Joshua E. Lewis

767 total citations
24 papers, 485 citations indexed

About

Joshua E. Lewis is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Hematology. According to data from OpenAlex, Joshua E. Lewis has authored 24 papers receiving a total of 485 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Hematology. Recurrent topics in Joshua E. Lewis's work include Digital Imaging for Blood Diseases (6 papers), Cancer, Hypoxia, and Metabolism (4 papers) and Hematological disorders and diagnostics (4 papers). Joshua E. Lewis is often cited by papers focused on Digital Imaging for Blood Diseases (6 papers), Cancer, Hypoxia, and Metabolism (4 papers) and Hematological disorders and diagnostics (4 papers). Joshua E. Lewis collaborates with scholars based in United States, Philippines and China. Joshua E. Lewis's co-authors include Melissa L. Kemp, Cristina M. Furdui, Lee Cooper, David A. Boothman, David A. Gutman, Congzheng Song, Sameer H. Halani, Mohamed Amgad, Fatemeh Amrollahi and Daniel J. Brat and has published in prestigious journals such as Nature Communications, Blood and Cancer Research.

In The Last Decade

Joshua E. Lewis

21 papers receiving 481 citations

Peers

Countries citing papers authored by Joshua E. Lewis

Since Specialization

Citations

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

Fields of papers citing papers by Joshua E. Lewis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joshua E. Lewis

