. 1192208–1192208. 2 indexed citations

2.

Yu, Katharine, et al.. (2022). A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires. Frontiers in Immunology. 12. 790119–790119. 14 indexed citations

3.

Pineda, Sílvia, et al.. (2021). Tumor-Infiltrating B- and T-Cell Repertoire in Pancreatic Cancer Associated With Host and Tumor Features. Frontiers in Immunology. 12. 730746–730746. 10 indexed citations

4.

Le, Brian L., Gaia Andreoletti, Tomiko Oskotsky, et al.. (2021). Transcriptomics-based drug repositioning pipeline identifies therapeutic candidates for COVID-19. Scientific Reports. 11(1). 12310–12310. 25 indexed citations

5.

Yu, Katharine, Ian Ferguson, Matthew A. Nix, et al.. (2020). Evaluating the efficacy of multiple myeloma cell lines as models for patient tumors via transcriptomic correlation analysis. Leukemia. 34(10). 2754–2765. 33 indexed citations

6.

Yu, Katharine, Bin Chen, Dvir Aran, et al.. (2019). Comprehensive transcriptomic analysis of cell lines as models of primary tumors across 22 tumor types. Nature Communications. 10(1). 3574–3574. 101 indexed citations

7.

Yu, Katharine, et al.. (2019). Evaluating the efficacy of multiple myeloma cell lines as models for patient tumors via transcriptomic correlation analysis. Clinical Lymphoma Myeloma & Leukemia. 19(10). e76–e76. 1 indexed citations

8.

Mendelsohn, Bryce A., Neal K. Bennett, Katharine Yu, et al.. (2018). A high-throughput screen of real-time ATP levels in individual cells reveals mechanisms of energy failure. PLoS Biology. 16(8). e2004624–e2004624. 43 indexed citations

9.

Pathak, Divya, Amandine Berthet, Jacob Bendor, et al.. (2017). Loss of α-Synuclein Does Not Affect Mitochondrial Bioenergetics in Rodent Neurons. eNeuro. 4(2). ENEURO.0216–16.2017. 14 indexed citations

10.

Sherborne, Amy L., Vincent Lavergne, Katharine Yu, et al.. (2016). Somatic and Germline TP53 Alterations in Second Malignant Neoplasms from Pediatric Cancer Survivors. Clinical Cancer Research. 23(7). 1852–1861. 24 indexed citations

11.

Sherborne, Amy L., et al.. (2015). Mutational Analysis of Ionizing Radiation Induced Neoplasms. Cell Reports. 12(11). 1915–1926. 28 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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