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Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare

Overview of attention for article published in Genetics Selection Evolution, April 2016
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

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7 X users

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301 Mendeley
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Title
Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare
Published in
Genetics Selection Evolution, April 2016
DOI 10.1186/s12711-016-0217-x
Pubmed ID
Authors

Prashanth Suravajhala, Lisette J. A. Kogelman, Haja N. Kadarmideen

Abstract

In the past years, there has been a remarkable development of high-throughput omics (HTO) technologies such as genomics, epigenomics, transcriptomics, proteomics and metabolomics across all facets of biology. This has spearheaded the progress of the systems biology era, including applications on animal production and health traits. However, notwithstanding these new HTO technologies, there remains an emerging challenge in data analysis. On the one hand, different HTO technologies judged on their own merit are appropriate for the identification of disease-causing genes, biomarkers for prevention and drug targets for the treatment of diseases and for individualized genomic predictions of performance or disease risks. On the other hand, integration of multi-omic data and joint modelling and analyses are very powerful and accurate to understand the systems biology of healthy and sustainable production of animals. We present an overview of current and emerging HTO technologies each with a focus on their applications in animal and veterinary sciences before introducing an integrative systems genomics framework for analysing and integrating multi-omic data towards improved animal production, health and welfare. We conclude that there are big challenges in multi-omic data integration, modelling and systems-level analyses, particularly with the fast emerging HTO technologies. We highlight existing and emerging systems genomics approaches and discuss how they contribute to our understanding of the biology of complex traits or diseases and holistic improvement of production performance, disease resistance and welfare.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 301 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 1 <1%
United States 1 <1%
Unknown 299 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 65 22%
Student > Ph. D. Student 60 20%
Student > Master 31 10%
Student > Doctoral Student 22 7%
Student > Bachelor 19 6%
Other 52 17%
Unknown 52 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 103 34%
Biochemistry, Genetics and Molecular Biology 60 20%
Veterinary Science and Veterinary Medicine 16 5%
Computer Science 14 5%
Medicine and Dentistry 9 3%
Other 33 11%
Unknown 66 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 February 2023.
All research outputs
#6,997,226
of 25,373,627 outputs
Outputs from Genetics Selection Evolution
#218
of 822 outputs
Outputs of similar age
#92,413
of 312,739 outputs
Outputs of similar age from Genetics Selection Evolution
#4
of 15 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 822 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 73% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 312,739 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.