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Institution

Griffith University

EducationBrisbane, Queensland, Australia
About: Griffith University is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Context (language use). The organization has 13830 authors who have published 49318 publications receiving 1420865 citations.


Papers
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Journal ArticleDOI
TL;DR: Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods.

7,090 citations

Journal ArticleDOI
Theo Vos, Abraham D. Flaxman1, Mohsen Naghavi1, Rafael Lozano1  +360 moreInstitutions (143)
TL;DR: Prevalence and severity of health loss were weakly correlated and age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010, but population growth and ageing have increased YLD numbers and crude rates over the past two decades.

7,021 citations

Journal ArticleDOI
Christopher J L Murray1, Theo Vos2, Rafael Lozano1, Mohsen Naghavi1  +366 moreInstitutions (141)
TL;DR: The results for 1990 and 2010 supersede all previously published Global Burden of Disease results and highlight the importance of understanding local burden of disease and setting goals and targets for the post-2015 agenda taking such patterns into account.

6,861 citations

Journal ArticleDOI
TL;DR: This protocol provides a workflow for genome-independent transcriptome analysis leveraging the Trinity platform and presents Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes.
Abstract: De novo assembly of RNA-seq data enables researchers to study transcriptomes without the need for a genome sequence; this approach can be usefully applied, for instance, in research on 'non-model organisms' of ecological and evolutionary importance, cancer samples or the microbiome. In this protocol we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms. We also present Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes. In the procedure, we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sourceforge.net. The run time of this protocol is highly dependent on the size and complexity of data to be analyzed. The example data set analyzed in the procedure detailed herein can be processed in less than 5 h.

6,369 citations

Journal ArticleDOI
Theo Vos1, Theo Vos2, Theo Vos3, Stephen S Lim  +2416 moreInstitutions (246)
TL;DR: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates, and there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries.

5,802 citations


Authors

Showing all 14162 results

NameH-indexPapersCitations
Rasmus Nielsen13555684898
Claudiu T. Supuran134197386850
Jeffrey D. Sachs13069286589
David Smith1292184100917
Michael R. Green12653757447
John J. McGrath120791124804
E. K. U. Gross119115475970
David M. Evans11663274420
Mike Clarke1131037164328
Wayne Hall111126075606
Patrick J. McGrath10768151940
Peter K. Smith10785549174
Erko Stackebrandt10663368201
Phyllis Butow10273137752
John Quackenbush9942767029
Network Information
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023162
2022572
20214,086
20203,879
20193,573
20183,318