Arnab China

24 papers receiving 550 citations

Peers

Arnab China
Comparison fields: 5 of 77
  • Molecular Medicine 53
  • Infectious Diseases 160
  • Organic Chemistry 201
  • Molecular Biology 360
  • Toxicology 15
Replace Ashoka V. R. Madduri with:
Ashoka V. R. Madduri Netherlands
Peter C. Ray United Kingdom
Joseph Gambino United States
Jeremiah S. Helm United States
C. Dini France
Chengxin Zhi United States
Joseph W. Guiles United States
Aaron Korkegian United States
Marc A. Boudreau United States
P. F. MISCO United States
Arnab China relative to Ashoka V. R. Madduri Netherlands Ashoka V. R. Madduri's profile →
Citations per field
00.5×3.8×
Ashoka V. R. Madduri · 1×
Citations per year

Countries citing papers authored by Arnab China

Since Specialization
Citations

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

Fields of papers citing papers by Arnab China

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201798
2 200671
3 200856
4 200746
5 200745
6 200739
7 200723
8 201022
9 200720
10 200918
11 200816
12 201216
13 201114
14 200814
15 200614
16 201113
17 20239
18 20189
19 20109
20 20075

About Arnab China

Arnab China is a scholar working on Molecular Biology, Infectious Diseases, Epidemiology, Organic Chemistry and Genetics, having authored 24 papers that have together received 568 indexed citations. Recurring topics across this work include Cancer therapeutics and mechanisms (9 papers), RNA and protein synthesis mechanisms (9 papers), Tuberculosis Research and Epidemiology (9 papers), Mycobacterium research and diagnosis (8 papers), Synthesis and biological activity (6 papers), Synthesis and Biological Evaluation (5 papers), Bacterial Genetics and Biotechnology (5 papers) and RNA modifications and cancer (4 papers). The work is most often cited by research in Molecular Medicine (53 citations), Infectious Diseases (160 citations), Organic Chemistry (201 citations), Molecular Biology (360 citations) and Toxicology (15 citations). Arnab China has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Valakunja Nagaraja, Dharmarajan Sriram, Murugesan Dinakaran, Perumal Yogeeswari, Palaniappan Senthilkumar, Vikas Jain, R. Saleem-Batcha, Dipankar Chatterji, Paul L. Fox and K.I. Vasu. Their work appears in journals such as Microbiology, Nature Communications, Bioorganic & Medicinal Chemistry, PLoS ONE and Biochemical and Biophysical Research Communications.

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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