Daniel Eriksson

2.5k citations
32 papers · 754 indexed · h-index 15

Impact in

    • Spectroscopy and Chemometric Analyses
    • Metabolomics and Mass Spectrometry Studies
    • Gene expression and cancer classification
    • Bioinformatics and Genomic Networks

Papers in

Daniel Eriksson

29 papers receiving 718 citations

Peers

Daniel Eriksson
Comparison fields: 5 of 116
  • Analytical Chemistry 64
  • Molecular Biology 308
  • Endocrinology, Diabetes and Metabolism 70
  • Food Science 75
  • Biochemistry 20
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Na Guan China
Xiaoqing Ye China
Cheng Pan China
Xuan Dong China
Xiaomeng Liu China
Jaspreet Sandhu United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Eriksson

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Eriksson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20240
4 20237
5 20230
6 20234
7 202210
8 20204
9 20188
10 201825
11 20184
12 201641
13 20164
14 20169
15 201121
16 200764
17 2007187
18 200649
19 200516
20
Spatial modeling of nature conservation variables useful in forestry planning
20006

About Daniel Eriksson

Daniel Eriksson is a scholar working on Nature and Landscape Conservation, Endocrinology, Diabetes and Metabolism, Genetics, Biotechnology and Building and Construction, having authored 32 papers that have together received 754 indexed citations. Recurring topics across this work include Forest ecology and management (5 papers), Adrenal Hormones and Disorders (5 papers), Gene expression and cancer classification (4 papers), Hormonal Regulation and Hypertension (4 papers), BRCA gene mutations in cancer (3 papers), Wood Treatment and Properties (3 papers), Diabetes and associated disorders (3 papers) and Molecular Biology Techniques and Applications (3 papers). The work is most often cited by research in Analytical Chemistry (64 citations), Molecular Biology (308 citations), Endocrinology, Diabetes and Metabolism (70 citations), Food Science (75 citations) and Biochemistry (20 citations). Daniel Eriksson has collaborated with scholars based in Sweden, United States and Norway. Frequent co-authors include Max Bylesjö, Johan Trygg, Thomas Möritz, Miyako Kusano, Urban Bergsten, Stefan Jansson, Andreas Sjödin, Paul Geladi, Mehrdad Arshadi and Olle Kämpe. Their work appears in journals such as Journal of Internal Medicine, BMC Bioinformatics, The Plant Journal, Scientific Reports and Frontiers in Immunology.

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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