Jennifer A. Cham

836 citations
6 papers · 155 · h-index 6

Impact in

Papers in

    • Biomedical Text Mining and Ontologies 2
    • Bioinformatics and Genomic Networks 2
    • Genetics, Bioinformatics, and Biomedical Research 2
    • Genomics and Phylogenetic Studies 1
    • Advanced Proteomics Techniques and Applications 2
    • Mass Spectrometry Techniques and Applications 2
    • Analytical Chemistry and Chromatography 1

Jennifer A. Cham

6 papers receiving 154 citations

Peers

Jennifer A. Cham
Comparison fields: 5 of 56
  • Spectroscopy 66
  • Information Systems and Management 15
  • Molecular Biology 100
  • Human-Computer Interaction 4
  • Health Information Management 2
Replace Pieter Lukasse with:
Pieter Lukasse Netherlands
Dmitry Repchevsky Spain
Kimberly Begley United States
Saqib Mir United Kingdom
Fawaz Ghali United Kingdom
Sanjay Agravat United States
Giles Velarde United Kingdom
Lars Kolbowski Germany
Laia Codó Spain
Avinash Kumar Shanmugam United States
Jennifer A. Cham relative to Pieter Lukasse Netherlands Pieter Lukasse's profile →
Citations per field
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Citations per year

Countries citing papers authored by Jennifer A. Cham

Since Specialization
Citations

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

Fields of papers citing papers by Jennifer A. Cham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jennifer A. Cham. 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 Jennifer A. Cham. The network helps show where Jennifer A. Cham may publish in the future.

Co-authors

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

All Works

6 of 6 papers shown

About Jennifer A. Cham

Jennifer A. Cham is a scholar working on Molecular Biology, Spectroscopy, Information Systems and Management, Computer Science Applications and Biomedical Engineering, having authored 6 papers that have together received 155 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (2 papers), Biomedical Text Mining and Ontologies (2 papers), Bioinformatics and Genomic Networks (2 papers), Mass Spectrometry Techniques and Applications (2 papers), Genetics, Bioinformatics, and Biomedical Research (2 papers), Genomics and Phylogenetic Studies (1 paper), Analytical Chemistry and Chromatography (1 paper) and Scientific Computing and Data Management (1 paper). The work is most often cited by research in Spectroscopy (66 citations), Information Systems and Management (15 citations), Molecular Biology (100 citations), Human-Computer Interaction (4 citations) and Health Information Management (2 citations). Jennifer A. Cham has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Luca Bianco, Conrad Bessant, Christoph Steinbeck, Paula de Matos, Graham Cameron, Cath Brooksbank, Chris Barton, Rodrigo López, Tamer Gür and Silvano Squizzato. Their work appears in journals such as Nucleic Acids Research, Drug Discovery Today, Journal of Proteome Research, PLoS Computational Biology and PROTEOMICS.

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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