Chand S. Mangat

1.1k citations
29 papers · 634 indexed · h-index 13
Topics
SARS-CoV-2 detection and testing (13 papers)Biosensors and Analytical Detection (8 papers)Advanced biosensing and bioanalysis techniques (6 papers)

In The Last Decade

Chand S. Mangat

26 papers receiving 625 citations

Peers

Chand S. Mangat
Comparison fields: 5 of 79
  • Infectious Diseases 278
  • Molecular Biology 268
  • Biomedical Engineering 167
  • Molecular Medicine 121
  • Genetics 98
Replace Shisong Fang with:
Shisong Fang China
Bachar H. Hassan United States
Vijaya Kumar Deekshit India
Cherilyn D. Garner United States
Alison S. Low United Kingdom
Taro Noguchi Japan
Imane El Meouche France
Jung-Ho Youn United States
Arne M. Taxt Norway
Solomon Mwaigwisya United Kingdom
Chand S. Mangat relative to Shisong Fang China Shisong Fang's profile →
Citations per field
00.5×2.8×
Shisong Fang · 1×
Citations per year

Countries citing papers authored by Chand S. Mangat

Since Specialization
Citations

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

Fields of papers citing papers by Chand S. Mangat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chand S. Mangat. 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 Chand S. Mangat. The network helps show where Chand S. Mangat may publish in the future.

Co-authorship network of co-authors of Chand S. Mangat

This figure shows the co-authorship network connecting the top 25 collaborators of Chand S. Mangat. A scholar is included among the top collaborators of Chand S. Mangat 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 Chand S. Mangat. Chand S. Mangat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 5
4 2
5 0
6 10
7 6
8 8
9 4
10 7
11 9
12 28
13 70
14 8
15 35
16 85
17 53
18 40
19 21
20 5

About Chand S. Mangat

Chand S. Mangat is a scholar working on Molecular Medicine, Infectious Diseases and Endocrinology, having authored 29 papers that have together received 634 indexed citations. Recurring topics across this work include SARS-CoV-2 detection and testing (13 papers), Biosensors and Analytical Detection (8 papers) and Advanced biosensing and bioanalysis techniques (6 papers). The work is most often cited by research in Molecular Medicine (121 citations), Infectious Diseases (278 citations) and Endocrinology (65 citations). Chand S. Mangat has collaborated with scholars based in Canada, United States and Sweden. Frequent co-authors include Eric D. Brown, Amrita Bharat, Michael R. Mulvey, Sebastian S. Gehrke, Shawn French, James R. Williamson, Jean‐Philippe Côté, Jonathan Stokes, Joseph H. Davis and Shelley Peterson. Their work appears in journals such as The Science of The Total Environment, Scientific Reports and Journal of Clinical Microbiology.

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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