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Salmon farming in the future must navigate conflicting and shifting demands of sustainability, shifting feed prices, disease, and product quality. The industry needs to develop a flexible, integrated basis of knowledge for rapid response to new challenges. The Digital Salmon will be an ensemble of mathematical descriptions of salmon physiology, combining mathematics, high-dimensional data analysis, computer science and measurement technology with genomics and experimental biology into a concerted ...
Projects: GenoSysFat, DigiSal, SEEK tutorial for DigiSal, DigiSal-BT8121
Web page: http://tinyurl.com/digisal
Salmon farming in the future must navigate conflicting and shifting demands of sustainability, shifting feed prices, disease, and product quality. The industry needs to develop a flexible, integrated basis of knowledge for rapid response to new challenges. The Digital Salmon will be an ensemble of mathematical descriptions of salmon physiology, combining mathematics, high-dimensional data analysis, computer science and measurement technology with genomics and experimental biology into a concerted ...
Projects: GenoSysFat, DigiSal, SEEK tutorial for DigiSal, DigiSal-BT8121
Web page: http://tinyurl.com/digisal
Salmon farming in the future must navigate conflicting and shifting demands of sustainability, shifting feed prices, disease, and product quality. The industry needs to develop a flexible, integrated basis of knowledge for rapid response to new challenges. The Digital Salmon will be an ensemble of mathematical descriptions of salmon physiology, combining mathematics, high-dimensional data analysis, computer science and measurement technology with genomics and experimental biology into a concerted ...
Projects: GenoSysFat, DigiSal, SEEK tutorial for DigiSal, DigiSal-BT8121
Web page: http://tinyurl.com/digisal
Towards the Digital Salmon: From a reactive to a pre-emptive research strategy in aquaculture (DigiSal)
Salmon farming in the future must navigate conflicting and shifting demands of sustainability, shifting feed prices, disease, and product quality. The industry needs to develop a flexible, integrated basis of knowledge for rapid response to new challenges. Project DigiSal will lay the foundations for a Digital Salmon: an ensemble of mathematical descriptions of salmon physiology, combining ...
Programme: The Digital Salmon
Public web page: http://tinyurl.com/digisal
Organisms: Danio rerio, Salmo salar, Oncorhynchus mykiss
Salmon farmed on modern feeds contains less of the healthy, long-chain fatty acids (EPA and DHA) than before. Up until the turn of the millennium, farmed salmon were fed fish oil as a replacement for their omega-3 rich natural prey. However, fish oil is now a scarce resource, and more than half of the fat in modern feeds comes from plant oils that are inexpensive, but devoid of long-chain omega-3 fatty acids. How can we increase the omega-3 content of salmon on sustainable feeds?
One option is ...
Programme: The Digital Salmon
Public web page: http://tinyurl.com/genosysfat
Organisms: Danio rerio, Salmo salar, Oncorhynchus mykiss
This is a sandbox where DigiSal members can learn to use the SEEK.
Tutorial document: http://tinyurl.com/seek-ds17
The SEEK is a web interface to a database of research "assets" organised in a hierarchical "ISA structure" (investigation-study-assay) [1]. These are further organised into projects and programmes.
- Programme = Overarching research theme (The Digital Salmon)
- Project = Research grant (DigiSal, GenoSysFat)
- Investigation = a particular biological process, phenomenon or thing ...
Programme: The Digital Salmon
Public web page: http://www.nmbu.no/prosjekter/digisal
Organisms: Salmo salar
16S rRNA amplicon sequencing (Illumina MiSeq, V3-V4 region) to assess community structure.
Submitter: Jon Olav Vik
Assay type: Experimental Assay Type
Technology type: Next generation sequencing
Investigation: Omega-3 metabolism of salmon in relation to die...
Organisms: Salmo salar
SOPs: 16S metagenomic sequencing library preparations, DNA extraction from intestinal samples
Data files: Combined taxonomy table from freshwater and sal..., Feed switch 2015-09 Solbergstranda FASTA for gu..., Feed switch 2015-09 Solbergstranda gut microbio..., Feed switch 2016-01 Solbergstranda FASTA for gu..., Feed switch 2016-01 Solbergstranda gut microbio...
Snapshots: No snapshots
Targeted proteomics for peptides related to fatty acid metabolism. Aim: Check which of these proteins we are able to detect in this experiment.
Submitter: Jon Olav Vik
Assay type: Proteomics
Technology type: Technology Type
Investigation: Omega-3 metabolism of salmon in relation to die...
Organisms: Salmo salar
SOPs: No SOPs
Data files: Feed switch 2015-09 Solbergstranda proteomics o..., Feed switch 2015-09 Solbergstranda target prote...
