Everardo Macias

437 citations
15 papers · 331 indexed · h-index 9

Impact in

Papers in

    • Cancer, Lipids, and Metabolism 5
    • Cancer, Hypoxia, and Metabolism 2
    • Hippo pathway signaling and YAP/TAZ 4

Everardo Macias

15 papers receiving 326 citations

Peers

Everardo Macias
Comparison fields: 5 of 57
  • Cancer Research 150
  • Hepatology 28
  • Oncology 71
  • Pulmonary and Respiratory Medicine 74
  • Molecular Biology 155
Replace Zhishi Yang with:
Zhishi Yang China
Boyun Shi China
Qiandong Zhu China
Kaijing Wang China
Zhongqin Gong China
Xianju Qin China
Márcia Saldanha Kubrusly Brazil
Baomin Shi China
Atsutaka Masuda Japan
Nanhong Tang China
Everardo Macias relative to Zhishi Yang China Zhishi Yang's profile →
Citations per field
00.5×6.7×
Zhishi Yang · 1×
Citations per year

Countries citing papers authored by Everardo Macias

Since Specialization
Citations

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

Fields of papers citing papers by Everardo Macias

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Everardo Macias, 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 Everardo Macias Line = papers co-authored together Everardo Macias links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 20245
2 20232
3 20236
4 20227
5 202123
6 20218
7 202044
8 20191
9 201822
10 201789
11 201721
12
Angiotensin receptor signaling and prostate tumor growth in mice.
20175
13 201617
14 20118
15 200873

About Everardo Macias

Everardo Macias is a scholar working on Cancer Research, Cell Biology, Pulmonary and Respiratory Medicine, Hepatology and Endocrinology, Diabetes and Metabolism, having authored 15 papers that have together received 331 indexed citations. Recurring topics across this work include Cancer, Lipids, and Metabolism (5 papers), Hippo pathway signaling and YAP/TAZ (4 papers), Prostate Cancer Treatment and Research (4 papers), Cholesterol and Lipid Metabolism (3 papers), Ubiquitin and proteasome pathways (3 papers), Cancer, Hypoxia, and Metabolism (2 papers), Cancer-related Molecular Pathways (2 papers) and Cell death mechanisms and regulation (1 paper). The work is most often cited by research in Cancer Research (150 citations), Hepatology (28 citations), Oncology (71 citations), Pulmonary and Respiratory Medicine (74 citations) and Molecular Biology (155 citations). Everardo Macias has collaborated with scholars based in United States, China and Jordan. Frequent co-authors include Stephen J. Freedland, Jen‐Tsan Chi, Marcelo L. Rodríguez‐Puebla, Mahmoud A. Alfaqih, Michael R. Freeman, Kirk D. Jones, Ernest T. Lam, Mohini A. Patil, Xin Chen and Susie A. Lee. Their work appears in journals such as Cancer Research, The Prostate, Prostate Cancer and Prostatic Diseases, Molecular Cancer Research and Cancers.

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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