Keith Baggerly

30.5k total citations · 3 hit papers
157 papers, 12.6k citations indexed

About

Keith Baggerly is a scholar working on Molecular Biology, Cancer Research and Spectroscopy. According to data from OpenAlex, Keith Baggerly has authored 157 papers receiving a total of 12.6k indexed citations (citations by other indexed papers that have themselves been cited), including 101 papers in Molecular Biology, 36 papers in Cancer Research and 26 papers in Spectroscopy. Recurrent topics in Keith Baggerly's work include Gene expression and cancer classification (28 papers), Advanced Proteomics Techniques and Applications (23 papers) and Mass Spectrometry Techniques and Applications (15 papers). Keith Baggerly is often cited by papers focused on Gene expression and cancer classification (28 papers), Advanced Proteomics Techniques and Applications (23 papers) and Mass Spectrometry Techniques and Applications (15 papers). Keith Baggerly collaborates with scholars based in United States, Canada and China. Keith Baggerly's co-authors include Kevin R. Coombes, Jeffrey S. Morris, Donald Geman, Héctor Corrada Bravo, Jeffrey T. Leek, W. Evan Johnson, Ben Langmead, Rafael A. Irizarry, Robert B. Scharpf and Ralf Krahe and has published in prestigious journals such as JAMA, Nature Genetics and Journal of Clinical Oncology.

In The Last Decade

Keith Baggerly

157 papers receiving 12.2k 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.

Tackling the widespread and critical impact of batch effects in high-throughput data

2010 1.4k citations Keith Baggerly et al. profile →
Identification of Distinct Basal and Luminal Subtypes of Muscle-Invasive Bladder Cancer with Different Sensitivities to Frontline Chemotherapy

2014 1.2k citations Tadeusz Majewski, Keith Baggerly et al. profile →
Differential Response to Neoadjuvant Chemotherapy Among 7 Triple-Negative Breast Cancer Molecular Subtypes

2013 525 citations Hiroko Masuda, Keith Baggerly et al. Clinical Cancer Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Keith Baggerly United States	56	6.8k	2.1k	2.1k	1.9k	1.6k	157	12.6k
David A. Fishman United States	53	6.3k 0.9×	2.2k 1.1×	2.0k 1.0×	785 0.4×	2.2k 1.4×	157	11.4k
Peter J. Wild Germany	65	6.8k 1.0×	2.7k 1.3×	2.3k 1.1×	1.5k 0.8×	456 0.3×	394	14.4k
Emanuel F. Petricoin United States	66	11.4k 1.7×	4.6k 2.2×	3.1k 1.5×	1.3k 0.7×	5.4k 3.5×	259	18.3k
Jeremy M. G. Taylor United States	72	5.1k 0.8×	4.0k 1.9×	2.5k 1.2×	2.6k 1.3×	436 0.3×	402	22.0k
Igor Jurišica Canada	64	10.1k 1.5×	2.3k 1.1×	4.5k 2.2×	820 0.4×	452 0.3×	286	15.9k
Jeffrey S. Morris United States	51	3.1k 0.5×	1.7k 0.8×	1.0k 0.5×	1.6k 0.8×	1.1k 0.7×	196	8.9k
Kevin R. Coombes United States	53	6.8k 1.0×	1.7k 0.8×	2.1k 1.0×	377 0.2×	1.7k 1.1×	241	10.2k
David J. Harrison United Kingdom	65	9.4k 1.4×	4.4k 2.1×	2.2k 1.1×	1.6k 0.8×	279 0.2×	482	17.6k
Ming Chen China	56	4.9k 0.7×	2.4k 1.1×	2.1k 1.0×	1.3k 0.7×	252 0.2×	700	13.9k
Gary D. Bader Canada	69	22.9k 3.4×	2.5k 1.2×	4.4k 2.1×	937 0.5×	1.1k 0.7×	211	31.7k

Countries citing papers authored by Keith Baggerly

Since Specialization

Citations

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

Fields of papers citing papers by Keith Baggerly

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keith Baggerly

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

All Works

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20 of 20 papers shown

McGuire, Michael H., Santosh K. Dasari, Hui Yao, et al.. (2021). Gene Body Methylation of the Lymphocyte-Specific Gene CARD11 Results in Its Overexpression and Regulates Cancer mTOR Signaling. Molecular Cancer Research. 19(11). 1917–1928. 6 indexed citations

Wen, Yunfei, Ying Wang, Anca Chelariu-Raicu, et al.. (2020). Blockade of the Short Form of Prolactin Receptor Induces FOXO3a/EIF-4EBP1–Mediated Cell Death in Uterine Cancer. Molecular Cancer Therapeutics. 19(9). 1943–1954. 4 indexed citations

Villar‐Prados, Alejandro, Sherry Y. Wu, Karem A. Court, et al.. (2018). Predicting Novel Therapies and Targets: Regulation of Notch3 by the Bromodomain Protein BRD4. Molecular Cancer Therapeutics. 18(2). 421–436. 10 indexed citations

