Michael Takla
Impact in
Papers in
-
- Insect Resistance and Genetics 4
- CRISPR and Genetic Engineering 4
- Ubiquitin and proteasome pathways 2
- Ion channel regulation and function 2
- Co-authors
- David C. Rubinsztein (3 shared papers)Kamalan Jeevaratnam (4 shared papers)Niall Wilson (1 shared paper)Viktor I. Korolchuk (1 shared paper)Lidia Wróbel (1 shared paper)Sung Min Son (1 shared paper)Christopher Huang (3 shared papers)Anthony J. Conner (5 shared papers)
- Journals
- Computer Methods and Programs in Biomedicine (1 paper)Cell Reports (1 paper)Neuron (1 paper)EMBO Reports (1 paper)Saudi Pharmaceutical Journal (1 paper)
- Partner nations
- United KingdomNew ZealandGermany
In The Last Decade
Michael Takla
14 papers receiving 224 citations
Michael Takla's Hit Papers
Peers
Comparison fields: 5 of 61
- Health Informatics 8
- Aging 6
- Physiology 10
- Biological Psychiatry 4
- Epidemiology 51
Countries citing papers authored by Michael Takla
This map shows the geographic impact of Michael Takla'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 Michael Takla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Takla more than expected).
Fields of papers citing papers by Michael Takla
This network shows the impact of papers produced by Michael Takla. 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 Michael Takla. The network helps show where Michael Takla may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Takla, 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 | Autophagy, aging, and age-related neurodegeneration Hit paper breakdown → | 2024 | 86 |
| 2 | 2023 | 37 | |
| 3 | 2004 | 19 | |
| 4 | 2020 | 18 | |
| 5 | 2020 | 18 | |
| 6 | 2024 | 11 | |
| 7 | 2009 | 9 | |
| 8 | 2002 | 8 | |
| 9 | 2021 | 7 | |
| 10 | Evaluation of transgenic approaches for controlling tuber moth in potatoes. | 2005 | 5 |
| 11 | 2005 | 5 | |
| 12 | 2023 | 4 | |
| 13 | 2021 | 3 | |
| 14 | 2024 | 1 |
About Michael Takla
Michael Takla is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Cardiology and Cardiovascular Medicine, Health Informatics and Epidemiology, having authored 14 papers that have together received 231 indexed citations. Recurring topics across this work include Insect Resistance and Genetics (4 papers), CRISPR and Genetic Engineering (4 papers), Cardiac electrophysiology and arrhythmias (2 papers), Ubiquitin and proteasome pathways (2 papers), Genetically Modified Organisms Research (2 papers), Ion channel regulation and function (2 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Autophagy in Disease and Therapy (2 papers). The work is most often cited by research in Health Informatics (8 citations), Aging (6 citations), Physiology (10 citations), Biological Psychiatry (4 citations) and Epidemiology (51 citations). Michael Takla has collaborated with scholars based in United Kingdom, New Zealand and Germany. Frequent co-authors include David C. Rubinsztein, Kamalan Jeevaratnam, Niall Wilson, Viktor I. Korolchuk, Lidia Wróbel, Sung Min Son, Christopher Huang, Anthony J. Conner, Jeanne M. E. Jacobs and S. D. Wratten. Their work appears in journals such as Computer Methods and Programs in Biomedicine, Cell Reports, Neuron, EMBO Reports and Saudi Pharmaceutical Journal.
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.