John Tra

894 citations
7 papers · 739 indexed · h-index 6

Impact in

    • Advanced Proteomics Techniques and Applications
    • Mass Spectrometry Techniques and Applications
  • Cell Biology top 10%
    • Endoplasmic Reticulum Stress and Disease

Papers in

    • Advanced Proteomics Techniques and Applications 3
    • Machine Learning in Bioinformatics 1
    • Protein purification and stability 1
    • RNA modifications and cancer 1
    • Epigenetics and DNA Methylation 1
    • Cancer-related gene regulation 1

John Tra

7 papers receiving 713 citations

Peers

John Tra
Comparison fields: 5 of 92
  • Spectroscopy 243
  • Cell Biology 162
  • Molecular Biology 538
  • Aging 13
  • Immunology 87
Replace Eric Puravs with:
Eric Puravs United States
Jun Ho Jang South Korea
Franck Brichory United States
Niaobh O’Donoghue Ireland
Kevin Brown Chandler United States
Simon Hauri Switzerland
Jette B. Lauridsen Denmark
Therese Dau Germany
Chuanfei Yu China
Courtney Voss Canada
John Tra relative to Eric Puravs United States Eric Puravs's profile →
Citations per field
00.5×1.5×
Eric Puravs · 1×
Citations per year

Countries citing papers authored by John Tra

Since Specialization
Citations

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

Fields of papers citing papers by John Tra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

7 of 7 papers shown
#Work
1 2003429
2 2005113
3 200167
4 200558
5 200241
6 201428
7 20113

About John Tra

John Tra is a scholar working on Spectroscopy, Molecular Biology, Oncology, Cell Biology and Cardiology and Cardiovascular Medicine, having authored 7 papers that have together received 739 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (3 papers), Machine Learning in Bioinformatics (1 paper), Protein purification and stability (1 paper), RNA modifications and cancer (1 paper), Clusterin in disease pathology (1 paper), Epigenetics and DNA Methylation (1 paper), Cancer-related gene regulation (1 paper) and Blood properties and coagulation (1 paper). The work is most often cited by research in Spectroscopy (243 citations), Cell Biology (162 citations), Molecular Biology (538 citations), Aging (13 citations) and Immunology (87 citations). John Tra has collaborated with scholars based in United States. Frequent co-authors include Samir Hanash, David E. Misek, Franck Brichory, Eric Puravs, Hong Wang, Jun Ho Jang, Bong Kyung Shin, Rong Zhao, François Le Naour and Claire W. Michael. Their work appears in journals such as PROTEOMICS, Mechanisms of Ageing and Development, Molecular & Cellular Proteomics, Journal of Biological Chemistry and PROTEOMICS - CLINICAL APPLICATIONS.

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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