Ilan Wapinski

6.3k total citations · 1 hit paper
38 papers, 2.0k citations indexed

About

Ilan Wapinski is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Oncology. According to data from OpenAlex, Ilan Wapinski has authored 38 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 15 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Oncology. Recurrent topics in Ilan Wapinski's work include Radiomics and Machine Learning in Medical Imaging (15 papers), AI in cancer detection (8 papers) and Fungal and yeast genetics research (7 papers). Ilan Wapinski is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (15 papers), AI in cancer detection (8 papers) and Fungal and yeast genetics research (7 papers). Ilan Wapinski collaborates with scholars based in United States, Israel and United Kingdom. Ilan Wapinski's co-authors include Aviv Regev, Nir Friedman, Avi Pfeffer, William Stafford Noble, Paul Pavlidis, Anne‐Ruxandra Carvunis, Nicolas Simonis, Marc Vidal, Michael E. Cusick and Thomas Rolland and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Clinical Oncology.

In The Last Decade

Ilan Wapinski

37 papers receiving 2.0k citations

Hit Papers

Construction and Analysis of Two Genome-Scale Deletion Li... 2017 2026 2020 2023 2017 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Construction and Analysis of Two Genome-Scale Deletion Libraries for Bacillus subtilis
    2017 414 citations Byoung‐Mo Koo, George Kritikos et al. Cell Systems profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ilan Wapinski United States 15 1.6k 522 337 237 103 38 2.0k
Mahmut Uludağ Saudi Arabia 10 1.5k 1.0× 280 0.5× 381 1.1× 241 1.0× 153 1.5× 24 2.4k
Alexandre Gattiker Switzerland 13 1.7k 1.1× 379 0.7× 463 1.4× 145 0.6× 178 1.7× 14 2.5k
Depeng Wang China 25 1.7k 1.1× 359 0.7× 544 1.6× 218 0.9× 72 0.7× 46 2.8k
Sébastien Moretti Switzerland 16 1.6k 1.0× 362 0.7× 357 1.1× 217 0.9× 106 1.0× 28 2.3k
Philip Bucher Germany 9 2.0k 1.3× 273 0.5× 353 1.0× 159 0.7× 173 1.7× 12 2.8k
Michele Magrane United Kingdom 14 1.7k 1.1× 211 0.4× 192 0.6× 175 0.7× 110 1.1× 21 2.2k
Rasko Leinonen United Kingdom 9 2.4k 1.5× 501 1.0× 475 1.4× 325 1.4× 87 0.8× 11 3.3k
Petra Langendijk-Genevaux Switzerland 10 1.8k 1.2× 266 0.5× 498 1.5× 190 0.8× 167 1.6× 13 2.6k
Beatriz A. Castilho Brazil 26 1.6k 1.0× 421 0.8× 199 0.6× 179 0.8× 289 2.8× 47 2.2k
Gregory Von Kuster United States 6 1.2k 0.8× 327 0.6× 275 0.8× 276 1.2× 64 0.6× 6 1.9k

Countries citing papers authored by Ilan Wapinski

Since Specialization
Citations

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

Fields of papers citing papers by Ilan Wapinski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ilan Wapinski. 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 Ilan Wapinski. The network helps show where Ilan Wapinski may publish in the future.

