John-William Sidhom

6.1k total citations
17 papers, 777 citations indexed

About

John-William Sidhom is a scholar working on Immunology, Oncology and Molecular Biology. According to data from OpenAlex, John-William Sidhom has authored 17 papers receiving a total of 777 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Immunology, 7 papers in Oncology and 6 papers in Molecular Biology. Recurrent topics in John-William Sidhom's work include Immunotherapy and Immune Responses (6 papers), Cancer Immunotherapy and Biomarkers (6 papers) and CAR-T cell therapy research (5 papers). John-William Sidhom is often cited by papers focused on Immunotherapy and Immune Responses (6 papers), Cancer Immunotherapy and Biomarkers (6 papers) and CAR-T cell therapy research (5 papers). John-William Sidhom collaborates with scholars based in United States, Israel and France. John-William Sidhom's co-authors include Alexander S. Baras, Drew M. Pardoll, Jonathan P. Schneck, H. Benjamin Larman, Catherine Bessell, Alyssa K. Kosmides, Andrew K. Fraser, Erik Wennerberg, Nils-Petter Rudqvist and Sandra Demaria and has published in prestigious journals such as Nature Communications, ACS Nano and Scientific Reports.

In The Last Decade

John-William Sidhom

17 papers receiving 769 citations

Peers

Countries citing papers authored by John-William Sidhom

Since Specialization

Citations

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

Fields of papers citing papers by John-William Sidhom

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John-William Sidhom. 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 John-William Sidhom. The network helps show where John-William Sidhom may publish in the future.

