Alex J. Walsh

2.6k total citations
67 papers, 1.8k citations indexed

About

Alex J. Walsh is a scholar working on Molecular Biology, Biophysics and Biomedical Engineering. According to data from OpenAlex, Alex J. Walsh has authored 67 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 29 papers in Biophysics and 18 papers in Biomedical Engineering. Recurrent topics in Alex J. Walsh's work include Advanced Fluorescence Microscopy Techniques (25 papers), 3D Printing in Biomedical Research (10 papers) and Cell Image Analysis Techniques (10 papers). Alex J. Walsh is often cited by papers focused on Advanced Fluorescence Microscopy Techniques (25 papers), 3D Printing in Biomedical Research (10 papers) and Cell Image Analysis Techniques (10 papers). Alex J. Walsh collaborates with scholars based in United States, Mexico and United Kingdom. Alex J. Walsh's co-authors include Melissa C. Skala, Rebecca S. Cook, Carlos L. Arteaga, Melinda E. Sanders, H. Charles Manning, Alec Lafontant, Donna J. Hicks, Nipun B. Merchant, Jason Castellanos and Nagaraj S. Nagathihalli and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Immunology and Gastroenterology.

In The Last Decade

Alex J. Walsh

62 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alex J. Walsh United States 23 716 576 568 504 393 67 1.8k
Nathaniel D. Kirkpatrick United States 19 972 1.4× 273 0.5× 454 0.8× 593 1.2× 622 1.6× 27 2.2k
Ewan J. McGhee United Kingdom 22 969 1.4× 339 0.6× 374 0.7× 597 1.2× 240 0.6× 43 2.4k
Paul T. Winnard United States 23 1.1k 1.5× 211 0.4× 284 0.5× 323 0.6× 378 1.0× 49 2.0k
Pritha Ray India 26 1.8k 2.5× 232 0.4× 596 1.0× 450 0.9× 285 0.7× 78 2.8k
Joe T. Sharick United States 10 575 0.8× 321 0.6× 304 0.5× 186 0.4× 345 0.9× 15 1.3k
Meera Iyer United States 24 1.7k 2.4× 222 0.4× 385 0.7× 401 0.8× 179 0.5× 39 2.9k
Suzanne M. Ponik United States 29 1.1k 1.5× 141 0.2× 710 1.3× 964 1.9× 413 1.1× 55 2.6k
Jason Heth United States 21 874 1.2× 199 0.3× 217 0.4× 360 0.7× 221 0.6× 56 2.1k
Michele Zanoni Italy 21 708 1.0× 100 0.2× 693 1.2× 758 1.5× 276 0.7× 43 2.0k
Maria Vinci Italy 17 894 1.2× 114 0.2× 603 1.1× 604 1.2× 295 0.8× 46 2.1k

Countries citing papers authored by Alex J. Walsh

Since Specialization
Citations

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

Fields of papers citing papers by Alex J. Walsh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alex J. Walsh. 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 Alex J. Walsh. The network helps show where Alex J. Walsh may publish in the future.

