Mark Ayers

15.8k citations
56 papers · 7.8k indexed · 3 hit papers · h-index 33

Mark Ayers

55 papers receiving 7.7k citations

Hit Papers

T-Cell–Inflamed Gene-Expression ...656200520262012201950010001.5k2.0k

Peers

Mark Ayers
Comparison fields: 5 of 117
  • Oncology 5.2k
  • Cancer Research 2.7k
  • Immunology 1.6k
  • Pulmonary and Respiratory Medicine 1.9k
  • Pathology and Forensic Medicine 780
Replace Shumei Kato with:
Shumei Kato United States
Todd M. Bauer United States
Florent Petitprez France
Priti Lal United States
Marcin Kowanetz United States
Roberto Salgado Belgium
Silvia Darb‐Esfahani Germany
Paolo Nucíforo Spain
Bjørn Naume Norway
Lukas C. Amler United States
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Citations per field
00.5×2.5×
Shumei Kato · 1×
Citations per year

Countries citing papers authored by Mark Ayers

Since Specialization
Citations

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

Fields of papers citing papers by Mark Ayers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Mark Ayers, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mark Ayers Line = papers co-authored together Mark Ayers links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 202340
3 202254
4 202140
5 201827
6
T-Cell–Inflamed Gene-Expression Profile, Programmed Death Ligand 1 Expression, and Tumor Mutational Burden Predict Efficacy in Patients Treated With Pembrolizumab Across 20 Cancers: KEYNOTE-028breakdown →
2018656
7 20175
8 201652
9 201573
10 20155
11 201321
12 201228
13 200839
14
Breast Cancer Molecular Subtypes Respond Differently to Preoperative Chemotherapybreakdown →
20051414
15 200541
16 200534
17 20048
18 2003140
19 200346
20
Gene expression profiles obtained from fine-needle aspirations of breast cancer reliably identify routine prognostic markers and reveal large-scale molecular differences between estrogen-negative and estrogen-positive tumors.
2003168

About Mark Ayers

Mark Ayers is a scholar working on Cancer Research, Oncology, Otorhinolaryngology, Pulmonary and Respiratory Medicine and Molecular Biology, having authored 56 papers that have together received 7.8k indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (22 papers), Cancer Genomics and Diagnostics (18 papers), Colorectal Cancer Treatments and Studies (10 papers), Lung Cancer Treatments and Mutations (9 papers), Gene expression and cancer classification (9 papers), Breast Cancer Treatment Studies (8 papers), HER2/EGFR in Cancer Research (6 papers) and Pancreatic and Hepatic Oncology Research (5 papers). The work is most often cited by research in Oncology (5.2k citations), Cancer Research (2.7k citations), Immunology (1.6k citations), Pulmonary and Respiratory Medicine (1.9k citations) and Pathology and Forensic Medicine (780 citations). Mark Ayers has collaborated with scholars based in United States, Japan and South Korea. Frequent co-authors include Lajos Pusztai, James Stec, Jared Lunceford, W. Fraser Symmans, Jeffrey S. Ross, Gabriel N. Hortobágyi, Andrey Loboda, Sarina A. Piha‐Paul, Andrew Albright and Michael Nebozhyn. Their work appears in journals such as Journal of Clinical Oncology, Annals of Oncology, Clinical Cancer Research, Cancer Research and The Oncologist.

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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