Deebly Chavez

578 citations
6 papers · 432 · h-index 5

Impact in

    • Liver physiology and pathology
    • Neonatal Respiratory Health Research
    • Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
    • Pulmonary Hypertension Research and Treatments
    • Medical Imaging and Pathology Studies

Papers in

Deebly Chavez

6 papers receiving 429 citations

Peers

Deebly Chavez
Comparison fields: 5 of 62
  • Hepatology 51
  • Pulmonary and Respiratory Medicine 192
  • Immunology 70
  • Genetics 31
  • Surgery 106
Replace Robert Brockett with:
Robert Brockett United States
Jacob Hull Kristensen Denmark
Hideki Makino Japan
Debomita Chakraborty Germany
Manik Amin United States
Takayuki Imada Japan
Dorthe Vang Larsen Denmark
Ji Hyun Lee South Korea
Stéphanie Brayer France
Zehava Vadasz Israel
Deebly Chavez relative to Robert Brockett United States Robert Brockett's profile →
Citations per field
00.5×10×20×26×
Robert Brockett · 1×
Citations per year

Countries citing papers authored by Deebly Chavez

Since Specialization
Citations

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

Fields of papers citing papers by Deebly Chavez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

6 of 6 papers shown
#Work
1 2016202
2 2015121
3 201661
4 201726
5 202218
6 20234

About Deebly Chavez

Deebly Chavez is a scholar working on Pulmonary and Respiratory Medicine, Surgery, Molecular Biology, Epidemiology and Hepatology, having authored 6 papers that have together received 432 indexed citations. Recurring topics across this work include Neonatal Respiratory Health Research (3 papers), Liver physiology and pathology (2 papers), Pulmonary Hypertension Research and Treatments (2 papers), 14-3-3 protein interactions (1 paper), Bioinformatics and Genomic Networks (1 paper), Pancreatic function and diabetes (1 paper), Computational Drug Discovery Methods (1 paper) and Pleural and Pulmonary Diseases (1 paper). The work is most often cited by research in Hepatology (51 citations), Pulmonary and Respiratory Medicine (192 citations), Immunology (70 citations), Genetics (31 citations) and Surgery (106 citations). Deebly Chavez has collaborated with scholars based in United States, Sweden and China. Frequent co-authors include Bi‐Sen Ding, Shahin Rafii, Zhongwei Cao, Koji Shido, Sina Y. Rabbany, Raphaël Lis, Michael Ginsberg, Guo‐Hua Fong, Thomas P. Sakmar and Ilias Ι. Siempos. Their work appears in journals such as Nature Cell Biology, Nature Medicine, Journal of Clinical Investigation, JCI Insight and Nature Communications.

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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