Snapshots: No snapshots
From the "data accessibility" section of Life-stage associated remodeling of lipid metabolism regulation in Atlantic salmon. (Publication):
Supplementary files have been deposited to datadryad.org under the accession: https://doi.org/10.5061/dryad.j4h65. Raw RNA-Seq data have been deposited into European Nucleotide Archive (ENA) under the project Accession no. PRJEB24480.
Dead links 2022-06-29 (the Shiny ...
Submitter: Graceline Tina Kirubakaran
Assay type: RNA-seq
Technology type: Next generation sequencing
Investigation: Omega-3 metabolism of salmon in relation to die...
Organisms: Salmo salar
SOPs: Liver Slice protocol, RNASeq Template
Data files: Gene_information, Gut- CPM, Gut- Counts, Gut- FPKM, Lipid_Gene_List, Liver- CPM, Liver- Counts, Liver- FPKM, Metadata, Sample metadata
Snapshots: No snapshots
Record of weight, length and sex of fish sampled after feed switch between vegetable and marine oil, in September 2015 (freshwater) and January 2016 (seawater). Young fry arrived at Solbergstranda 2015-02-05 17:20.
Submitter: Thomas Harvey
Assay type: Experimental Assay Type
Technology type: Next generation sequencing
Investigation: Omega-3 metabolism of salmon in relation to die...
Organisms: Salmo salar
SOPs: Schedule for transition to seawater in GSF1, Ge...
Data files: Description of feeds for crossover feeding tria..., Feed switch 2015-09, 2016-01 Solbergstranda gro..., Metabolomics sampleID Old to New
Snapshots: No snapshots
An overview of RNA sequencing data generated in GenoSysFat (and a couple of others).
Source: Email from Simen Rød Sandve to Jon Olav Vik and Fabian Grammes 2017-02-10, titled "RNAseq generert i GSF".
This should be turned into separate RNAseq Assays when we can allocate people for it. Currently the following have records already:
Tissue panel for gene expression in ZF, Med, RT https://fairdomhub.org/assays/324
Tissue panel for gene expression in ZF,Med,RT- RNA sequencing https://fairdomhub.org/assays/395 ...
Submitter: Jon Olav Vik
Assay type: Experimental Assay Type
Technology type: Rna-seq
Investigation: Omega-3 metabolism of salmon in relation to die...
NB! The files here are the old version for the files in Lipidomics (Experimental Assay)
Lipidomic analysis by LC-MS of tissue samples from the GSF1 feed-switch experiment. Samples were analyzed at NTNU by Zdenka Bartosova and Per Bruheim.
There are two separate data files of lipid analysis in muscle and liver samples. Excel sheets contains both raw and normalised data of compounds abundance. Normalization to all compounds was used as a normalization method.
We have also performed a "normalization ...
Submitter: Jon Olav Vik
Assay type: Experimental Assay Type
Technology type: Liquid Chromatography Mass Spectrometry
Investigation: Omega-3 metabolism of salmon in relation to die...
Organisms: Salmo salar
SOPs: SOP_Lipid analysis
Data files: NEG FW_Liver_Tentative Compounds Identification, NEG FW_Muscle_Tentative Compounds Identification, NEG Fresh Water Liver, NEG Fresh Water Muscle, NEG SW_Liver_Tentative Compounds Identification, NEG SW_Muscle_Tentative Compounds Identification, NEG_Salt Water Liver, NEG_Salt Water Muscle, POS FW_Liver_Tentative Compounds Identification, POS FW_Muscle_Tentative Compounds Identification, POS_ Fresh Water Liver, POS_ Fresh water Muscle, POS_Normalization_experiment, POS_Salt Water Liver, POS_Salt Water Muscle, Preliminary principal component analysis, SW_Liver_Tentative Compounds Identification- Po..., SW_Muscle_Tentative Compounds Identification- P...
Snapshots: No snapshots
Lipidomic analysis by UPC2-MS of tissue samples from the GSF1 feed-switch experiment. Samples were analyzed at NTNU by Zdenka Bartosova and Per Bruheim.
There are three separate data files of lipid analysis in muscle, liver and gut tissue samples. Excel sheets contains both raw and normalised data of compounds abundance. Normalization to all compounds was used as a normalization method.
Columns: Compound 0.93_858.7669n Anova (p) 0,044998264 q Value 0,009417222 Max Fold Change 1,644961431 Maximum ...
Submitter: Zdenka Bartosova
Assay type: Experimental Assay Type
Technology type: Supercritical fluid chromatography - Mass spectrometry
Investigation: Omega-3 metabolism of salmon in relation to die...