Co-authorship network of co-authors of John-William Sidhom

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

All Works

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17 of 17 papers shown

#	Work	Indexed citations
1	Multiple-instance learning of somatic mutations for the classification of tumour type and the prediction of microsatellite status 2023 ·Nature Biomedical Engineering ·Jordan Anaya, John-William Sidhom, Faisal Mahmood, Alexander S. Baras	6
2	Probabilistic Mixture Models Improve Calibration of Panel-derived Tumor Mutational Burden in the Context of both Tumor-normal and Tumor-only Sequencing 2023 ·Cancer Research Communications ·Jordan Anaya, John-William Sidhom, Craig Cummings, Alexander S. Baras	4
3	Deep learning reveals predictive sequence concepts within immune repertoires to immunotherapy 2022 ·Science Advances ·John-William Sidhom, Giacomo Oliveira, Petra Ross‐Macdonald, Megan Wind‐Rotolo, Catherine J. Wu, Drew M. Pardoll, Alexander S. Baras	32
4	Author Correction: DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires 2021 ·Nature Communications ·John-William Sidhom, H. Benjamin Larman, Drew M. Pardoll, Alexander S. Baras	8
5	Deep learning for diagnosis of acute promyelocytic leukemia via recognition of genomically imprinted morphologic features 2021 ·npj Precision Oncology ·John-William Sidhom, (unknown), (unknown), (unknown), (unknown), (unknown), Amy S. Duffield, Michael B. Streiff, Alison R. Moliterno, Philip Imus, Christian B. Gocke, Lukasz P. Gondek, Amy E. DeZern, Alexander S. Baras, Thomas S. Kickler, Mark J. Levis, Eugene Shenderov	21
6	DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires 2021 ·Nature Communications ·John-William Sidhom, H. Benjamin Larman, Drew M. Pardoll, Alexander S. Baras	147
7	Deep learning identifies antigenic determinants of severe SARS-CoV-2 infection within T-cell repertoires 2021 ·Scientific Reports ·John-William Sidhom, Alexander S. Baras	14
8	Anti-PD-1 elicits regression of undifferentiated pleomorphic sarcomas with UV-mutation signatures 2021 ·Journal for ImmunoTherapy of Cancer ·Laurene S. Cheung, Ling‐Ling Chen, (unknown), Thomas Schaffer, Karim Boudadi, (unknown), John Gross, Holly Kemberling, Luis A. Díaz, Evan J. Lipson, John-William Sidhom, Janis M. Taube, Robert A. Anders, Drew M. Pardoll, Dung T. Le, Christian F. Meyer, Nicolás J. Llosa	9
9	Multiple genetic programs contribute to CD4 T cell memory differentiation and longevity by maintaining T cell quiescence 2020 ·Cellular Immunology ·(unknown), Srona Sengupta, (unknown), (unknown), (unknown), Mithra R. Kumar, Søren Ulrik Sønder, John-William Sidhom, Hao Zhang, Chunfa Jie, Robert F. Siliciano, Scheherazade Sadegh‐Nasseri	8
10	High-dimensional Cytometry (ExCYT) and Mass Spectrometry of Myeloid Infiltrate in Clinically Localized Clear Cell Renal Cell Carcinoma Identifies Novel Potential Myeloid Targets for Immunotherapy 2020 ·Molecular & Cellular Proteomics ·Debebe Theodros, (unknown), John-William Sidhom, Thomas R. Nirschl, David Clark, (unknown), Ada Tam, Richard L. Blosser, Zeyad Schwen, Michael H. Johnson, Phillip M. Pierorazio, Hui Zhang, Sudipto Ganguly, Drew M. Pardoll, Jelani C. Zarif	2
11	A CD40 Agonist and PD-1 Antagonist Antibody Reprogram the Microenvironment of Nonimmunogenic Tumors to Allow T-cell–Mediated Anticancer Activity 2019 ·Cancer Immunology Research ·S. Hayley, (unknown), Evanthia T. Roussos Torres, John-William Sidhom, Tara M. Robinson, Brian J. Christmas, Blake Scott, Kayla Cruz, Skylar Woolman, Valerie Wall, Todd D. Armstrong, Elizabeth M. Jaffee	94
12	ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data 2019 ·Journal of Visualized Experiments ·John-William Sidhom, Debebe Theodros, (unknown), Jelani C. Zarif, Sudipto Ganguly, Drew M. Pardoll, Alexander S. Baras	6
13	ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data 2019 ·Journal of Visualized Experiments ·John-William Sidhom, Debebe Theodros, (unknown), Jelani C. Zarif, Sudipto Ganguly, Drew M. Pardoll, Alexander S. Baras	2
14	The Mutation-Associated Neoantigen Functional Expansion of Specific T Cells (MANAFEST) Assay: A Sensitive Platform for Monitoring Antitumor Immunity 2018 ·Cancer Immunology Research ·Ludmila Danilova, Valsamo Anagnostou, Justina X. Caushi, John-William Sidhom, Haidan Guo, Hok Yee Chan, Prerna Suri, Ada Tam, Jiajia Zhang, Margueritta El Asmar, Kristen A. Marrone, Jarushka Naidoo, Julie R. Brahmer, Patrick M. Forde, Alexander S. Baras, Leslie Cope, Victor E. Velculescu, Drew M. Pardoll, Franck Housseau, Kellie N. Smith	99
15	ImmunoMap: A Bioinformatics Tool for T-cell Repertoire Analysis 2017 ·Cancer Immunology Research ·John-William Sidhom, Catherine Bessell, Jonathan J. Havel, Alyssa K. Kosmides, Timothy A. Chan, Jonathan P. Schneck	31
16	Radiotherapy and CTLA-4 Blockade Shape the TCR Repertoire of Tumor-Infiltrating T Cells 2017 ·Cancer Immunology Research ·Nils-Petter Rudqvist, Karsten A. Pilones, Claire Lhuillier, Erik Wennerberg, John-William Sidhom, Ryan Emerson, Harlan Robins, Jonathan P. Schneck, Silvia C. Formenti, Sandra Demaria	163
17	Dual Targeting Nanoparticle Stimulates the Immune System To Inhibit Tumor Growth 2017 ·ACS Nano ·Alyssa K. Kosmides, John-William Sidhom, Andrew K. Fraser, Catherine Bessell, Jonathan P. Schneck	131

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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