Hong Ni

508 citations
18 papers · 369 indexed · h-index 9

Hong Ni

18 papers receiving 353 citations

Peers

Hong Ni
Comparison fields: 5 of 77
  • Molecular Biology 244
  • Cancer Research 38
  • Pharmacology 22
  • Computational Theory and Mathematics 33
  • Cell Biology 31
Replace Ally Perlina with:
Ally Perlina United States
Lydia Aschauer Austria
Olivia Hanson‐Painton United States
Jeffrey A. Willy United States
Ty M. Thomson Switzerland
Sarah Mackenzie United States
Tiffany Cho Canada
Marije Niemeijer Netherlands
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Citations per field
00.5×1.5×1.9×
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Citations per year

Countries citing papers authored by Hong Ni

Since Specialization
Citations

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

Fields of papers citing papers by Hong Ni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

18 of 18 papers shown
#Work
1
Prokaryotic expression of cp genes from Apple stem grooving virus and production of antisera against recombinant coat proteins.
20101
2 20104
3 20105
4 20101
5
Application of Simplicity-based Envelope Extraction in Heart Sound Segmentation
20091
6 200565
7
[Investigation on the molecular mechanisms of anti-hepatocarcinoma herbs of traditional Chinese medicine by cell cycle microarray].
20059
8
Preparation and analysis of cSNP chip on hepatocellular carcinoma-related genes.
20055
9 200447
10
[Detection of differentially expressed genes in hepatocellularcarcinoma cells SMMC-7721 treated with Typhonium giganteum extract by mRNA differential display].
20044
11
The inhibition effects of typhonium giganteum engl. on hepatocarcinoma cell
20033
12 200310
13 20023
14 200240
15 200235
16 19999
17 199887
18 199840

About Hong Ni

Hong Ni is a scholar working on Biotechnology, Biophysics and Molecular Biology, having authored 18 papers that have together received 369 indexed citations. Recurring topics across this work include Gene expression and cancer classification (5 papers), Molecular Biology Techniques and Applications (4 papers), Immune Cell Function and Interaction (2 papers), Plant Genetic and Mutation Studies (2 papers), Virus-based gene therapy research (1 paper), Respiratory viral infections research (1 paper), Bacteriophages and microbial interactions (1 paper) and Genomics, phytochemicals, and oxidative stress (1 paper). The work is most often cited by research in Molecular Biology (244 citations), Cancer Research (38 citations) and Pharmacology (22 citations). Hong Ni has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Zhengbin Yao, Xuhong Sunny Wang, Katrina Diener, Lawrence Yoon, Kevin T. Morgan, Warren Casey, Roger H. Brown, Theodore Friedmann, Larry G. Johnson and John C. Olsen. Their work appears in journals such as Journal of Virology, Biochemical and Biophysical Research Communications and Environmental Health Perspectives.

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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