Organisms: Salmo salar
SOPs: No SOPs
Data files: Lipid Class Quantitation- POS Gut SW+FW, Lipid Class Quantitation- POS Liver SW+FW, Lipid Class Quantitation- POS Muscle SW+FW, Lipid identification- POS Gut, Lipid identification- POS Liver, Lipid identification- POS Muscle, POS Gut tissue FW+SW, POS Liver tissue FW+SW, POS Muscle tissue FW+SW
Snapshots: No snapshots
Atlantic salmon (Salmo salar) is the most valuable farmed fish globally and there is much interest in optimizing its genetics and rearing conditions for growth and feed efficiency. Marine feed ingredients must be replaced to meet global demand, with challenges for fish health and sustainability. Metabolic models can address this by connecting genomes to metabolism, which converts nutrients in the feed to energy and biomass, but such models are currently not available for major aquaculture species ...
Creators: Maksim Zakhartsev, Filip Rotnes, Marie Gulla, Ove Oyas, Jesse van Dam, Maria Suarez Diez, Fabian Grammes, Wout van Helvoirt, Jasper Koehorst, Peter Schaap, Yang Jin, Liv Torunn Mydland, Arne Gjuvsland, Sandve Simen, Vitor Martins dos Santos, Jon Olav Vik
Submitter: Jon Olav Vik
Model type: Stoichiometric model
Model format: SBML
Environment: Not specified
Abstract (Expand)
Authors: Maksim Zakhartsev, Filip Rotnes, Marie Gulla, Ove Oyas, Jesse van Dam, Maria Suarez Diez, Fabian Grammes, Robert Hafthorsson, Wout van Helvoirt, Jasper Koehorst, Peter Schaap, Yang Jin, Liv Torunn Mydland, Arne Gjuvsland, Sandve Simen, Vitor Martins dos Santos, Jon Olav Vik
Date Published: 1st Jun 2022
Publication Type: Journal
DOI: 10.1371/journal.pcbi.1010194
Citation:
Abstract (Expand)
Authors: Knut Rudi, Inga Leena Angell, Phillip B. Pope, Jon Olav Vik, Simen Rød Sandve, Lars-Gustav Snipen
Date Published: 15th Jan 2018
Publication Type: Not specified
DOI: 10.1128/AEM.01974-17
Citation: Appl Environ Microbiol 84(2) : e01974-17
Abstract (Expand)
Author: R. C. Edgar
Date Published: 18th Aug 2013
Publication Type: Not specified
PubMed ID: 23955772
Citation: Nat Methods. 2013 Oct;10(10):996-8. doi: 10.1038/nmeth.2604. Epub 2013 Aug 18.
Abstract (Expand)
Author: R. C. Edgar
Date Published: 12th Aug 2010
Publication Type: Not specified
PubMed ID: 20709691
Citation: Bioinformatics. 2010 Oct 1;26(19):2460-1. doi: 10.1093/bioinformatics/btq461. Epub 2010 Aug 12.
Abstract
Authors: J. G. Caporaso, J. Kuczynski, J. Stombaugh, K. Bittinger, F. D. Bushman, E. K. Costello, N. Fierer, A. G. Pena, J. K. Goodrich, J. I. Gordon, G. A. Huttley, S. T. Kelley, D. Knights, J. E. Koenig, R. E. Ley, C. A. Lozupone, D. McDonald, B. D. Muegge, M. Pirrung, J. Reeder, J. R. Sevinsky, P. J. Turnbaugh, W. A. Walters, J. Widmann, T. Yatsunenko, J. Zaneveld, R. Knight
Date Published: 11th Apr 2010
Publication Type: Not specified
PubMed ID: 20383131
Citation: Nat Methods. 2010 May;7(5):335-6. doi: 10.1038/nmeth.f.303. Epub 2010 Apr 11.
Abstract (Expand)
Authors: A. Brazma, P. Hingamp, J. Quackenbush, G. Sherlock, P. Spellman, C. Stoeckert, J. Aach, W. Ansorge, C. A. Ball, H. C. Causton, T. Gaasterland, P. Glenisson, F. C. Holstege, I. F. Kim, V. Markowitz, J. C. Matese, H. Parkinson, A. Robinson, U. Sarkans, S. Schulze-Kremer, J. Stewart, R. Taylor, J. Vilo, M. Vingron
Date Published: 1st Dec 2001
Publication Type: Not specified
PubMed ID: 11726920
Citation: Nat Genet. 2001 Dec;29(4):365-71.
Abstract (Expand)
Authors: G. Gillard, T. N. Harvey, A. Gjuvsland, Y. Jin, M. Thomassen, S. Lien, M. Leaver, J. S. Torgersen, T. R. Hvidsten, J. O. Vik, S. R. Sandve
Date Published: No date defined
Publication Type: Not specified
PubMed ID: 29431879
Citation: Mol Ecol. 2018 Feb 12. doi: 10.1111/mec.14533.