Maija Lahtela‐Kakkonen

74 papers receiving 2.7k citations

Maija Lahtela‐Kakkonen's Hit Papers

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development 2020 · 403 citations
4030+2+4Years since publication100200300400

Peers

Maija Lahtela‐Kakkonen
Comparison fields: 5 of 130
  • Geriatrics and Gerontology 771
  • Physiology 280
  • Computational Theory and Mathematics 313
  • Biochemistry 125
  • Complementary and alternative medicine 133
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Thomas Erker Austria
Izet M. Kapetanović United States
Meishiang Jang United States
Hyung Ryong Moon South Korea
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Marinella Roberti Italy
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Grace Chao Yeh United States
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Countries citing papers authored by Maija Lahtela‐Kakkonen

Since Specialization
Citations

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

Fields of papers citing papers by Maija Lahtela‐Kakkonen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maija Lahtela‐Kakkonen. 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 Maija Lahtela‐Kakkonen. The network helps show where Maija Lahtela‐Kakkonen may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
Hit paper breakdown →
2020403
2 2016308
3 2014129
4 2012126
5 2018117
6 2014111
7 201282
8 200868
9 201660
10 201759
11 200459
12 200958
13 201456
14 202349
15 200449
16 200546
17 200645
18 201445
19 201943
20 201141

About Maija Lahtela‐Kakkonen

Maija Lahtela‐Kakkonen is a scholar working on Molecular Biology, Geriatrics and Gerontology, Oncology, Computational Theory and Mathematics and Physiology, having authored 76 papers that have together received 2.8k indexed citations. Recurring topics across this work include Sirtuins and Resveratrol in Medicine (27 papers), Calcium signaling and nucleotide metabolism (10 papers), Computational Drug Discovery Methods (10 papers), Biochemical effects in animals (7 papers), Pharmacogenetics and Drug Metabolism (6 papers), Autophagy in Disease and Therapy (6 papers), PARP inhibition in cancer therapy (6 papers) and Tea Polyphenols and Effects (6 papers). The work is most often cited by research in Geriatrics and Gerontology (771 citations), Physiology (280 citations), Computational Theory and Mathematics (313 citations), Biochemistry (125 citations) and Complementary and alternative medicine (133 citations). Maija Lahtela‐Kakkonen has collaborated with scholars based in Finland, United States and Italy. Frequent co-authors include Elina M. Jarho, Antti Poso, Minna Rahnasto‐Rilla, Tiina Suuronen, Tarja Kokkola, Outi M. H. Salo‐Ahen, Antonello Mai, Dante Rotili, Lucia Altucci and Wim Vanden Berghe. Their work appears in journals such as Journal of Medicinal Chemistry, European Journal of Pharmaceutical Sciences, ACS Medicinal Chemistry Letters, Biomedicine & Pharmacotherapy and Bioorganic & Medicinal Chemistry.

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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