Ankit Sinha

4.0k citations
34 papers · 1.4k · h-index 18

Impact in

Papers in

    • Extracellular vesicles in disease 6
    • RNA Interference and Gene Delivery 3
    • Metabolomics and Mass Spectrometry Studies 2
    • Machine Learning in Bioinformatics 2
    • Advanced Proteomics Techniques and Applications 8

Ankit Sinha

33 papers receiving 1.4k citations

Peers

Ankit Sinha
Comparison fields: 5 of 115
  • Cancer Research 292
  • Molecular Biology 735
  • Spectroscopy 172
  • Mechanics of Materials 236
  • Ocean Engineering 138
Replace Hongkun Liu with:
Hongkun Liu China
Benjamin B. Williams United States
Steven Robert McDougall United Kingdom
Yueguo Li China
Jean Tessier United Kingdom
Hong Ji China
Jiliang Xia China
Maria C. Johansson Sweden
Toru Shibata Japan
S. R. McDougall United Kingdom
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Citations per field
00.5×11.5×
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Citations per year

Countries citing papers authored by Ankit Sinha

Since Specialization
Citations

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

Fields of papers citing papers by Ankit Sinha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009301
2 2013138
3 2017109
4 2014104
5 2017104
6 2014101
7 201395
8 201873
9 202050
10 201737
11 201332
12 201429
13 201729
14 201928
15 201427
16 201522
17 201120
18 201918
19 202316
20 201715

About Ankit Sinha

Ankit Sinha is a scholar working on Molecular Biology, Spectroscopy, Immunology, Oncology and Cell Biology, having authored 34 papers that have together received 1.4k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (8 papers), Extracellular vesicles in disease (6 papers), RNA Interference and Gene Delivery (3 papers), Cellular transport and secretion (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Immunotherapy and Immune Responses (2 papers), Machine Learning in Bioinformatics (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Cancer Research (292 citations), Molecular Biology (735 citations), Spectroscopy (172 citations), Mechanics of Materials (236 citations) and Ocean Engineering (138 citations). Ankit Sinha has collaborated with scholars based in Canada, United States and India. Frequent co-authors include Thomas Kislinger, Jayant K. Singh, Sudhir Kumar Singh, Goutam Deo, Vladimir Ignatchenko, Alexandr Ignatchenko, Javier A. Alfaro, Paul C. Boutros, Simona Principe and Salvador Mejia‐Guerrero. Their work appears in journals such as PROTEOMICS, Nature Communications, Journal of Proteome Research, Neuro-Oncology 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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