Arbeidsoppgaver:
- Underdirektør for Avdeling for IT i Forskning ved USIT, UiO
- Leder av sekretariatet for de strategiske koordineringsgruppene for IT ved UiO
- Deltager i sekretariatet for Forskningsinfrastrukturutvalget
- Deltaker fra UiO i Fagråd og Tjenesteråd for Forskning hos UNIT
- Ansvarlig for USITs leveranser for TSD, Uninett Sigma2 AS, CERN NDGF-Tier-1, MusemsIT, Instrumentnett, Fairdata@UiO, Forskerplattformen med mer.
Diverse:
Bakgrunn:
- FitSM Foundations, 2020
- Etterutdanning på Inst for Informatikk, UiO, i IT-ledelse, IT-arkitektur, IT-governance og ledelse av komplese IT-systemer (ITLED; 4010,4021,4260,4280)
- ITIL Foundations, 2013
- High Throughput Sequencing / Next Generation Sequencing CCB, UIO/OUS
- Microarray design og analyse, CMBN og CCB, UIO/OUS
- PhD Bioinformatikk, CMBN OUS/ UIO
- Gründerskolen
- Cand Scient Informatikk, UIO
- Befalsskolen for Kavaleriet, Oppklaringslinjen
Publikasjoner
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Aarestrup, FM; Albeyatti, A; Armitage, W; Auffray, C; Augello, L & Balling, Rudi
[Vis alle 52 forfattere av denne artikkelen]
(2020).
Towards a European health research and innovation cloud (HRIC).
Genome Medicine.
ISSN 1756-994X.
12(18).
doi:
10.1186/s13073-020-0713-z.
Fulltekst i vitenarkiv
Vis sammendrag
The European Union (EU) initiative on the Digital Transformation of Health and Care (Digicare) aims to provide the conditions necessary for building a secure, flexible, and decentralized digital health infrastructure. Creating a European Health Research and Innovation Cloud (HRIC) within this environment should enable data sharing and analysis for health research across the EU, in compliance with data protection legislation while preserving the full trust of the participants. Such a HRIC should learn from and build on existing data infrastructures, integrate best practices, and focus on the concrete needs of the community in terms of technologies, governance, management, regulation, and ethics requirements. Here, we describe the vision and expected benefits of digital data sharing in health research activities and present a roadmap that fosters the opportunities while answering the challenges of implementing a HRIC. For this, we put forward five specific recommendations and action points to ensure that a European HRIC: i) is built on established standards and guidelines, providing cloud technologies through an open and decentralized infrastructure; ii) is developed and certified to the highest standards of interoperability and data security that can be trusted by all stakeholders; iii) is supported by a robust ethical and legal framework that is compliant with the EU General Data Protection Regulation (GDPR); iv) establishes a proper environment for the training of new generations of data and medical scientists; and v) stimulates research and innovation in transnational collaborations through public and private initiatives and partnerships funded by the EU through Horizon 2020 and Horizon Europe.
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Lorenz, Susanne; Barøy, Tale; Sun, Jinchang; Nome, Torfinn; Vodak, Daniel & Bryne, Jan Christian
[Vis alle 21 forfattere av denne artikkelen]
(2016).
Unscrambling the genomic chaos of osteosarcoma reveals extensive transcript fusion, recurrent rearrangements and frequent novel TP53 aberrations.
OncoTarget.
ISSN 1949-2553.
7(5),
s. 5273–5288.
doi:
10.18632/oncotarget.6567.
