{"entity": "researcher", "timestamp": "2026-09-25T18:00:07.552Z", "family": "Karlsson", "given": "Ida", "initials": "I", "orcid": "0000-0002-5598-1200", "affiliations": ["Department of Crop Production Ecology, Swedish University of Agricultural Sciences, Box 7043, 750 07, Uppsala, Sweden. ida.karlsson@scilifelab.uu.se.", "Present Address: Clinical Genomics Uppsala, Dept. of Immunology, Genetics and Pathology, Uppsala University, Rudbeck Laboratory, 751 85, Uppsala, Sweden. ida.karlsson@scilifelab.uu.se."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/0886d94fdde24c8aaaa3bbc2369e605b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/0886d94fdde24c8aaaa3bbc2369e605b"}}, "publications": [{"entity": "publication", "iuid": "57080e32c6004f3fb0352b5bb7b83c2d", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/57080e32c6004f3fb0352b5bb7b83c2d.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/57080e32c6004f3fb0352b5bb7b83c2d"}}, "title": "From SARS-CoV-2 to Global Preparedness: A Graphical Interface for Standardised High-Throughput Bioinformatics Analysis in Pandemic Scenarios and Surveillance of Drug Resistance.", "authors": [{"family": "Cumlin", "given": "Tomas", "initials": "T"}, {"family": "Karlsson", "given": "Ida", "initials": "I", "orcid": "0000-0002-5598-1200", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0886d94fdde24c8aaaa3bbc2369e605b.json"}}, {"family": "Haars", "given": "Jonathan", "initials": "J", "orcid": "0009-0003-8735-4097", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/366865f87201405b93e8c51c268f1d44.json"}}, {"family": "Rosengren", "given": "Maria", "initials": "M"}, {"family": "Lennerstrand", "given": "Johan", "initials": "J"}, {"family": "Pimushyna", "given": "Maryna", "initials": "M", "orcid": "0009-0001-7730-0584", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/5358506ed4514a39b2ca804e2f4d4056.json"}}, {"family": "Feuk", "given": "Lars", "initials": "L"}, {"family": "Ladenvall", "given": "Claes", "initials": "C", "orcid": "0000-0002-7501-6598", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/1cfe5cbb5d454552bdcbc464238f88fb.json"}}, {"family": "Kaden", "given": "Rene", "initials": "R", "orcid": "0000-0002-2111-9751", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/3cf620e34cca4df88309d96bf8cd0786.json"}}], "type": "journal article", "published": "2024-06-17", "journal": {"title": "Int J Mol Sci", "issn": "1422-0067", "volume": "25", "issue": "12", "issn-l": null}, "abstract": "The COVID-19 pandemic highlighted the need for a rapid, convenient, and scalable diagnostic method for detecting a novel pathogen amidst a global pandemic. While command-line interface tools offer automation for SARS-CoV-2 Oxford Nanopore Technology sequencing data analysis, they are inapplicable to users with limited programming skills. A solution is to establish such automated workflows within a graphical user interface software. We developed two workflows in the software Geneious Prime 2022.1.1, adapted for data obtained from the Midnight and Artic's nCoV-2019 sequencing protocols. Both workflows perform trimming, read mapping, consensus generation, and annotation on SARS-CoV-2 Nanopore sequencing data. Additionally, one workflow includes phylogenetic assignment using the bioinformatic tools pangolin and Nextclade as plugins. The basic workflow was validated in 2020, adhering to the requirements of the European Centre for Disease Prevention and Control for SARS-CoV-2 sequencing and analysis. The enhanced workflow, providing phylogenetic assignment, underwent validation at Uppsala University Hospital by analysing 96 clinical samples. It provided accurate diagnoses matching the original results of the basic workflow while also reducing manual clicks and analysis time. These bioinformatic workflows streamline SARS-CoV-2 Nanopore data analysis in Geneious Prime, saving time and manual work for operators lacking programming knowledge.", "doi": "10.3390/ijms25126645", "pmid": "38928350", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC11204113"}, {"db": "pii", "key": "ijms25126645"}], "notes": [], "created": "2026-09-23T13:17:32.119Z", "modified": "2026-09-23T13:17:32.235Z"}, {"entity": "publication", "iuid": "034069603230426a89d8014272c3e612", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/034069603230426a89d8014272c3e612.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/034069603230426a89d8014272c3e612"}}, "title": "Temporal and spatial dynamics of Fusarium spp. and mycotoxins in Swedish cereals during 16 years.", "authors": [{"family": "Karlsson", "given": "Ida", "initials": "I", "orcid": "0000-0002-5598-1200", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/0886d94fdde24c8aaaa3bbc2369e605b.json"}}, {"family": "Mellqvist", "given": "Eva", "initials": "E"}, {"family": "Persson", "given": "Paula", "initials": "P"}], "type": "journal article", "published": "2023-02-00", "journal": {"title": "Mycotoxin Res", "issn": "1867-1632", "volume": "39", "issue": "1", "pages": "3-18", "issn-l": null}, "abstract": "We analysed the dynamics of Fusarium spp. and mycotoxin contamination in Swedish cereals during 2004-2018. More than 1400 cereal samples from field trials were included, collected in a monitoring programme run by the Swedish Board of Agriculture. Five Fusarium mycotoxins were quantified with LC-MS/MS and fungal DNA from four species was quantified using quantitative real-time PCR. Correlation analyses revealed that deoxynivalenol (DON) and zearalenone (ZEN) were mainly associated with Fusarium graminearum, but stronger correlations with F. culmorum was seen some years. Nivalenol (NIV) was associated with F. poae and the HT-2 and T-2 toxins with F. langsethiae. Clear differences in mycotoxin contamination between different cereal crops and geographical regions were identified. The highest levels of DON and ZEN were found in spring wheat in Western Sweden. For NIV, HT-2 and T-2 toxins, the levels were highest in spring oats and spring barley. Regional differences were not detected for NIV, while HT-2 and T-2 toxins were associated with the northernmost region. We found that delayed harvest was strongly associated with increased levels of DON and ZEN in several crops. However, harvest date did not influence the levels of NIV or HT-2 and T-2 toxins. Our results suggest similar distribution patterns of DON and ZEN, in contrast to NIV and HT-2 and T-2 toxins, probably mirroring the differences in the ecology of the toxin-producing Fusarium species. Timely harvest is important to reduce the risk of DON and ZEN contamination, especially for fields with other risk factors.", "doi": "10.1007/s12550-022-00469-9", "pmid": "36279098", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10156870"}, {"db": "pii", "key": "10.1007/s12550-022-00469-9"}], "notes": [], "created": "2026-09-23T11:03:47.485Z", "modified": "2026-09-23T11:03:47.619Z"}]}