Mikko Arvas

12.4k total citations
62 papers, 1.4k citations indexed

About

Mikko Arvas is a scholar working on Molecular Biology, Management of Technology and Innovation and Genetics. According to data from OpenAlex, Mikko Arvas has authored 62 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 17 papers in Management of Technology and Innovation and 15 papers in Genetics. Recurrent topics in Mikko Arvas's work include Blood donation and transfusion practices (17 papers), Hemoglobinopathies and Related Disorders (15 papers) and Iron Metabolism and Disorders (14 papers). Mikko Arvas is often cited by papers focused on Blood donation and transfusion practices (17 papers), Hemoglobinopathies and Related Disorders (15 papers) and Iron Metabolism and Disorders (14 papers). Mikko Arvas collaborates with scholars based in Finland, Netherlands and United Kingdom. Mikko Arvas's co-authors include Merja Penttilä, Markku Saloheimo, Tiina Pakula, Merja Oja, Mari Häkkinen, Nina Aro, Mari Valkonen, Marika Vitikainen, Jukka Partanen and Ann Westerholm‐Parvinen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

Mikko Arvas

58 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Mikko Arvas Finland	19	821	509	266	201	129	62	1.4k
Marcel van den Broek Netherlands	27	1.8k 2.2×	539 1.1×	407 1.5×	163 0.8×	154 1.2×	57	2.3k
Virve Vidgren Finland	21	1.0k 1.3×	224 0.4×	551 2.1×	102 0.5×	213 1.7×	32	1.6k
Takao Kitagawa Japan	20	674 0.8×	147 0.3×	85 0.3×	49 0.2×	49 0.4×	67	1.0k
Zhiming Hu China	22	593 0.7×	62 0.1×	56 0.2×	109 0.5×	39 0.3×	93	1.3k
Kai Wu China	23	1.1k 1.3×	96 0.2×	132 0.5×	56 0.3×	75 0.6×	102	1.7k
Ying Zhuo China	25	1.4k 1.7×	91 0.2×	139 0.5×	116 0.6×	58 0.4×	56	2.1k
Yoshiki Yamasaki Japan	19	458 0.6×	202 0.4×	490 1.8×	482 2.4×	21 0.2×	82	1.1k
Haili Li China	20	623 0.8×	41 0.1×	553 2.1×	21 0.1×	76 0.6×	101	1.5k
Hee Min Yoo South Korea	18	733 0.9×	103 0.2×	48 0.2×	41 0.2×	80 0.6×	61	1.2k

Countries citing papers authored by Mikko Arvas

Since Specialization

Citations

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

Fields of papers citing papers by Mikko Arvas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mikko Arvas

This figure shows the co-authorship network connecting the top 25 collaborators of Mikko Arvas. A scholar is included among the top collaborators of Mikko Arvas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mikko Arvas. Mikko Arvas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Perola, Markus, et al.. (2025). Electronic health records reveal variations in the use of blood units by hour and medical specialty. Vox Sanguinis. 120(6). 584–596. 1 indexed citations

Remoortel, Hans Van, Lucile Malard, Ronél Swanevelder, et al.. (2025). Potential benefits of an alternative haemoglobin deferral strategy evaluated in seven countries. Vox Sanguinis. 121(1). 26–34.

Arvas, Mikko, et al.. (2025). Biobank participants’ perspectives on receiving genetic risk information from a biobank – the case of haemochromatosis. BMC Medical Genomics. 18(1). 197–197.

Hurk, Katja van den, Mikko Arvas, David J. Roberts, Johanna Castrén, & Christian Erikstrup. (2024). Whole Blood Donor Iron Management Across Europe: Experiences and Challenges in Four Blood Establishments. Transfusion Medicine Reviews. 38(4). 150860–150860. 3 indexed citations

Dillon, Mary, et al.. (2023). Supporting platelet inventory management decisions: What is the effect of extending platelets’ shelf life?. European Journal of Operational Research. 310(2). 640–654. 9 indexed citations

