Bryan E. Welm

5.7k total citations · 1 hit paper
43 papers, 3.4k citations indexed

About

Bryan E. Welm is a scholar working on Oncology, Molecular Biology and Cancer Research. According to data from OpenAlex, Bryan E. Welm has authored 43 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Oncology, 19 papers in Molecular Biology and 12 papers in Cancer Research. Recurrent topics in Bryan E. Welm's work include Cancer Cells and Metastasis (22 papers), Cancer Genomics and Diagnostics (6 papers) and Fibroblast Growth Factor Research (4 papers). Bryan E. Welm is often cited by papers focused on Cancer Cells and Metastasis (22 papers), Cancer Genomics and Diagnostics (6 papers) and Fibroblast Growth Factor Research (4 papers). Bryan E. Welm collaborates with scholars based in United States, Spain and Norway. Bryan E. Welm's co-authors include Jeffrey M. Rosen, Alana L. Welm, Zena Werb, Margaret A. Goodell, Keith M. Gligorich, Matthew S. Sigman, Guoying Wang, Tejas P. Pathak, Timothy A. Graubert and Yoko S. DeRose and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Bryan E. Welm

43 papers receiving 3.3k 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.

Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes

2011 699 citations Philip S. Bernard, Saundra S. Buys et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bryan E. Welm United States	23	1.7k	1.6k	691	354	324	43	3.4k
Gillian Farnie United Kingdom	25	1.9k 1.1×	1.8k 1.1×	668 1.0×	196 0.6×	131 0.4×	41	3.1k
Laura K. Shawver United States	26	3.4k 2.0×	2.0k 1.2×	1.2k 1.7×	239 0.7×	330 1.0×	47	5.1k
Oleg Schmidt‐Kittler United States	18	2.1k 1.2×	1.5k 0.9×	1.2k 1.7×	322 0.9×	97 0.3×	24	3.5k
Jonathan A. Pachter United States	32	2.4k 1.4×	1.7k 1.0×	664 1.0×	195 0.6×	115 0.4×	137	4.4k
Adina Vultur United States	22	2.1k 1.2×	1.3k 0.8×	556 0.8×	90 0.3×	187 0.6×	48	3.0k
D J Chaplin United Kingdom	19	1.4k 0.8×	740 0.4×	1.0k 1.5×	138 0.4×	290 0.9×	33	3.0k
Dominic Fan United States	37	2.0k 1.2×	2.0k 1.2×	755 1.1×	152 0.4×	114 0.4×	72	4.1k
Nor Eddine Sounni Belgium	31	1.7k 1.0×	1.3k 0.8×	1.6k 2.3×	115 0.3×	168 0.5×	51	3.5k
Hans Skovgaard Poulsen Denmark	44	2.5k 1.5×	2.0k 1.2×	1.2k 1.8×	486 1.4×	98 0.3×	188	5.9k
Lori Hazlehurst United States	35	2.5k 1.5×	1.9k 1.2×	557 0.8×	126 0.4×	129 0.4×	91	4.6k

Countries citing papers authored by Bryan E. Welm

Since Specialization

Citations

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

Fields of papers citing papers by Bryan E. Welm

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bryan E. Welm. 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 Bryan E. Welm. The network helps show where Bryan E. Welm may publish in the future.

Co-authorship network of co-authors of Bryan E. Welm

This figure shows the co-authorship network connecting the top 25 collaborators of Bryan E. Welm. A scholar is included among the top collaborators of Bryan E. Welm 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 Bryan E. Welm. Bryan E. Welm 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

Vaklavas, Christos, Cindy Matsen, Zhengtao Chu, et al.. (2024). TOWARDS Study: Patient-Derived Xenograft Engraftment Predicts Poor Survival in Patients With Newly Diagnosed Triple-Negative Breast Cancer. JCO Precision Oncology. 8(8). e2300724–e2300724. 3 indexed citations

Butterfield, Andrew, Sandra D. Scherer, Emilio Cortes-Sanchez, et al.. (2022). Multiparametric quantitative phase imaging for real-time, single cell, drug screening in breast cancer. Communications Biology. 5(1). 794–794. 22 indexed citations

Dobrolecki, Lacey E., Matthew H. Bailey, Alana L. Welm, et al.. (2022). Immunologically “cold” triple negative breast cancers engraft at a higher rate in patient derived xenografts. npj Breast Cancer. 8(1). 104–104. 9 indexed citations

Feusier, Julie, Sasi Arunachalam, Tsewang Tashi, et al.. (2021). Large-scale Identification of Clonal Hematopoiesis and Mutations Recurrent in Blood Cancers. Blood Cancer Discovery. 2(3). 226–237. 23 indexed citations