Co-authorship network of co-authors of Ilan Wapinski

This figure shows the co-authorship network connecting the top 25 collaborators of Ilan Wapinski. A scholar is included among the top collaborators of Ilan Wapinski 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 Ilan Wapinski. Ilan Wapinski 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.
Herbst, Roy S., Daniel Ruderman, James F. Conway, et al.. (2023). OA15.04 Comparison of Digital Vs Manual PD-L1 Tumour Cell Scoring on SP263-Stained Whole Imaging Slides from IMpower110. Journal of Thoracic Oncology. 18(11). S79–S80. 2 indexed citations
2.
Walker, Andrew, Geetika Singh, Mary Lin, et al.. (2023). Mo1754 MACHINE LEARNING-BASED PREDICTION OF GEBOES SCORE AND HISTOLOGIC IMPROVEMENT AND REMISSION THRESHOLDS IN ULCERATIVE COLITIS. Gastroenterology. 164(6). S–894.
3.
Li, Jin, et al.. (2023). MACHINE LEARNING-BASED PREDICTION OF GEBOES SCORE AND HISTOLOGIC IMPROVEMENT AND REMISSION THRESHOLDS IN ULCERATIVE COLITIS. Gastroenterology. 164(4). S25–S26. 2 indexed citations
4.
Conway, Jake R., Yevgeniy Gindin, David Z. Pan, et al.. (2023). Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASH. Cell Reports Medicine. 4(4). 101016–101016. 12 indexed citations
5.
Lin, Mary, et al.. (2023). Artificial Intelligence Enables Quantitative Assessment of Ulcerative Colitis Histology. Modern Pathology. 36(6). 100124–100124. 28 indexed citations
6.
Nguyen, Tan H., Mohammad Mirzadeh, Aaditya Prakash, et al.. (2023). Abstract P5-02-09: Quantitative analysis of fiber-level collagen features in H&E whole-slide images predicts neoadjuvant therapy response in patients with HER2+ breast cancer. Cancer Research. 83(5_Supplement). P5–2. 1 indexed citations
7.
Srinivasan, Sandhya, Neel Patel, Michael G. Drage, et al.. (2023). Abstract 5447: Artificial intelligence (AI)-based classification of stromal subtypes reveals associations between stromal composition and prognosis in NSCLC. Cancer Research. 83(7_Supplement). 5447–5447. 1 indexed citations
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10.
Szabó, Péter M., George Lee, Scott Ely, et al.. (2019). CD8+ T cells in tumor parenchyma and stroma by image analysis (IA) and gene expression profiling (GEP): Potential biomarkers for immuno-oncology (I-O) therapy.. Journal of Clinical Oncology. 37(15_suppl). 2594–2594. 4 indexed citations
11.
Manson, Abigail L., Christopher A. Desjardins, Alejandro Pironti, et al.. (2018). SynerClust: a highly scalable, synteny-aware orthologue clustering tool. Microbial Genomics. 4(11). 12 indexed citations
12.
Koo, Byoung‐Mo, George Kritikos, Jeremiah D. Farelli, et al.. (2017). Construction and Analysis of Two Genome-Scale Deletion Libraries for Bacillus subtilis. Cell Systems. 4(3). 291–305.e7. 414 indexed citations breakdown →
13.
Muntel, Jan, Sarah A. Boswell, Shaojun Tang, et al.. (2014). Abundance-based Classifier for the Prediction of Mass Spectrometric Peptide Detectability Upon Enrichment (PPA). Molecular & Cellular Proteomics. 14(2). 430–440. 20 indexed citations
14.
Roy, Sushmita, Ilan Wapinski, Jenna Pfiffner, et al.. (2013). Arboretum: Reconstruction and analysis of the evolutionary history of condition-specific transcriptional modules. Genome Research. 23(6). 1039–1050. 43 indexed citations
15.
Carvunis, Anne‐Ruxandra, Thomas Rolland, Ilan Wapinski, et al.. (2012). Proto-genes and de novo gene birth. Nature. 487(7407). 370–374. 444 indexed citations
16.
Wapinski, Ilan, Jenna Pfiffner, Courtney E. French, et al.. (2010). Gene duplication and the evolution of ribosomal protein gene regulation in yeast. Proceedings of the National Academy of Sciences. 107(12). 5505–5510. 58 indexed citations
17.
Wapinski, Ilan & Aviv Regev. (2010). Reconstructing Gene Histories in Ascomycota Fungi. Methods in enzymology on CD-ROM/Methods in enzymology. 470. 447–485. 3 indexed citations
18.
Li, Qianru, Anne‐Ruxandra Carvunis, Haiyuan Yu, et al.. (2008). Revisiting the Saccharomyces cerevisiae predicted ORFeome. Genome Research. 18(8). 1294–1303. 23 indexed citations
19.
Wapinski, Ilan, Avi Pfeffer, Nir Friedman, & Aviv Regev. (2007). Natural history and evolutionary principles of gene duplication in fungi. Nature. 449(7158). 54–61. 480 indexed citations
20.
Pavlidis, Paul, Ilan Wapinski, & William Stafford Noble. (2004). Support vector machine classification on the web. Bioinformatics. 20(4). 586–587. 100 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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