Co-authorship network of co-authors of Alex J. Walsh

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

All Works

20 of 20 papers shown
1.
2.
Samimi, Kayvan, Isabel Jones, Matthew H. Forsberg, et al.. (2025). Autofluorescence lifetime imaging classifies human B and NK cell activation state. Frontiers in Bioengineering and Biotechnology. 13. 1557021–1557021.
3.
Walsh, Alex J., et al.. (2025). Fluorescence lifetime imaging to investigate propofol-induced metabolic alterations in MDA-MB-231 cells. Biomedical Optics Express. 16(11). 4470–4470.
4.
Lei, Yuanjiu, et al.. (2024). 3D convolutional neural networks predict cellular metabolic pathway use from fluorescence lifetime decay data. APL Bioengineering. 8(1). 16112–16112. 1 indexed citations
5.
Walsh, Alex J., et al.. (2024). Evaluation of Cellpose segmentation with sequential thresholding for instance segmentation of cytoplasms within autofluorescence images. Computers in Biology and Medicine. 179. 108846–108846.
6.
Walsh, Alex J., et al.. (2024). Autofluorescence is a biomarker of neural stem cell activation state. Cell stem cell. 31(4). 570–581.e7. 5 indexed citations
7.
Walsh, Alex J., et al.. (2024). Fast autofluorescence imaging to evaluate dynamic changes in cell metabolism. Journal of Biomedical Optics. 29(12). 126501–126501. 1 indexed citations
8.
Sharma, Dhavan, et al.. (2023). Comparison of phasor analysis and biexponential decay curve fitting of autofluorescence lifetime imaging data for machine learning prediction of cellular phenotypes. SHILAP Revista de lepidopterología. 3. 1210157–1210157. 5 indexed citations
9.
Walsh, Alex J., et al.. (2023). Comparison of clinical outcomes between total hip replacement and total knee replacement. World Journal of Orthopedics. 14(12). 853–867. 2 indexed citations
10.
Walsh, Alex J., et al.. (2023). POSEA: A novel algorithm to evaluate the performance of multi-object instance image segmentation. PLoS ONE. 18(3). e0283692–e0283692. 2 indexed citations
11.
Kaunas, Roland, et al.. (2023). Volumetric imaging of human mesenchymal stem cells (hMSCs) for non-destructive quantification of 3D cell culture growth. PLoS ONE. 18(3). e0282298–e0282298. 7 indexed citations
12.
Walsh, Alex J., Rebecca S. Cook, Melinda E. Sanders, Carlos L. Arteaga, & Melissa C. Skala. (2016). Drug response in organoids generated from frozen primary tumor tissues. Scientific Reports. 6(1). 18889–18889. 84 indexed citations
13.
Walsh, Alex J., et al.. (2015). Collagen density and alignment in responsive and resistant trastuzumab-treated breast cancer xenografts. Journal of Biomedical Optics. 20(2). 26004–26004. 31 indexed citations
14.
Walsh, Alex J., Rebecca S. Cook, Melinda E. Sanders, et al.. (2014). Quantitative Optical Imaging of Primary Tumor Organoid Metabolism Predicts Drug Response in Breast Cancer. Cancer Research. 74(18). 5184–5194. 229 indexed citations
15.
Walsh, Alex J., et al.. (2014). In vivo hyperspectral imaging of microvessel response to trastuzumab treatment in breast cancer xenografts. Biomedical Optics Express. 5(7). 2247–2247. 36 indexed citations
16.
Shah, Amy T., Michelle Demory Beckler, Alex J. Walsh, et al.. (2014). Optical Metabolic Imaging of Treatment Response in Human Head and Neck Squamous Cell Carcinoma. PLoS ONE. 9(3). e90746–e90746. 63 indexed citations
17.
Venkateswaran, Amudhan, Konjeti R. Sekhar, Daniel S. Levic, et al.. (2013). The NADH Oxidase ENOX1, a Critical Mediator of Endothelial Cell Radiosensitization, Is Crucial for Vascular Development. Cancer Research. 74(1). 38–43. 16 indexed citations
18.
Walsh, Alex J., Rebecca S. Cook, H. Charles Manning, et al.. (2013). Optical Metabolic Imaging Identifies Glycolytic Levels, Subtypes, and Early-Treatment Response in Breast Cancer. Cancer Research. 73(20). 6164–6174. 247 indexed citations
19.
Bi, Xiaohong, Alex J. Walsh, Anita Mahadevan‐Jansen, & Alan J. Herline. (2011). Development of Spectral Markers for the Discrimination of Ulcerative Colitis and Crohn's Disease Using Raman Spectroscopy. Diseases of the Colon & Rectum. 54(1). 48–53. 37 indexed citations
20.
Goossens, Willy, et al.. (1996). First basic performance evaluation of the Cell-Dyn 4000. International Journal of Laboratory Hematology. 2. 151–156. 5 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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