Truong, Thu H., Nuri A. Temiz, Ying Wang, et al.. (2021). PELP1/SRC-3-dependent regulation of metabolic PFKFB kinases drives therapy resistant ER+ breast cancer. Oncogene. 40(25). 4384–4397. 26 indexed citations

Graham, James M., Katrin P. Guillen, Patsy G. Oliver, et al.. (2020). STAT3 and GR Cooperate to Drive Gene Expression and Growth of Basal-Like Triple-Negative Breast Cancer. Cancer Research. 80(20). 4355–4370. 22 indexed citations

Rodriguez, Adriana C., Jeffery M. Vahrenkamp, Kristofer C. Berrett, et al.. (2020). ETV4 Is Necessary for Estrogen Signaling and Growth in Endometrial Cancer Cells. Cancer Research. 80(6). 1234–1245. 43 indexed citations

Knight, Stacey, Carol Sweeney, Rachel E. Factor, et al.. (2018). Reparameterization of PAM50 Expression Identifies Novel Breast Tumor Dimensions and Leads to Discovery of a Genome-Wide Significant Breast Cancer Locus at 12q15. Cancer Epidemiology Biomarkers & Prevention. 27(6). 644–652. 7 indexed citations

Vahrenkamp, Jeffery M., Adriana C. Rodriguez, Aliyah Almomen, et al.. (2018). Clinical and Genomic Crosstalk between Glucocorticoid Receptor and Estrogen Receptor α In Endometrial Cancer. Cell Reports. 22(11). 2995–3005. 57 indexed citations

10.

Leonard, Christopher J., et al.. (2014). Dioxin Exposure Blocks Lactation through a Direct Effect on Mammary Epithelial Cells Mediated by the Aryl Hydrocarbon Receptor Repressor. Toxicological Sciences. 143(1). 36–45. 13 indexed citations

11.

Vaden, Rachel M., Keith M. Gligorich, Ranjan Jana, Matthew S. Sigman, & Bryan E. Welm. (2014). The small molecule C-6 is selectively cytotoxic against breast cancer cells and its biological action is characterized by mitochondrial defects and endoplasmic reticulum stress. Breast Cancer Research. 16(6). 11 indexed citations

12.

Pathak, Tejas P., et al.. (2012). Synthesis and preliminary biological study of bisindolylmethanes accessed by an acid-catalyzed hydroarylation of vinyl indoles. Tetrahedron. 68(26). 5203–5208. 73 indexed citations

13.

Kieffer, Collin, Dawne N. Shelton, Christopher J. Leonard, et al.. (2012). Chemical Genetic Screen Reveals a Role for Desmosomal Adhesion in Mammary Branching Morphogenesis. Journal of Biological Chemistry. 288(4). 2261–2270. 19 indexed citations

14.

Pond, Adam C., Jason I. Herschkowitz, Kathryn L. Schwertfeger, et al.. (2010). Fibroblast Growth Factor Receptor Signaling Dramatically Accelerates Tumorigenesis and Enhances Oncoprotein Translation in the Mouse Mammary Tumor Virus–Wnt-1 Mouse Model of Breast Cancer. Cancer Research. 70(12). 4868–4879. 40 indexed citations

15.

Shelton, Dawne N., Rodrigo Fernández‐González, Irineu Illa-Bochaca, et al.. (2010). Use of Stem Cell Markers in Dissociated Mammary Populations. Methods in molecular biology. 621. 49–55. 6 indexed citations

16.

Freeman, Kevin W., Rama Gangula, Bryan E. Welm, et al.. (2003). Conditional activation of fibroblast growth factor receptor (FGFR) 1, but not FGFR2, in prostate cancer cells leads to increased osteopontin induction, extracellular signal-regulated kinase activation, and in vivo proliferation.. PubMed. 63(19). 6237–43. 68 indexed citations

17.

Li, Yi, Bryan E. Welm, Katrina Podsypanina, et al.. (2003). Evidence that transgenes encoding components of the Wnt signaling pathway preferentially induce mammary cancers from progenitor cells. Proceedings of the National Academy of Sciences. 100(26). 15853–15858. 428 indexed citations

18.

Seagroves, Tiffany N., Darryl L. Hadsell, Carol A. Palmer, et al.. (2003). HIF1α is a critical regulator of secretory differentiation and activation, but not vascular expansion, in the mouse mammary gland. Development. 130(8). 1713–1724. 68 indexed citations

19.

Pownall, Mary Elizabeth, Bryan E. Welm, Kevin W. Freeman, et al.. (2003). An inducible system for the study of FGF signalling in early amphibian development. Developmental Biology. 256(1). 90–100. 34 indexed citations

20.

Welm, Bryan E., et al.. (2002). Sca-1pos Cells in the Mouse Mammary Gland Represent an Enriched Progenitor Cell Population. Developmental Biology. 245(1). 42–56. 412 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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