Vis sammendrag
In contrast to many other sarcoma subtypes, the chaotic karyotypes of osteosarcoma have precluded the identification of pathognomonic translocations. We here report hundreds of genomic rearrangements in osteosarcoma cell lines, showing clear characteristics of microhomology-mediated break-induced replication (MMBIR) and end-joining repair (MMEJ) mechanisms. However, at RNA level, the majority of the fused transcripts did not correspond to genomic rearrangements, suggesting the involvement of trans-splicing, which was further supported by typical trans-splicing characteristics. By combining genomic and transcriptomic analysis, certain recurrent rearrangements were identified and further validated in patient biopsies, including a PMP22-ELOVL5 gene fusion, genomic structural variations affecting RB1, MTAP/CDKN2A and MDM2, and, most frequently, rearrangements involving TP53. Most cell lines (7/11) and a large fraction of tumor samples (10/25) showed TP53 rearrangements, in addition to somatic point mutations (6 patient samples, 1 cell line) and MDM2 amplifications (2 patient samples, 2 cell lines). The resulting inactivation of p53 was demonstrated by a deficiency of the radiation-induced DNA damage response. Thus, TP53 rearrangements are the major mechanism of p53 inactivation in osteosarcoma. Together with active MMBIR and MMEJ, this inactivation probably contributes to the exceptional chromosomal instability in these tumors. Although rampant rearrangements appear to be a phenotype of osteosarcomas, we demonstrate that among the huge number of probable passenger rearrangements, specific recurrent, possibly oncogenic, events are present. For the first time the genomic chaos of osteosarcoma is characterized so thoroughly and delivered new insights in mechanisms involved in osteosarcoma development and may contribute to new diagnostic and therapeutic strategies.
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Celestino, Ricardo; Sigstad, Eva; Løvf, Marthe; Thomassen, Gard O Sundby; Kotanska-Grøholt, Krystyna & Jørgensen, Lars Hilmar
[Vis alle 13 forfattere av denne artikkelen]
(2012).
Survey of 548 oncogenic fusion transcripts in thyroid tumors supports the importance of the already established thyroid fusions genes.
Genes, Chromosomes and Cancer.
ISSN 1045-2257.
51(12),
s. 1154–1164.
doi:
10.1002/gcc.22003.
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Løvf, Marthe; Thomassen, Gard O Sundby; Bakken, Anne Cathrine; Celestino, Ricardo; Fioretos, Thoas & Lind, Guro Elisabeth
[Vis alle 8 forfattere av denne artikkelen]
(2011).
Fusion Gene Microarray Reveals Cancer Type-Specificity Among Fusion Genes.
Genes, Chromosomes and Cancer.
ISSN 1045-2257.
50(5),
s. 348–357.
doi:
10.1002/gcc.20860.
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Thomassen, Gard O Sundby; Sneve, Ragnhild; Rowe, Alexander D.; Booth, James; Lindvall, Jessica M. & Lagesen, Karin
[Vis alle 9 forfattere av denne artikkelen]
(2010).
Tiling Array Analysis of UV Treated Escherichia coli Predicts Novel Differentially Expressed Small Peptides.
PLOS ONE.
ISSN 1932-6203.
5(12).
doi:
10.1371/journal.pone.0015356.
Fulltekst i vitenarkiv
Vis sammendrag
Background
Despite comprehensive investigation, the Escherichia coli SOS response system is not yet fully understood. We have applied custom designed whole genome tiling arrays to measure UV invoked transcriptional changes in E. coli. This study provides a more complete insight into the transcriptome and the UV irradiation response of this microorganism.
Results
We detected a number of novel differentially expressed transcripts in addition to the expected SOS response genes (such as sulA, recN, uvrA, lexA, umuC and umuD) in the UV treated cells. Several of the differentially expressed transcripts might play important roles in regulation of the cellular response to UV damage. We have predicted 23 novel small peptides from our set of detected non-gene transcripts. Further, three of the predicted peptides were cloned into protein expression vectors to test the biological activity. All three constructs expressed the predicted peptides, in which two of them were highly toxic to the cell. Additionally, a remarkably high overlap with previously in-silico predicted non-coding RNAs (ncRNAs) was detected. Generally we detected a far higher transcriptional activity than the annotation suggests, and these findings correspond with previous transcription mappings from E. coli and other organisms.
