William J. Faison

498 total citations
9 papers, 244 citations indexed

About

William J. Faison is a scholar working on Radiology, Nuclear Medicine and Imaging, Immunology and Molecular Biology. According to data from OpenAlex, William J. Faison has authored 9 papers receiving a total of 244 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Immunology and 3 papers in Molecular Biology. Recurrent topics in William J. Faison's work include T-cell and B-cell Immunology (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers) and Bacteriophages and microbial interactions (2 papers). William J. Faison is often cited by papers focused on T-cell and B-cell Immunology (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers) and Bacteriophages and microbial interactions (2 papers). William J. Faison collaborates with scholars based in United States, Luxembourg and France. William J. Faison's co-authors include Todd Bradley, Kevin Wiehe, Nishanth Marthandan, Mattia Bonsignori, David Easterhoff, Steven H. Kleinstein, Bjoern Peters, Brian Corrie, Jamie K. Scott and Uri Laserson and has published in prestigious journals such as Nature Immunology, Scientific Reports and Frontiers in Immunology.

In The Last Decade

William J. Faison

9 papers receiving 239 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
William J. Faison United States	7	141	139	67	47	21	9	244
Susanna Marquez United States	10	205 1.5×	199 1.4×	75 1.1×	79 1.7×	28 1.3×	18	363
Florent Colomb United Kingdom	12	207 1.5×	254 1.8×	38 0.6×	32 0.7×	43 2.0×	19	375
Sneha Rangarajan United States	10	135 1.0×	100 0.7×	96 1.4×	21 0.4×	38 1.8×	10	312
Cécile Hérate France	9	62 0.4×	116 0.8×	52 0.8×	62 1.3×	13 0.6×	14	215
Erica Houthuys Belgium	8	108 0.8×	154 1.1×	48 0.7×	30 0.6×	28 1.3×	14	291
Hongjin Bian United States	6	225 1.6×	142 1.0×	71 1.1×	16 0.3×	56 2.7×	9	347
Bianka Mußil France	8	74 0.5×	160 1.2×	51 0.8×	62 1.3×	38 1.8×	9	285
Paula Ordonez Japan	6	52 0.4×	64 0.5×	114 1.7×	82 1.7×	17 0.8×	9	256
Néstor Vázquez Bernat Sweden	6	250 1.8×	120 0.9×	112 1.7×	119 2.5×	7 0.3×	8	338
Collin Joyce United States	3	180 1.3×	169 1.2×	166 2.5×	37 0.8×	24 1.1×	6	329

Countries citing papers authored by William J. Faison

Since Specialization

Citations

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

Fields of papers citing papers by William J. Faison

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William J. Faison

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

All Works

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9 of 9 papers shown

Colone, Alessia, et al.. (2019). Detection of a Low Level and Heterogeneous B Cell Immune Response in Peripheral Blood of Acute Borreliosis Patients With High Throughput Sequencing. Frontiers in Immunology. 10. 1105–1105. 7 indexed citations

Frisbee, Alyse, Todd Bradley, William J. Faison, et al.. (2019). HLA class II-Restricted CD8+ T cells in HIV-1 Virus Controllers. Scientific Reports. 9(1). 10165–10165. 9 indexed citations

Wiehe, Kevin, Todd Bradley, Robert Meyerhoff, et al.. (2018). Functional Relevance of Improbable Antibody Mutations for HIV Broadly Neutralizing Antibody Development. Cell Host & Microbe. 23(6). 759–765.e6. 72 indexed citations

Faison, William J., et al.. (2018). High-throughput sequencing of murine immunoglobulin heavy chain repertoires using single side unique molecular identifiers on an Ion Torrent PGM. Oncotarget. 9(54). 30225–30239. 1 indexed citations

Rubelt, Florian, Christian E. Busse, Syed Ahmad Chan Bukhari, et al.. (2017). Adaptive Immune Receptor Repertoire Community recommendations for sharing immune-repertoire sequencing data. Nature Immunology. 18(12). 1274–1278. 116 indexed citations

Faison, William J., et al.. (2017). Functionally Convergent B Cell Receptor Sequences in Transgenic Rats Expressing a Human B Cell Repertoire in Response to Tetanus Toxoid and Measles Antigens. Frontiers in Immunology. 8. 1834–1834. 8 indexed citations

Faison, William J., et al.. (2016). High-resolution analysis of the B cell repertoire before and after polyethylene glycol fusion reveals preferential fusion of rare antigen-specific B cells. Human Antibodies. 24(1-2). 1–15. 4 indexed citations

Faison, William J., Alexandre Rostovtsev, Eduardo Castro‐Nallar, et al.. (2014). Whole genome single-nucleotide variation profile-based phylogenetic tree building methods for analysis of viral, bacterial and human genomes. Genomics. 104(1). 1–7. 15 indexed citations

Cole, Charles N., Konstantinos Krampis, Konstantinos Karagiannis, et al.. (2014). Non-synonymous variations in cancer and their effects on the human proteome: workflow for NGS data biocuration and proteome-wide analysis of TCGA data. BMC Bioinformatics. 15(1). 28–28. 12 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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