Abhisek Mukherjee
- Neurology top 2%
- Neurological diseases and metabolism 5
- Parkinson's Disease Mechanisms and Treatments 3
- Neurology top 5%
- Neurological diseases and metabolism 5
- Parkinson's Disease Mechanisms and Treatments 3
- Aging top 5%
- Physiology top 5%
- Alzheimer's disease research and treatments 8
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- Prion Diseases and Protein Misfolding 7
- Signaling Pathways in Disease 3
- Pluripotent Stem Cells Research 2
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- Trace Elements in Health 3
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- Endoplasmic Reticulum Stress and Disease 3
- Co-authors
- Claudio SotoDiego Morales‐ScheihingPeter C. ButlerMohammad ShahnawazKarina Cuanalo-ContrerasNicolás MéndezAnn M. SchmeichelAh-Lim Tsai
- Cited by
- NeurologyAgingPhysiology
- Partner nations
- United StatesChileMexico
In The Last Decade
Abhisek Mukherjee
25 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 107
- Neurology 495
- Neurology 264
- Aging 40
- Physiology 514
- Cellular and Molecular Neuroscience 208
Countries citing papers authored by Abhisek Mukherjee
This map shows the geographic impact of Abhisek Mukherjee'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 Abhisek Mukherjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abhisek Mukherjee more than expected).
Fields of papers citing papers by Abhisek Mukherjee
This network shows the impact of papers produced by Abhisek Mukherjee. 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 Abhisek Mukherjee. The network helps show where Abhisek Mukherjee may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Abhisek Mukherjee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 48 | |
| 2 | 2023 | 26 | |
| 3 | 2022 | 6 | |
| 4 | 2022 | 2 | |
| 5 | 2021 | 11 | |
| 6 | 2021 | 1 | |
| 7 | Discriminating α-synuclein strains in Parkinson’s disease and multiple system atrophybreakdown → | 2020 | 535 |
| 8 | 2020 | 1 | |
| 9 | 2020 | 10 | |
| 10 | 2017 | 25 | |
| 11 | 2017 | 35 | |
| 12 | 2016 | 15 | |
| 13 | 2015 | 268 | |
| 14 | 2015 | 3 | |
| 15 | 2013 | 1 | |
| 16 | 2013 | 2 | |
| 17 | 2012 | 13 | |
| 18 | 2011 | 59 | |
| 19 | 2010 | 43 | |
| 20 | 2009 | 93 |
About Abhisek Mukherjee
Abhisek Mukherjee is a scholar working on Aging, Biological Psychiatry, Neurology, Clinical Biochemistry and Physiology, having authored 25 papers that have together received 1.4k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (8 papers), Prion Diseases and Protein Misfolding (7 papers), Neurological diseases and metabolism (5 papers), Trace Elements in Health (3 papers), Endoplasmic Reticulum Stress and Disease (3 papers), Parkinson's Disease Mechanisms and Treatments (3 papers), Signaling Pathways in Disease (3 papers) and Pluripotent Stem Cells Research (2 papers). The work is most often cited by research in Neurology (495 citations), Neurology (264 citations), Aging (40 citations), Physiology (514 citations) and Cellular and Molecular Neuroscience (208 citations). Abhisek Mukherjee has collaborated with scholars based in United States, Chile and Mexico. Frequent co-authors include Claudio Soto, Diego Morales‐Scheihing, Peter C. Butler, Mohammad Shahnawaz, Karina Cuanalo-Contreras, Nicolás Méndez, Ann M. Schmeichel, Ah-Lim Tsai, Wolfgang Singer and Gang Wu. Their work appears in journals such as PLoS Pathogens, Cells, Alzheimer s & Dementia, Frontiers in Aging Neuroscience and PLoS ONE.
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.