M. Håkansson
Impact in
- Immunology top 5%
- Galectins and Cancer Biology
- Molecular Biology top 10%
- Protein Structure and Dynamics
- Enzyme Catalysis and Immobilization
- Glycosylation and Glycoproteins Research
Papers in
- Immunology 13
- Galectins and Cancer Biology 11
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- Protein Structure and Dynamics 6
- Enzyme Catalysis and Immobilization 3
- Biochemical and Structural Characterization 2
- Co-authors
- Derek T. Logan (17 shared papers)Hakon Leffler (12 shared papers)Ulf J. Nilsson (12 shared papers)Mikael Akke (4 shared papers)Carl Diehl (6 shared papers)Samuel Genheden (2 shared papers)Ulf Ryde (2 shared papers)Björn Walse (7 shared papers)
In The Last Decade
M. Håkansson
47 papers receiving 1.5k citations
M. Håkansson's Hit Papers
Peers
Comparison fields: 5 of 91
- Immunology 370
- Molecular Biology 549
- Organic Chemistry 220
- Computational Theory and Mathematics 99
- Physical and Theoretical Chemistry 47
Countries citing papers authored by M. Håkansson
This map shows the geographic impact of M. Håkansson'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 M. Håkansson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Håkansson more than expected).
Fields of papers citing papers by M. Håkansson
This network shows the impact of papers produced by M. Håkansson. 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 M. Håkansson. The network helps show where M. Håkansson may publish in the future.
Co-authors
The 25 scholars most cited alongside M. Håkansson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 205 | |
| 2 | 2011 | 145 | |
| 3 | 2012 | 110 | |
| 4 | 2017 | 94 | |
| 5 | 2017 | 88 | |
| 6 | 2018 | 78 | |
| 7 | Prospective de novo drug design with deep interactome learning Hit paper breakdown → | 2024 | 60 |
| 8 | 2014 | 55 | |
| 9 | 2012 | 53 | |
| 10 | 1985 | 52 | |
| 11 | 2000 | 45 | |
| 12 | 2018 | 40 | |
| 13 | 1985 | 36 | |
| 14 | 2012 | 34 | |
| 15 | 2013 | 33 | |
| 16 | 2019 | 32 | |
| 17 | 2001 | 29 | |
| 18 | 2019 | 29 | |
| 19 | 2002 | 28 | |
| 20 | 2021 | 23 |
About M. Håkansson
M. Håkansson is a scholar working on Immunology, Molecular Biology, Materials Chemistry, Organic Chemistry and Oncology, having authored 48 papers that have together received 1.6k indexed citations. Recurring topics across this work include Galectins and Cancer Biology (11 papers), Enzyme Structure and Function (9 papers), Protein Structure and Dynamics (6 papers), Carbohydrate Chemistry and Synthesis (5 papers), Enzyme Catalysis and Immobilization (3 papers), Polysaccharides and Plant Cell Walls (3 papers), Bacteriophages and microbial interactions (3 papers) and Biochemical and Structural Characterization (2 papers). The work is most often cited by research in Immunology (370 citations), Molecular Biology (549 citations), Organic Chemistry (220 citations), Computational Theory and Mathematics (99 citations) and Physical and Theoretical Chemistry (47 citations). M. Håkansson has collaborated with scholars based in Sweden, Germany and Austria. Frequent co-authors include Derek T. Logan, Hakon Leffler, Ulf J. Nilsson, Mikael Akke, Carl Diehl, Samuel Genheden, Ulf Ryde, Björn Walse, Fredrik R. Zetterberg and Kristoffer Peterson. Their work appears in journals such as Journal of Medicinal Chemistry, Biochemistry, Journal of Biological Chemistry, ACS Medicinal Chemistry Letters and Acta Crystallographica Section D Structural Biology.
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.