Johanna B. Withers

668 total citations
27 papers, 492 citations indexed

About

Johanna B. Withers is a scholar working on Rheumatology, Molecular Biology and Epidemiology. According to data from OpenAlex, Johanna B. Withers has authored 27 papers receiving a total of 492 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Rheumatology, 10 papers in Molecular Biology and 6 papers in Epidemiology. Recurrent topics in Johanna B. Withers's work include Rheumatoid Arthritis Research and Therapies (11 papers), Viral Infections and Immunology Research (5 papers) and Biosimilars and Bioanalytical Methods (5 papers). Johanna B. Withers is often cited by papers focused on Rheumatoid Arthritis Research and Therapies (11 papers), Viral Infections and Immunology Research (5 papers) and Biosimilars and Bioanalytical Methods (5 papers). Johanna B. Withers collaborates with scholars based in United States, France and Canada. Johanna B. Withers's co-authors include Yingfu Li, Rani P. Cruz, Karen Beemon, Lixia Zhang, Joan A. Steitz, Joel M. Kremer, Dimitrios A. Pappas, Jeffrey C. F. Lam, Viatcheslav R. Akmaev and Yingfu Li and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Johanna B. Withers

25 papers receiving 473 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Johanna B. Withers United States 13 310 83 51 37 37 27 492
H Furukawa Japan 11 220 0.7× 16 0.2× 31 0.6× 13 0.4× 16 0.4× 30 475
Virginia Chu United States 6 150 0.5× 12 0.1× 38 0.7× 30 0.8× 12 0.3× 6 368
Douglas Ross‐Thriepland United Kingdom 9 114 0.4× 11 0.1× 25 0.5× 15 0.4× 23 0.6× 13 350
Ji Chang You South Korea 11 377 1.2× 14 0.2× 78 1.5× 14 0.4× 25 0.7× 35 579
Danhua Zhao China 6 283 0.9× 6 0.1× 94 1.8× 21 0.6× 28 0.8× 17 487
Michel Ventura France 15 349 1.1× 9 0.1× 42 0.8× 30 0.8× 65 1.8× 28 585
Patrik Dahlén Finland 12 201 0.6× 9 0.1× 20 0.4× 37 1.0× 23 0.6× 16 430
Ulfert Rand Germany 14 201 0.6× 13 0.2× 353 6.9× 28 0.8× 52 1.4× 26 654
Toni M. Schwarz United States 13 210 0.7× 17 0.2× 47 0.9× 4 0.1× 5 0.1× 17 401
Jérôme Chenau France 9 222 0.7× 46 0.6× 66 1.3× 33 0.9× 1 0.0× 10 339

Countries citing papers authored by Johanna B. Withers

Since Specialization
Citations

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

Fields of papers citing papers by Johanna B. Withers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Johanna B. Withers. 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 Johanna B. Withers. The network helps show where Johanna B. Withers may publish in the future.

Co-authorship network of co-authors of Johanna B. Withers

This figure shows the co-authorship network connecting the top 25 collaborators of Johanna B. Withers. A scholar is included among the top collaborators of Johanna B. Withers 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 Johanna B. Withers. Johanna B. Withers 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.
Nowell, W. Benjamin, Shilpa Venkatachalam, Kelly Gavigan, et al.. (2023). Patient Perceptions of Rheumatoid Arthritis Blood Work: A Cross‐Sectional Survey in the ArthritisPower Registry. Arthritis Care & Research. 77(2). 163–168. 1 indexed citations
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Ghiassian, Susan Dina, et al.. (2022). Network-based response module comprised of gene expression biomarkers predicts response to infliximab at treatment initiation in ulcerative colitis. Translational research. 246. 78–86. 4 indexed citations
4.
Zhang, Lixia, et al.. (2022). The module triad: a novel network biology approach to utilize patients’ multi-omics data for target discovery in ulcerative colitis. Scientific Reports. 12(1). 21685–21685. 6 indexed citations
5.
6.
Curtis, Jeffrey R., Vibeke Strand, Lixia Zhang, et al.. (2022). Patient outcomes improve when a molecular signature test guides treatment decision-making in rheumatoid arthritis. Expert Review of Molecular Diagnostics. 22(10). 973–982. 5 indexed citations
7.
Withers, Johanna B., Piero Ricchiuto, Michael O. McAnally, et al.. (2021). A systems-based method to repurpose marketed therapeutics for antiviral use: a SARS-CoV-2 case study. Life Science Alliance. 4(5). e202000904–e202000904. 2 indexed citations
8.
Arnell, Christopher, Martin Bergman, Dhiman Basu, et al.. (2021). Guided therapy selection in rheumatoid arthritis using a molecular signature response classifier: an assessment of budget impact and clinical utility. Journal of Managed Care & Specialty Pharmacy. 27(12). 1734–1742. 3 indexed citations
9.
Cohen, Stanley, Alvin F. Wells, Jeffrey R. Curtis, et al.. (2021). A Molecular Signature Response Classifier to Predict Inadequate Response to Tumor Necrosis Factor-α Inhibitors: The NETWORK-004 Prospective Observational Study. Rheumatology and Therapy. 8(3). 1159–1176. 23 indexed citations
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Mellors, Theodore, Johanna B. Withers, Asher Ameli, et al.. (2020). Clinical Validation of a Blood-Based Predictive Test for Stratification of Response to Tumor Necrosis Factor Inhibitor Therapies in Rheumatoid Arthritis Patients. SHILAP Revista de lepidopterología. 3(1). 91–104. 30 indexed citations
12.
Bergman, Martin, Alan Kivitz, Dimitrios A. Pappas, et al.. (2020). Clinical Utility and Cost Savings in Predicting Inadequate Response to Anti-TNF Therapies in Rheumatoid Arthritis. Rheumatology and Therapy. 7(4). 775–792. 20 indexed citations
13.
Withers, Johanna B., et al.. (2019). Idiosyncrasies of Viral Noncoding RNAs Provide Insights into Host Cell Biology. Annual Review of Virology. 6(1). 297–317. 21 indexed citations
14.
Withers, Johanna B., et al.. (2012). Exclusion of Exon 2 Is a Common mRNA Splice Variant of Primate Telomerase Reverse Transcriptases. PLoS ONE. 7(10). e48016–e48016. 24 indexed citations
15.
Withers, Johanna B. & Karen Beemon. (2011). The structure and function of the rous sarcoma virus RNA stability element. Journal of Cellular Biochemistry. 112(11). 3085–3092. 30 indexed citations
16.
Lam, Jeffrey C. F., Johanna B. Withers, & Yingfu Li. (2010). A Complex RNA-Cleaving DNAzyme That Can Efficiently Cleave a Pyrimidine–Pyrimidine Junction. Journal of Molecular Biology. 400(4). 689–701. 17 indexed citations
17.
Withers, Johanna B. & Karen Beemon. (2010). Structural features in the Rous sarcoma virus RNA stability element are necessary for sensing the correct termination codon. Retrovirology. 7(1). 65–65. 31 indexed citations
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19.
Erskine, P.T., Mark Knight, Halina Mikolajek, et al.. (2006). High Resolution Structure of BipD: An Invasion Protein Associated with the Type III Secretion System of Burkholderia Pseudomallei. Journal of Molecular Biology. 363(1). 125–136. 47 indexed citations
20.
Cruz, Rani P., Johanna B. Withers, & Yingfu Li. (2004). Dinucleotide Junction Cleavage Versatility of 8-17 Deoxyribozyme. Chemistry & Biology. 11(1). 57–67. 164 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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