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
- 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.
- 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.
Caucasian and south Asian men show equivalent improvements in surrogate biomarkers of cardiovascular and metabolic health following 6-weeks of supervised resistance training
- Knox, Allan, Sculthorpe, Nicholas, Grace, Fergal
- Authors: Knox, Allan , Sculthorpe, Nicholas , Grace, Fergal
- Date: 2018
- Type: Text , Journal article
- Relation: F1000Research Vol. 7, no. (2018), p. 1-16
- Full Text:
- Reviewed:
- Description: Background: The South Asian population have greater cardiovascular risk than their age-matched Caucasian counterparts, characterized by unfavorable biomarkers. South Asians may also be partially resistant to the pleiotropic benefits of physical activity on cardiovascular health. There is a current absence of studies that compare markers of cardio-metabolic health between Caucasians and South Asians employing resistance exercise. This study set out to compare the response in biomarkers of cardio-metabolic health in Caucasians and South Asians in response to resistance exercise. Methods: Caucasian (n=15, 25.5 ± 4.8 yrs) and South Asian (n=13, 25.4 ± 7.0 yrs) males completed a 6-week progressive resistance exercise protocol. Fasting blood glucose, insulin, and their product insulin resistance (HOMA-IR), triglycerides (TRIGS), low density lipoprotein (LDL), high density lipoprotein (HDL), total cholesterol (TC), vascular endothelial growth factor (VEGF), asymmetric dimythylarginine (ADMA), L-arginine (L-ARG) and C-reactive protein (CRP) were established at baseline and following resistance exercise. Results: There were significant improvements in fasting glucose, TC, LDL, HDL and VEGF in both groups following resistance exercise ( p<0.05, for all). No change was observed in insulin, HOMA-IR, TRIGS, ADMA, L-ARG following resistance exercise ( p>0.05, in both groups). CRP increased in the South Asian group ( p<0.05) but not the Caucasian group ( p>0.05) Conclusions: The cardio-metabolic response to resistance exercise is comparable in young Caucasian and South Asian males though inflammatory response to exercise may be prolonged in South Asians.
- Authors: Knox, Allan , Sculthorpe, Nicholas , Grace, Fergal
- Date: 2018
- Type: Text , Journal article
- Relation: F1000Research Vol. 7, no. (2018), p. 1-16
- Full Text:
- Reviewed:
- Description: Background: The South Asian population have greater cardiovascular risk than their age-matched Caucasian counterparts, characterized by unfavorable biomarkers. South Asians may also be partially resistant to the pleiotropic benefits of physical activity on cardiovascular health. There is a current absence of studies that compare markers of cardio-metabolic health between Caucasians and South Asians employing resistance exercise. This study set out to compare the response in biomarkers of cardio-metabolic health in Caucasians and South Asians in response to resistance exercise. Methods: Caucasian (n=15, 25.5 ± 4.8 yrs) and South Asian (n=13, 25.4 ± 7.0 yrs) males completed a 6-week progressive resistance exercise protocol. Fasting blood glucose, insulin, and their product insulin resistance (HOMA-IR), triglycerides (TRIGS), low density lipoprotein (LDL), high density lipoprotein (HDL), total cholesterol (TC), vascular endothelial growth factor (VEGF), asymmetric dimythylarginine (ADMA), L-arginine (L-ARG) and C-reactive protein (CRP) were established at baseline and following resistance exercise. Results: There were significant improvements in fasting glucose, TC, LDL, HDL and VEGF in both groups following resistance exercise ( p<0.05, for all). No change was observed in insulin, HOMA-IR, TRIGS, ADMA, L-ARG following resistance exercise ( p>0.05, in both groups). CRP increased in the South Asian group ( p<0.05) but not the Caucasian group ( p>0.05) Conclusions: The cardio-metabolic response to resistance exercise is comparable in young Caucasian and South Asian males though inflammatory response to exercise may be prolonged in South Asians.
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