Imlimaong Aier

855 citations
24 papers · 617 · h-index 8

Impact in

Papers in

    • Epigenetics and DNA Methylation 5
    • Machine Learning in Bioinformatics 4
    • RNA modifications and cancer 3
    • Cancer Genomics and Diagnostics 3

Imlimaong Aier

22 papers receiving 607 citations

Peers

Imlimaong Aier
Comparison fields: 5 of 110
  • Sensory Systems 76
  • Computational Theory and Mathematics 109
  • Molecular Biology 307
  • Cancer Research 58
  • Oncology 93
Replace Veronica Di Sarno with:
Veronica Di Sarno Italy
Chun‐Chen Chen Taiwan
Thomas Ryckmans United Kingdom
Maryam Hamzeh‐Mivehroud Iran
Sunhye Hong South Korea
Emmanuel Prata de Souza Brazil
Brian J. Bender United States
Huang Huang China
Maximilian C. C. J. C. Ebert Canada
Judith V. Hobrath United States
Imlimaong Aier relative to Veronica Di Sarno Italy Veronica Di Sarno's profile →
Citations per field
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Veronica Di Sarno · 1×
Citations per year

Countries citing papers authored by Imlimaong Aier

Since Specialization
Citations

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

Fields of papers citing papers by Imlimaong Aier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Imlimaong Aier, 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 Imlimaong Aier Line = papers co-authored together Imlimaong Aier 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 2016318
2 201895
3 201890
4 202025
5 201914
6 201810
7 20208
8 20177
9 20197
10 20207
11 20226
12 20175
13 20175
14 20154
15 20204
16 20183
17 20193
18 20252
19 20231
20 20251

About Imlimaong Aier

Imlimaong Aier is a scholar working on Molecular Biology, Cancer Research, Oncology, Sensory Systems and Nutrition and Dietetics, having authored 24 papers that have together received 617 indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (5 papers), Pancreatic and Hepatic Oncology Research (5 papers), Machine Learning in Bioinformatics (4 papers), Olfactory and Sensory Function Studies (4 papers), Computational Drug Discovery Methods (3 papers), Biochemical Analysis and Sensing Techniques (3 papers), Cancer Genomics and Diagnostics (3 papers) and RNA modifications and cancer (3 papers). The work is most often cited by research in Sensory Systems (76 citations), Computational Theory and Mathematics (109 citations), Molecular Biology (307 citations), Cancer Research (58 citations) and Oncology (93 citations). Imlimaong Aier has collaborated with scholars based in India. Frequent co-authors include Pritish Kumar Varadwaj, Utkarsh Raj, Rahul Semwal, Anju Sharma, Pankaj Tyagi, Rajnish Kumar, Rashmi Tripathi, Pavan Chakraborty, Nirmalya Sen and Sumit Kumar Hira. Their work appears in journals such as Journal of Biomolecular Structure and Dynamics, Scientific Reports, Neural Computing and Applications, Current Neuropharmacology and IEEE/ACM Transactions on Computational Biology and 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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