Jack Fu

5.0k citations
17 papers · 372 · h-index 8

Impact in

    • Genomics and Chromatin Dynamics
    • RNA Research and Splicing
    • Ubiquitin and proteasome pathways
    • Epigenetics and DNA Methylation
    • Genetics and Neurodevelopmental Disorders
    • Genomics and Rare Diseases
    • Genomic variations and chromosomal abnormalities

Papers in

    • Biomedical Text Mining and Ontologies 4
    • Genomic variations and chromosomal abnormalities 7
    • Genetics and Neurodevelopmental Disorders 4
    • Genomics and Rare Diseases 4

Jack Fu

17 papers receiving 367 citations

Peers

Jack Fu
Comparison fields: 5 of 63
  • Molecular Biology 273
  • Genetics 91
  • Cell Biology 34
  • Cognitive Neuroscience 40
  • Cancer Research 28
Replace Jack S. Hsiao with:
Jack S. Hsiao United States
Xinlei Li China
Jill D. Gerber United States
Nicholas Sciascia United States
Manling Ma-Edmonds United States
Mary Gardiner United Kingdom
Laksshman Sundaram United States
Kirsten Cremer Germany
Anna Hackett Australia
Sachiyo Ohashi Japan
Jack Fu relative to Jack S. Hsiao United States Jack S. Hsiao's profile →
Citations per field
00.5×3.1×
Jack S. Hsiao · 1×
Citations per year

Countries citing papers authored by Jack Fu

Since Specialization
Citations

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

Fields of papers citing papers by Jack Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 1998158
2 201858
3 202339
4 202335
5 202122
6 202219
7 200411
8 20167
9 20235
10 20074
11 20074
12 20063
13 20182
14 20212
15 20181
16 20081
17 20071

About Jack Fu

Jack Fu is a scholar working on Molecular Biology, Genetics, Artificial Intelligence, Computer Networks and Communications and Cognitive Neuroscience, having authored 17 papers that have together received 372 indexed citations. Recurring topics across this work include Genomic variations and chromosomal abnormalities (7 papers), Semantic Web and Ontologies (6 papers), Advanced Database Systems and Queries (5 papers), Genetics and Neurodevelopmental Disorders (4 papers), Biomedical Text Mining and Ontologies (4 papers), Genomics and Rare Diseases (4 papers), Autism Spectrum Disorder Research (3 papers) and Cancer Genomics and Diagnostics (2 papers). The work is most often cited by research in Molecular Biology (273 citations), Genetics (91 citations), Cell Biology (34 citations), Cognitive Neuroscience (40 citations) and Cancer Research (28 citations). Jack Fu has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Tapas K. Kundu, Robert G. Roeder, Ernest Martinez, Michael E. Talkowski, Seth S. Margolis, Thomas Schaffer, Chan Hyun Na, Michael Delannoy, Kapil V. Ramachandran and F. Kyle Satterstrom. Their work appears in journals such as Nature Genetics, Bioinformatics, JAMA Pediatrics, Cell Genomics and Journal of Biological Chemistry.

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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