Kerkelä, Erja, Ulla Impola, Jukka Partanen, et al.. (2023). DeepIFC : Virtual fluorescent labeling of blood cells in imaging flow cytometry data with deep learning. Cytometry Part A. 103(10). 807–817. 3 indexed citations

Toivonen, Jarkko, Veerle Compernolle, Surendra Karki, et al.. (2023). An international comparison of haemoglobin deferral prediction models for blood banking. Vox Sanguinis. 118(6). 430–439. 5 indexed citations

Toivonen, Jarkko, et al.. (2023). The value of genetic data from 665,460 individuals in managing iron deficiency anaemia and suitability to donate blood. Vox Sanguinis. 119(1). 34–42. 1 indexed citations

Lobier, Muriel, Antti Larjo, Pirkko Mattila, et al.. (2019). FinDonor 10 000 study: a cohort to identify iron depletion and factors affecting it in Finnish blood donors. Vox Sanguinis. 115(1). 36–46. 16 indexed citations

10.

Lobier, Muriel, et al.. (2019). The effect of donation activity dwarfs the effect of lifestyle, diet and targeted iron supplementation on blood donor iron stores. PLoS ONE. 14(8). e0220862–e0220862. 13 indexed citations

11.

Brandl, Julian, María Victoria Aguilar Pontes, Mikko Arvas, et al.. (2018). A community-driven reconstruction of the Aspergillus niger metabolic network. SHILAP Revista de lepidopterología. 5(1). 16–16. 22 indexed citations

12.

Kumar, Abhishek, Jens Laurids Sørensen, Frederik Teilfeldt Hansen, et al.. (2018). Genome Sequencing and analyses of Two Marine Fungi from the North Sea Unraveled a Plethora of Novel Biosynthetic Gene Clusters. Scientific Reports. 8(1). 10187–10187. 27 indexed citations

13.

Kuivanen, Joosu, Mikko Arvas, & Peter Richard. (2017). Clustered Genes Encoding 2-Keto-l-Gulonate Reductase and l-Idonate 5-Dehydrogenase in the Novel Fungal d-Glucuronic Acid Pathway. Frontiers in Microbiology. 8. 225–225. 23 indexed citations

14.

Faccio, Greta, Mikko Arvas, Perttu Permi, et al.. (2017). Characterization of sulfhydryl oxidase from Aspergillus tubingensis. BMC Biochemistry. 18(1). 15–15. 4 indexed citations

15.

Castillo, Sandra, Dorothee Barth, Mikko Arvas, et al.. (2016). Whole-genome metabolic model of Trichoderma reesei built by comparative reconstruction. Biotechnology for Biofuels. 9(1). 252–252. 16 indexed citations

16.

Kuivanen, Joosu, et al.. (2016). A novel pathway for fungal D-glucuronate catabolism contains an L-idonate forming 2-keto-L-gulonate reductase. Scientific Reports. 6(1). 26329–26329. 22 indexed citations

17.

Kumar, Abhishek, Bernard Henrissat, Mikko Arvas, et al.. (2015). De Novo Assembly and Genome Analyses of the Marine-Derived Scopulariopsis brevicaulis Strain LF580 Unravels Life-Style Traits and Anticancerous Scopularide Biosynthetic Gene Cluster. PLoS ONE. 10(10). e0140398–e0140398. 29 indexed citations

18.

Arvas, Mikko, Teemu Kivioja, Alex Mitchell, et al.. (2007). Comparison of protein coding gene contents of the fungal phyla Pezizomycotina and Saccharomycotina. BMC Genomics. 8(1). 325–325. 46 indexed citations

19.

Kivioja, Teemu, Mikko Arvas, Markku Saloheimo, Merja Penttilä, & Esko Ukkonen. (2005). Optimization of cDNA-AFLP experiments using genomic sequence data. Computer applications in the biosciences. 21(11). 2573–2579. 18 indexed citations

20.

Kivioja, Teemu, Mikko Arvas, Kari Kataja, et al.. (2002). Assigning probes into a small number of pools separable by electrophoresis. Bioinformatics. 18(suppl_1). S199–S206. 20 indexed citations

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.

Explore authors with similar magnitude of impact