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

#	Work	Indexed citations
1	Advances in Bone Marrow Evaluation 2024 ·Clinics in Laboratory Medicine ·Joshua E. Lewis, Olga Pozdnyakova	2
2	Deep Learning-Based Integration of Morphology and Immunophenotype Predicts Molecular Genetic Subtypes of Multiple Myeloma 2024 ·American Journal of Clinical Pathology ·Joshua E. Lewis, Michael Horwath, (unknown), (unknown), (unknown), (unknown), (unknown), Geoffrey Smith, D. Gutman, Vikas A. Gupta	1
3	Digital assessment of peripheral blood and bone marrow aspirate smears 2023 ·International Journal of Laboratory Hematology ·Joshua E. Lewis, Olga Pozdnyakova	7
4	Automated Deep Learning-Based Diagnosis and Molecular Characterization of Acute Myeloid Leukemia Using Flow Cytometry 2023 ·Modern Pathology ·Joshua E. Lewis, Lee Cooper, David L. Jaye, Olga Pozdnyakova	14
5	The Immunophenotypic Profile of Healthy Human Bone Marrow 2023 ·Clinics in Laboratory Medicine ·Joshua E. Lewis, Christopher A. Hergott	2
6	One-year retrospective analysis of anti-FXa apixaban and rivaroxaban levels demonstrates utility for management decisions in various urgent and nonurgent clinical situations 2023 ·American Journal of Clinical Pathology ·Fabienne Lucas, Joshua E. Lewis, (unknown), Katelyn W. Sylvester, (unknown), (unknown), (unknown), (unknown), Jean M. Connors, Elisabeth M. Battinelli	1
7	Automated Machine Learning-Based Diagnosis and Molecular Characterization of Acute Leukemias using Flow Cytometry Data 2023 ·American Journal of Clinical Pathology ·Joshua E. Lewis, Lee Cooper, David L. Jaye, Olga Pozdnyakova	0
8	An Automated Pipeline for Differential Cell Counts on Whole-Slide Bone Marrow Aspirate Smears 2023 ·Modern Pathology ·Joshua E. Lewis, (unknown), (unknown), (unknown), (unknown), (unknown), Michael Horwath, (unknown), Geoffrey Smith, David A. Gutman, (unknown), Lee Cooper, David L. Jaye	15
9	Machine Learning Models Predict Molecular Genetic Subtypes of Multiple Myeloma from Whole-Slide Bone Marrow Aspirate Smears 2023 ·Blood ·Joshua E. Lewis, (unknown), (unknown), Michael Horwath, (unknown), (unknown), (unknown), Geoffrey Smith, David A. Gutman, Vikas A. Gupta, (unknown), Lee Cooper, David L. Jaye	2
10	Lessons learned: A look back at the performance of nine COVID-19 serologic assays and their proposed utility 2023 ·Clinical Biochemistry ·Nicole V. Tolan, (unknown), (unknown), Joshua E. Lewis, Daimon P. Simmons, Peter H. Schur, Manfred Brigl, Milenko J. Tanasijevic, Michaël Desjardins, Amy C Sherman, Lindsey R. Baden, (unknown), Stacy E.F. Melanson	0
11	Redox integration of signaling and metabolism in a head and neck cancer model of radiation resistance using COSMRO 2023 ·Frontiers in Oncology ·Zhiwei Ji, (unknown), Nelmi O. Devarie‐Baez, Joshua E. Lewis, Hanzhi Wu, Kirtikar Shukla, (unknown), Victor Vitvitsky, Chia‐Chi Chuang, Mercedes Porosnicu, Melissa L. Kemp, Ruma Banerjee, John S. Parks, Allen W. Tsang, Xiaobo Zhou, Cristina M. Furdui	5
12	Personalized Genome-Scale Metabolic Models Identify Targets of Redox Metabolism in Radiation-Resistant Tumors 2021 ·Cell Systems ·Joshua E. Lewis, (unknown), David A. Boothman, Cristina M. Furdui, Melissa L. Kemp	36
13	Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance 2021 ·Nature Communications ·Joshua E. Lewis, Melissa L. Kemp	123
14	An Integrative Gene Expression and Mathematical Flux Balance Analysis Identifies Targetable Redox Vulnerabilities in Melanoma Cells 2020 ·Cancer Research ·B. Bishal Paudel, Joshua E. Lewis, Keisha N. Hardeman, (unknown), Charles T. Robbins, (unknown), Simona G. Codreanu, Stacy D. Sherrod, John A. McLean, Melissa L. Kemp, Vito Quaranta	17
15	MTHFD2 Blockade Enhances the Efficacy of β-Lapachone Chemotherapy With Ionizing Radiation in Head and Neck Squamous Cell Cancer 2020 ·Frontiers in Oncology ·Kirtikar Shukla, (unknown), Joshua E. Lewis, Allen W. Tsang, David A. Boothman, Melissa L. Kemp, Cristina M. Furdui	10
16	Targeting NAD+ Metabolism to Enhance Radiation Therapy Responses 2019 ·PMC ·Joshua E. Lewis, (unknown), Reetta Holmila, Baran D. Sumer, Noelle S. Williams, Cristina M. Furdui, Melissa L. Kemp, David A. Boothman	2
17	RPGRIP1L is required for stabilizing epidermal keratinocyte adhesion through regulating desmoglein endocytosis 2019 ·PLoS Genetics ·Yeon Ja Choi, Christine Laclef, (unknown), (unknown), Joshua E. Lewis, Xuming Mao, Li Li, (unknown), Ken‐Ichi Takemaru, Chuan Qin, Sylvie Schneider‐Maunoury, Kenneth R. Shroyer, Yusuf A. Hannun, Peter J. Koch, Richard A. Clark, Aimee Payne, Andrew P. Kowalczyk, Jiang Chen	8
18	Targeting NAD+ Metabolism to Enhance Radiation Therapy Responses 2018 ·Seminars in Radiation Oncology ·Joshua E. Lewis, (unknown), Reetta Holmila, Baran D. Sumer, Noelle S. Williams, Cristina M. Furdui, Melissa L. Kemp, David A. Boothman	23
19	Genome-Scale Modeling of NADPH-Driven β-Lapachone Sensitization in Head and Neck Squamous Cell Carcinoma 2017 ·Antioxidants and Redox Signaling ·Joshua E. Lewis, (unknown), Jade Mims, Xiaofei Chen, Cristina M. Furdui, David A. Boothman, Melissa L. Kemp	23
20	Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models 2017 ·Scientific Reports ·Safoora Yousefi, Fatemeh Amrollahi, Mohamed Amgad, Chengliang Dong, Joshua E. Lewis, Congzheng Song, David A. Gutman, Sameer H. Halani, (unknown), Daniel J. Brat, Lee Cooper	143

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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