Michelle Y. Chan

711 citations
6 papers · 272 indexed · h-index 5
Topics
Protein purification and stability (2 papers)Immunotherapy and Immune Responses (2 papers)Monoclonal and Polyclonal Antibodies Research (2 papers)
Journals
Nature CommunicationsNeuronMethods in molecular biology
Partner nations
United StatesCanada

In The Last Decade

Michelle Y. Chan

6 papers receiving 268 citations

Peers

Michelle Y. Chan
Comparison fields: 5 of 62
  • Molecular Biology 202
  • Neurology 81
  • Genetics 55
  • Cellular and Molecular Neuroscience 24
  • Cell Biology 18
Replace Roland Kirchner with:
Roland Kirchner Germany
Miguel B. Coelho United Kingdom
Bhalchandra S. Rao United States
J.M. Baumhardt United States
D. Daujotyte United States
Andrii Kopach Germany
Arun Kumar Tharkeshwar Belgium
Amirhossein Ghanbari Niaki United States
Jaya Sarkar United States
Assael A. Madrigal United States
Michelle Y. Chan relative to Roland Kirchner Germany Roland Kirchner's profile →
Citations per field
00.5×11.5×
Roland Kirchner · 1×
Citations per year

Countries citing papers authored by Michelle Y. Chan

Since Specialization
Citations

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

Fields of papers citing papers by Michelle Y. Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michelle Y. Chan. 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 Michelle Y. Chan. The network helps show where Michelle Y. Chan may publish in the future.

Co-authorship network of co-authors of Michelle Y. Chan

This figure shows the co-authorship network connecting the top 25 collaborators of Michelle Y. Chan. A scholar is included among the top collaborators of Michelle Y. Chan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michelle Y. Chan. Michelle Y. Chan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

6 of 6 papers shown
#WorkIndexed citations
1 17
2 198
3 7
4 1
5 7
6 42

About Michelle Y. Chan

Michelle Y. Chan is a scholar working on Biophysics, Biotechnology and Immunology, having authored 6 papers that have together received 272 indexed citations. Recurring topics across this work include Protein purification and stability (2 papers), Immunotherapy and Immune Responses (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). The work is most often cited by research in Neurology (81 citations), Genetics (55 citations) and Molecular Biology (202 citations). Michelle Y. Chan has collaborated with scholars based in United States and Canada. Frequent co-authors include Ryan M. Kramer, Nicholas A. Castello, Ashkan Javaherian, Steven Finkbeiner, Jeremy W. Linsley, Éric Lécuyer, G Yeo, Mark Y. Fang, Sebastian Markmiller and Anthony Q. Vu. Their work appears in journals such as Nature Communications, Neuron and Methods in molecular biology.

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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