Conclusions
Here we demonstrate that the E. coli transcriptome consists of far more transcripts than the present annotation suggests, of which many transcripts seem important to the bacterial stress response. Sequence alignment of promoter regions suggest novel regulatory consensus sequences for some of the upregulated genes. Finally, several of the novel transcripts identified in this study encode putative small peptides, which are biologically active.
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Thomassen, Gard O Sundby; Rowe, Alexander D.; Lagesen, Karin; Lindvall, Jessica Margareta & Rognes, Torbjørn
(2009).
Custom Design and Analysis of High-Density Oligonucleotide Bacterial Tiling Microarrays.
PLOS ONE.
ISSN 1932-6203.
4(6).
Fulltekst i vitenarkiv
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Thomassen, Gard O. S.; Rosok, Oystein & Rognes, Torbjørn
(2006).
Computational prediction of microRNAs encoded in viral and other genomes.
Journal of Biomedicine and Biotechnology.
ISSN 1110-7243.
Fulltekst i vitenarkiv
Se alle arbeider i Cristin
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Stangeland, Elin; Soligard, Lars; Thomassen, Gard O Sundby; Bianchini, Federico & Bösl, Korbinian
(2020).
Data Management Planning workshop for Life Science Projects.
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Stansberg, Christine; Willassen, Nils P; Thomassen, Gard O Sundby; Hovig, Johannes Eivind & Jonassen, Inge
(2020).
How open databases turn out to be crucial in the fight against Covid-19.
NBS-nytt.
ISSN 0801-3535.
4,
s. 38–43.
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Øvrelid, Egil; Bygstad, Bendik & Thomassen, Gard O Sundby
(2020).
Tsd: A Research Platform For Sensitive Data.
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Øvrelid, Egil; Bygstad, Bendik & Thomassen, Gard O Sundby
(2020).
TSD: A GENERATIVE RESEARCH PLATFORM IN THE AGE OF THE PANDEMICS .
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Eide, Hans A; Fotland, Margaret Louise; Kvale, Live Håndlykken; Stangeland, Elin; Stølen, Svein & Thomassen, Gard O Sundby
[Vis alle 7 forfattere av denne artikkelen]
(2015).
Sharing and Storing Research Data
A 4-level model of the Data flow.
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Nakken, Sigve; Vodák, Daniel; Fournous, Ghislain; Thomassen, Gard O Sundby & Hovig, Johannes Eivind
(2013).
Big challenges in personalized cancer medicine.
META.
ISSN 1890-1956.
s. 8–12.
Vis sammendrag
DNA sequencing technology has recently made huge leaps, making it possible to characterize all genetic changes in any cancer. Robust bioinformatics solutions for both safe data storage, as well as processing, interpretation, and sharing, are critically important before this layer of patient information could be useful to the clinic. Here, we will provide an introduction to the field of bioinformatics in personalized cancer medicine, and specifically highlight the need for computation and storage resources at a local and national level.
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Eike, Morten Christoph; Lærum, Hallvard; Hughes, Timothy; Håndstad, Tony; Bremer, Sara & Bergan, Stein
[Vis alle 10 forfattere av denne artikkelen]
(2012).
GenAP: a platform for clinical genetic analysis of high-throughput sequencing data.
