The University of South Australia (UniSA)

Australia

In 2016, the University of South Australia (UniSA) celebrates its 25th birthday. We are a young university, continuing to set the pace for world-class research and solutions for a changing world. As Australia’s University of Enterprise, the spirit of enterprise runs through everything we do.

Our research is inspired by challenges and opportunities, partnered with end-users and communities, and underpinned by excellence. We work collaboratively with our partners right from the conception of a research idea, allowing our research directions to be shaped by their opportunities and challenges.

UniSA’s strong commitment to cutting-edge research and engagement with industry has been well recognised, with 97 per cent of our research rated at or above world-class standard (Excellence for Research in Australia 2015). This is an impressive result for a young university, and we are proud of our achievements.

Our research culture is vibrant, outward facing and responsive. We pride ourselves on our capacity to create interdisciplinary teams that can tackle significant real-world challenges, and our researchers strive to make a difference outside the world of academe.

We are globally connected and engaged, helping solve the problems of industry and the professions. Our teaching is industry-informed, our research inventive and adventurous, and focused on creating impact. Through our research, we create knowledge that is central to global economic and social prosperity.

University of South Australia retains sole responsibility for content © 2016 University of South Australia.

1 August 2017 - 31 July 2018

Region: Global
Subject/journal group: All

The table to the right includes counts of all research outputs for The University of South Australia (UniSA) published between 1 August 2017 - 31 July 2018 which are tracked by the Nature Index.

Hover over the donut graph to view the FC output for each subject. Below, the same research outputs are grouped by subject. Click on the subject to drill-down into a list of articles organized by journal, and then by title.

Note: Articles may be assigned to more than one subject area.

AC FC
57 10.10

Outputs by subject (FC)

Subject AC FC
Earth & Environmental Sciences 12 2.55
Chemistry 13 4.29
3 0.42
3 2.03
2 0.68
1 1
1 0
3 0.16
Life Sciences 24 2.43
Physical Sciences 17 1.69

Highlight of the month

Statistical standoff for estimating shared genes

© enot-poloskun/Getty

© enot-poloskun/Getty

A statistical method that uses individual-level data to estimate the contribution of genes to complex traits is better at identifying shared genetic underpinnings between traits or diseases than an alternative method that relies on summary statistics.

A team led by researchers from the University of South Australia compared two advanced techniques for calculating genetic correlations between two traits, based on studies of thousands of single-letter DNA differences scattered throughout the genome.

Using computer simulations and real data from a large study of schizophrenia, they showed that a method called linkage disequilibrium score regression — although less computationally intensive because it uses combined metadata to pool the findings of large numbers of studies — produces less accurate results than ‘genomic restricted maximum likelihood’, which relies on individual-level genotype data.

Only the latter technique revealed a negative relationship between regulatory regions of DNA affecting the development of schizophrenia, and height.

Supported content

  1. American Journal of Human Genetics 102, 1185–1194 (2018). doi: 10.1016/j.ajhg.2018.03.021

View the article on the Nature Index

See more research highlights from The University of South Australia (UniSA)

More research highlights from The University of South Australia (UniSA)

1 August 2017 - 31 July 2018

International vs. domestic collaboration by FC

  • 68.05% Domestic
  • 31.95% International

Note: Hover over the graph to view the percentage of collaboration.

Note: Collaboration is determined by the fractional count (FC), which is listed in parentheses.

Affiliated joint institutions and consortia

Return to institution outputs