Mark H. Chin

2.8k citations
15 papers · 1.3k · h-index 12

Impact in

    • Neurogenesis and neuroplasticity mechanisms
    • Advanced Proteomics Techniques and Applications
    • Mass Spectrometry Techniques and Applications

Papers in

    • Bioinformatics and Genomic Networks 3
    • Gene expression and cancer classification 3
    • Machine Learning in Bioinformatics 2
    • Metabolomics and Mass Spectrometry Studies 2
    • CRISPR and Genetic Engineering 2

Mark H. Chin

15 papers receiving 1.2k citations

Peers

Mark H. Chin
Comparison fields: 5 of 89
  • Developmental Neuroscience 133
  • Spectroscopy 221
  • Molecular Biology 902
  • Neurology 84
  • Genetics 257
Replace Jan Baumgart with:
Jan Baumgart Germany
Joseph Peltier United States
Olga Zelenaia United States
Sebastian Schmitt Germany
Anders M. Hinsby Denmark
Caroline G. Bergner Germany
John M. Aletta United States
Yukie Hirahara Japan
Filippo Casoni Italy
Rujun Kang Canada
Mark H. Chin relative to Jan Baumgart Germany Jan Baumgart's profile →
Citations per field
00.5×1.5×2.4×
Jan Baumgart · 1×
Citations per year

Countries citing papers authored by Mark H. Chin

Since Specialization
Citations

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

Fields of papers citing papers by Mark H. Chin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark H. Chin. 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 Mark H. Chin. The network helps show where Mark H. Chin may publish in the future.

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2005328
2 2010211
3 2006127
4 2006115
5 200294
6 200883
7 200775
8 200764
9 201063
10 201340
11 200723
12 201019
13 20095
14 20173
15 20083

About Mark H. Chin

Mark H. Chin is a scholar working on Molecular Biology, Physiology, Genetics, Spectroscopy and Neurology, having authored 15 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (3 papers), Bioinformatics and Genomic Networks (3 papers), Gene expression and cancer classification (3 papers), Machine Learning in Bioinformatics (2 papers), Parkinson's Disease Mechanisms and Treatments (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), CRISPR and Genetic Engineering (2 papers) and Amino Acid Enzymes and Metabolism (2 papers). The work is most often cited by research in Developmental Neuroscience (133 citations), Spectroscopy (221 citations), Molecular Biology (902 citations), Neurology (84 citations) and Genetics (257 citations). Mark H. Chin has collaborated with scholars based in United States, Netherlands and Australia. Frequent co-authors include Desmond Smith, Weijun Qian, Richard Smith, David Camp, Hai Wang, Diana J. Bigelow, Vladislav Petyuk, Guoping Fan, Ke Shuai and Keri Martinowich. Their work appears in journals such as Journal of Proteome Research, SLAS DISCOVERY, Molecular Biology of the Cell, Molecular & Cellular Proteomics and BMC Bioinformatics.

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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