Boulbés, Delphine R., Tracy J. Costello, Keith Baggerly, et al.. (2018). A Survey on Data Reproducibility and the Effect of Publication Process on the Ethical Reporting of Laboratory Research. Clinical Cancer Research. 24(14). 3447–3455. 22 indexed citations

Yang, Wei-Lei, Aleksandra Gentry‐Maharaj, Andy Ryan, et al.. (2017). Elevation of TP53 Autoantibody Before CA125 in Preclinical Invasive Epithelial Ovarian Cancer. Clinical Cancer Research. 23(19). 5912–5922. 44 indexed citations

Jiao, Jingjing, Weibo Niu, Ying Wang, et al.. (2017). Prevalence of Aflatoxin-Associated TP53R249S Mutation in Hepatocellular Carcinoma in Hispanics in South Texas. Cancer Prevention Research. 11(2). 103–112. 19 indexed citations

Herbrich, Shelley M., Peter P. Ruvolo, Vivian Ruvolo, et al.. (2017). Robust Bioinformatics Approach for Identifying Novel AML LSC Targets: Putative Role of Galectin-1 in the Immune-Microenvironment. Blood. 130. 3962–3962. 1 indexed citations

Aparicio, Ana M., Li Shen, Elsa Li Ning Tapia, et al.. (2015). Combined Tumor Suppressor Defects Characterize Clinically Defined Aggressive Variant Prostate Cancers. Clinical Cancer Research. 22(6). 1520–1530. 192 indexed citations

Li, Zhang, Veerabhadran Baladandayuthapani, Hongxiao Zhu, et al.. (2015). Functional CAR Models for Large Spatially Correlated Functional Datasets. Journal of the American Statistical Association. 111(514). 772–786. 38 indexed citations

10.

Zhang, Shu, Zhen Lü, Anna K. Unruh, et al.. (2014). Clinically Relevant microRNAs in Ovarian Cancer. Molecular Cancer Research. 13(3). 393–401. 70 indexed citations

11.

Tucker, Susan L., Kshipra M. Gharpure, Shelley M. Herbrich, et al.. (2014). Molecular Biomarkers of Residual Disease after Surgical Debulking of High-Grade Serous Ovarian Cancer. Clinical Cancer Research. 20(12). 3280–3288. 68 indexed citations

12.

Konopleva, Marina, Roland B. Walter, Stefan Faderl, et al.. (2014). Preclinical and Early Clinical Evaluation of the Oral AKT Inhibitor, MK-2206, for the Treatment of Acute Myelogenous Leukemia. Clinical Cancer Research. 20(8). 2226–2235. 70 indexed citations

13.

Masuda, Hiroko, Keith Baggerly, Ying Wang, et al.. (2013). Differential Response to Neoadjuvant Chemotherapy Among 7 Triple-Negative Breast Cancer Molecular Subtypes. Clinical Cancer Research. 19(19). 5533–5540. 525 indexed citations breakdown →

14.

Xie, Xuemei, et al.. (2013). Bisphosphorylated PEA-15 Sensitizes Ovarian Cancer Cells to Paclitaxel by Impairing the Microtubule-Destabilizing Effect of SCLIP. Molecular Cancer Therapeutics. 12(6). 1099–1111. 14 indexed citations

15.

Lee, Jae K., Charles Coutant, Young Chul Kim, et al.. (2010). Prospective Comparison of Clinical and Genomic Multivariate Predictors of Response to Neoadjuvant Chemotherapy in Breast Cancer. Clinical Cancer Research. 16(2). 711–718. 60 indexed citations

16.

Richards, Kristy L., Baili Zhang, Menghong Sun, et al.. (2010). Methylation of the candidate biomarker TCF21 is very frequent across a spectrum of early‐stage nonsmall cell lung cancers. Cancer. 117(3). 606–617. 55 indexed citations

17.

Colella, Stefano, Kristy L. Richards, Linda L. Bachinski, et al.. (2008). Molecular signatures of metastasis in head and neck cancer. Head & Neck. 30(10). 1273–1283. 24 indexed citations

18.

Hu, Yuhui, Hongxia Sun, Jeffrey Drake, et al.. (2004). From Mice to Humans. Cancer Research. 64(21). 7748–7755. 74 indexed citations

19.

Pusztai, Lajos, Betsy Gregory, Keith Baggerly, et al.. (2004). Pharmacoproteomic analysis of prechemotherapy and postchemotherapy plasma samples from patients receiving neoadjuvant or adjuvant chemotherapy for breast carcinoma. Cancer. 100(9). 1814–1822. 92 indexed citations

20.

Baggerly, Keith, Jeffrey S. Morris, Jing Wang, et al.. (2003). A comprehensive approach to the analysis of MALDI-TOF proteomics spectra from serum samples.. PROTEOMICS. 3. 10 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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