Avash Das

1.4k citations
22 papers · 963 indexed · h-index 15

Impact in

Papers in

Avash Das

22 papers receiving 951 citations

Peers

Avash Das
Comparison fields: 5 of 114
  • Cancer Research 185
  • Cardiology and Cardiovascular Medicine 192
  • Hepatology 63
  • Endocrinology, Diabetes and Metabolism 120
  • Epidemiology 224
Replace Xiaopeng Li with:
Xiaopeng Li United States
Michelle J. Ormseth United States
Barbara Toffoli Italy
Jan K. Hennigs Germany
Massimiliano Mancini Italy
Francesca Cardella Italy
José Delgado Alves Portugal
Daniel Carpio Spain
Gül Bahtiyar United States
Avash Das relative to Xiaopeng Li United States Xiaopeng Li's profile →
Citations per field
00.5×3.2×
Xiaopeng Li · 1×
Citations per year

Countries citing papers authored by Avash Das

Since Specialization
Citations

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

Fields of papers citing papers by Avash Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20248
2 202421
3 202328
4 202121
5 202188
6 20203
7 202092
8 202031
9 202028
10 201923
11 2019123
12 201848
13 201854
14 2017162
15 20171
16 2017137
17 201723
18 20162
19 20161
20 20161

About Avash Das

Avash Das is a scholar working on Clinical Biochemistry, Biochemistry, Hematology, Endocrinology, Diabetes and Metabolism and Cardiology and Cardiovascular Medicine, having authored 22 papers that have together received 963 indexed citations. Recurring topics across this work include Extracellular vesicles in disease (4 papers), Liver Disease Diagnosis and Treatment (3 papers), Multiple Myeloma Research and Treatments (2 papers), Lipid metabolism and biosynthesis (2 papers), Lipoproteins and Cardiovascular Health (2 papers), MicroRNA in disease regulation (2 papers), Protein Degradation and Inhibitors (2 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (2 papers). The work is most often cited by research in Cancer Research (185 citations), Cardiology and Cardiovascular Medicine (192 citations), Hepatology (63 citations), Endocrinology, Diabetes and Metabolism (120 citations) and Epidemiology (224 citations). Avash Das has collaborated with scholars based in United States, China and New Zealand. Frequent co-authors include Fei Luo, Federico Oldoni, Zhenfei Fang, Panyun Wu, Jingfei Chen, Saumya Das, Xiangping Li, Ravi V. Shah, Arjun Gupta and Nivedita Arora. Their work appears in journals such as Progress in Cardiovascular Diseases, British Journal of Haematology, American Journal of Cardiovascular Drugs, Lipids in Health and Disease and Circulation Research.

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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