Vis sammendrag
The introduction of high-throughput sequencing (HTS) into clinical practice poses great challenges in terms of analytic resources, integration and data security. The project Norwegian clinical genetic Analysis Platform (genAP) was initiated as a response to these challenges, aiming to establish a centralised infrastructure for secure storage and analysis of human sequencing data, with possibilities for disseminated clinical use. GenAP is a collaborative project between Oslo University Hospital and the University of Oslo, with implementation of the system in a high-performance computing environment. As part of this project, we are in the process of establishing pilot HTS pipelines for a set of clinical packages, each with a defined set of targeted genes. The pilots cover diagnostic, prognostic and pharmacogenetic areas, including cardiomyopathies, breast cancer and tacrolimus dosage, respectively. Initially, the pipelines involve data for a limited set of candidate genes, but the system will be scalable to exome and whole-genome data for a large number of patients. To reduce the workload associated with manual analysis, we have sought to achieve a high degree of automation, including variant annotation and quality control, filtering and prioritisation based on public resources, identification of previously classified variants, and standardisation of report information structure for integration with existing medical journal systems. The pilot phase includes comparing the performance of HTS to conventional methods, building a database of genetic variants adapted to our patient populations and real-world testing using collaborating clinicians. The experiences gained will be used to expand to other clinical packages, and the ultimate goal is to introduce the system in the clinic. Complementing the genetic, bioinformatic and clinical issues, the project also addresses legal, ethical and organizational issues encountered when HTS is deployed in large scale clinical decision making.
This presentation will demonstrate the overall architecture of our system and present initial experiences with the pilot systems.
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Eike, Morten Christoph; Lærum, Hallvard; Hughes, Timothy; Bremer, Sara; Bergan, Stein & Thomassen, Gard O Sundby
[Vis alle 9 forfattere av denne artikkelen]
(2012).
A national platform for clinical genetic analysis of high-throughput sequencing data in Norway.
Vis sammendrag
The introduction of high-throughput sequencing (HTS) into clinical practice poses great challenges in terms of analytic resources, integration and data security. The project Norwegian clinical genetic Analysis Platform (genAP) was initiated as a response to these challenges, aiming to establish a centralised infrastructure for secure storage and analysis of human sequencing data that allows for disseminated clinical use. GenAP is a collaborative project between Oslo University Hospital and the University of Oslo, with implementation of the system in an established high-performance computing environment. As part of this project, we are in the process of establishing pilot HTS pipelines for a set of clinical packages, each with a defined set of targeted genes. The pilots cover diagnostic, prognostic and pharmacogenetic areas, including cardiomyopathies, breast cancer and tacrolimus dosage, respectively. Initially, the pipelines involve targeted capture and resequencing, but the system will be scalable to exome and genome data for a large number of patients. To reduce the workload associated with manual analysis, we have sought to achieve a high degree of automation, including variant annotation and quality control, filtering based on public resources, identification of previously classified variants, and standardization of report information structure for integration with existing patient journal systems. The pilot phase includes comparing the performance of HTS to conventional methods, building a database of genetic variants adapted to our patient populations and real-world testing using collaborating clinicians. The experiences gained will be used to expand to other clinical packages, and the ultimate goal is to introduce the pipelines for widespread use in the clinic. Complementing the genetic, bioinformatic and clinical issues, the project also addresses legal, ethical and organizational issues encountered when HTS is deployed in large scale clinical decision making.
This presentation will demonstrate the overall architecture of our system and present initial experiences with the pilot systems.
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Løvf, Marthe; Thomassen, Gard O Sundby; Lind, Guro Elisabeth; Lothe, Ragnhild A & Skotheim, Rolf Inge
(2010).
An oligo microarray design for detection of known and putative oncogenic fusion transcripts.
European Journal of Cancer.
ISSN 0959-8049.
8(5),
s. 199–199.
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Skotheim, Rolf Inge; Eken, Marthe; Thomassen, Gard O Sundby; Lind, Guro Elisabeth & Lothe, Ragnhild A
(2009).
A universal assay for detection of oncogenic fusion transcripts by oligo microarray analysis.
European Journal of Cancer.
ISSN 0959-8049.
7(2),
s. 147–148.
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Thomassen, Gard O Sundby & Rognes, Torbjørn
(2010).
Design, analysis and applications of custom high-density oligonucleotide microarrays.
Unipub forlag.
ISSN 978-82-8072-495-3.
Se alle arbeider i Cristin
Publisert
20. des. 2012 11:20
- Sist endret
9. juni 2023 12:09