Best practice data life cycle approaches for the life sciences
- Griffin, Philippa, Khadake, Jyoti, LeMay, Kate, Lewis, Suzanna, Orchard, Sandra, Pask, Andrew, Pope, Bernard, Roessner, Ute, Russell, Keith, Seemann, Torsten, Treloar, Andrew, Tyagi, Sonika, Christiansen, Jeffrey, Dayalan, Saravanan, Gladman, Simon, Hangartner, Sandra, Hayden, Helen, Ho, William, Keeble-Gagnère, Gabriel, Korhonen, Pasi, Neish, Peter, Prestes, Priscilla, Richardson, Mark, Watson-Haigh, Nathan, Wyres, Kelly, Young, Neil, Schneider, Maria
- Authors: Griffin, Philippa , Khadake, Jyoti , LeMay, Kate , Lewis, Suzanna , Orchard, Sandra , Pask, Andrew , Pope, Bernard , Roessner, Ute , Russell, Keith , Seemann, Torsten , Treloar, Andrew , Tyagi, Sonika , Christiansen, Jeffrey , Dayalan, Saravanan , Gladman, Simon , Hangartner, Sandra , Hayden, Helen , Ho, William , Keeble-Gagnère, Gabriel , Korhonen, Pasi , Neish, Peter , Prestes, Priscilla , Richardson, Mark , Watson-Haigh, Nathan , Wyres, Kelly , Young, Neil , Schneider, Maria
- Date: 2018
- Type: Text , Journal article
- Relation: F1000 Research Vol. 6, no. (2018), p. 1-28
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- Description: Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a 'life cycle' view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on 'omics' datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices. © 2018 Griffin PC et al.
- Authors: Griffin, Philippa , Khadake, Jyoti , LeMay, Kate , Lewis, Suzanna , Orchard, Sandra , Pask, Andrew , Pope, Bernard , Roessner, Ute , Russell, Keith , Seemann, Torsten , Treloar, Andrew , Tyagi, Sonika , Christiansen, Jeffrey , Dayalan, Saravanan , Gladman, Simon , Hangartner, Sandra , Hayden, Helen , Ho, William , Keeble-Gagnère, Gabriel , Korhonen, Pasi , Neish, Peter , Prestes, Priscilla , Richardson, Mark , Watson-Haigh, Nathan , Wyres, Kelly , Young, Neil , Schneider, Maria
- Date: 2018
- Type: Text , Journal article
- Relation: F1000 Research Vol. 6, no. (2018), p. 1-28
- Full Text:
- Reviewed:
- Description: Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a 'life cycle' view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on 'omics' datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices. © 2018 Griffin PC et al.
Deguelin exerts potent nematocidal activity via the mitochondrial respiratory chain
- Preston, Sarah, Korhonen, Pasi, Mouchiroud, Laurent, Cornaglia, Matteo, McGee, Sean, Young, Neil, Davis, Rohan, Crawford, Simon, Nowell, Cameron, Ansell, Brendan, Fisher, Gillian, Andrews, Katherine, Chang, Bill, Gijs, Martin, Sternberg, Paul, Auwerx, Johan, Baell, Jonathan, Hofmann, Andreas, Jabbar, Abdul, Gasser, Robin
- Authors: Preston, Sarah , Korhonen, Pasi , Mouchiroud, Laurent , Cornaglia, Matteo , McGee, Sean , Young, Neil , Davis, Rohan , Crawford, Simon , Nowell, Cameron , Ansell, Brendan , Fisher, Gillian , Andrews, Katherine , Chang, Bill , Gijs, Martin , Sternberg, Paul , Auwerx, Johan , Baell, Jonathan , Hofmann, Andreas , Jabbar, Abdul , Gasser, Robin
- Date: 2017
- Type: Text , Journal article
- Relation: FASEB Journal Vol. 31, no. 10 (2017), p. 4515-4532
- Full Text: false
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- Description: As a result of limited classes of anthelmintics and an over-reliance on chemical control, there is a great need to discover new compounds to combat drug resistance in parasitic nematodes. Here, we show that deguelin, a plant-derived rotenoid, selectively and potently inhibits the motility and development of nematodes, which supports its potential as a lead candidate for drug development. Furthermore, we demonstrate that deguelin treatment significantly increases gene transcription that is associated with energy metabolism, particularly oxidative phosphorylation and mitoribosomal protein production before inhibiting motility. Mitochondrial tracking confirmed enhanced oxidative phosphorylation. In accordance, real-time measurements of oxidative phosphorylation in response to deguelin treatment demonstrated an immediate decrease in oxygen consumption in both parasitic (Haemonchus contortus) and free-living (Caenorhabditis elegans) nematodes. Consequently, we hypothesize that deguelin is exerting its toxic effect on nematodes as a modulator of oxidative phosphorylation. This study highlights the dynamic biologic response of multicellular organisms to deguelin perturbation. © FASEB.
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