AB3ACBS-2016 Special Guest
Professor Terri Attwood
Currently, I’m Professor of Bioinformatics at the University of Manchester. Research interests in protein sequence analysis and protein family classification led to the development of databases like PRINTS & InterPro, and software tools like CINEMA & Utopia; more recently, an interest in the area of semantic integration of research data with scholarly publications led to the creation of Utopia Documents and launch of ‘The Semantic Biochemical Journal’ with Portland Press. When not involved in research, I’m a keen educator and trainer: I wrote the first introductory bioinformatics text-book - my 3rd book was published this summer. In 2012, I led the initiative to create the GOBLET Foundation (the Global Organisation for Bioinformatics Learning, Education and Training), and I currently lead the development of ELIXIR's Training e-Support System, TeSS.
The Road to Utopia: challenges in linking literature & research data
This presentation describes a personal journey in which a life-time preoccupation with protein sequences anddatabases led to the unlikely development of Utopia Documents, a 'smart' PDF reader (http://getutopia.com), and a pioneering project to create the Semantic Biochemical Journal (http://www.biochemj.org/bj/semantic_faq.htm). Our quest was motivated by a desire to better link data and/or software tools with scientific articles, to blur the boundaries between databases and papers. During an era of ‘big data’, when more articles are being published and more data are being produced than humans can readily assimilate, Utopia Documents offers a new paradigm for extracting nuggets of information from the barrage of published scientific information that now assaults us every day. Examples will be given from the Lazarus project, in which Utopia harnesses the power of the ‘crowd’ to capture asserted facts and relationships automatically, as a simple side-effect of reading and interacting with scientific articles.
AB3ACBS-2016 Invited Speakers
Professor Simon Ho
Simon is a Professor of Molecular Evolution at the University of Sydney, where leads the Molecular Ecology, Evolution, and Phylogenetics Lab. His research interests include phylogenetic methods, evolutionary models, and molecular clocks. The focus of Simon’s recent work has been on describing patterns of evolutionary rate variation across genomes and on phylogenomic estimation of evolutionary timescales.
Simon received his PhD in 2006 (University of Oxford), then did postdoctoral work at Oxford and the Australian National University before joining the University of Sydney in 2010. He has received a number of awards for his work, including the 2015 Edgeworth David Medal, 2014 NSW Young Tall Poppy of the Year, and 2015 Eureka Prize for Outstanding Early Career Researcher.
Phylogenomic analysis and molecular evolutionary clocks
Evolutionary timescales can be estimated from DNA sequence data using the molecular clock, a statistical model that describes the behaviour of evolutionary rates among organisms. Although originally based on the assumption of rate constancy among lineages, molecular clocks now include ‘relaxed’ variants that are able to accommodate heterogeneous rates. These have played an important role in resolving evolutionary rates and timescales across the Tree of Life.
Genome-scale data offer exciting opportunities for improving our understanding of molecular evolution and refining our estimates of evolutionary timescales. A large number of genome projects are in the pipeline, promising to produce a flood of data that will be useful for evolutionary inferences. However, they also bring considerable computational and analytical challenges. I describe some of the approaches that have been used to estimate evolutionary timescales from genome-scale data, drawing on several recent examples from my work. I also explain how phylogenetic analysis can provide insight into molecular evolutionary dynamics, with particular reference to the “pacemaker” models of genome evolution.
Associate Professor Ute Roessner
A/Prof Ute Roessner has obtained her PhD in Plant Biochemistry at the Max-Planck-Institute for Molecular Plant Physiology in Germany, where she developed novel GC-MS based methods to analyse metabolites in plants. With the combination of small molecule analytics and sophisticated bioinformatics and statistics the field of metabolomics was born which today is an important tool in biological sciences, systems biology and biomarker discovery. In 2003 she moved to Australia where she established a GC-MS and LC-MS based metabolomics platform as part of the Australian Centre for Plant Functional Genomics (www.acpfg.com.au). Between 2011 and 2014 she led the ACPFG node at the School of BioSciences, The University of Melbourne. Also, in 2007 Ute became involved in the setup of the government funded Metabolomics Australia (MA, www.metabolomics.com.au), a member of BioPlatforms Australia (www.bioplatforms.com.au) and now leads the MA node at the School of BioSciences, The University of Melbourne. In 2013 she was awarded a prestigious ARC Future Fellowship which aims to identify novel mechanisms of salinity tolerance in barley by spatial analysis of metabolites and lipids using Imaging Mass Spectrometry.
Metabolomics – an important piece in the ‘omics puzzle.
Metabolomics is an emerging field in the suite of ‘omics’ approaches for Systems Biology. The goal of metabolomics is to detect the presence of all small-molecules in a biological sample. This presents a significant challenge due to their chemical diversity and large concentration ranges requiring the application of complementary analytical approaches, including mass spectrometry coupled to chromatography, to increase the coverage of metabolites analysed. The array of analytical approaches will be summarised and their application in biological systems demonstrated with examples from our research programs. The presentation will focus on computational and statistical challenges metabolomics researchers are facing and will highlight some of the workflows and tools currently available for conventional orthogonal metabolomics analyses. In addition, an outlook on novel techniques for spatial tissue metabolite and lipid analysis will be presented, again with a focus on the computational challenge of comparative highly dimensional mass spectrometry tissue imaging analyses.
Assistant Professor Kate L. Hertweck
Kate L. Hertweck is an Assistant Professor in the Department of Biology at the University of Texas at Tyler specializing in genomics, bioinformatics, and evolutionary biology. She received her B.S. in Biology from Western Kentucky University and Ph.D. in Biology from University of Missouri, where she studied systematics and evolution in plants. She traded in her lab coat and field boots for full-time computational work by joining the National Evolutionary Synthesis Center (NESCent, at Duke University) as a postdoctoral fellow, where she had the opportunity to refine her skills in data analysis and computational biology. Her current research spans the full breadth of genomic analysis, from populations through deep evolutionary time and humans to non-model systems.
Plant systematics to cancer biology: genome-wide patterns and organismal evolution
Obtaining data is no longer the limiting factor in genomic research. While such data offer incredible promise, we are faced with increasing demands to store, manage, and extract meaning from available genomes. Reproducible science skills allow researchers to meet these needs as well as associate genome-wide data with organismal information, like life history traits and phenotypes. Bioinformatics, therefore, offers unprecedented opportunities to reveal patterns in both evolutionary history and future trajectories of organisms. Three seemingly disparate but complementary examples will highlight the union of genome and organismal evolution: molecular systematics in monocotyledonous plants, transposable element proliferation in experimentally evolved Drosophila, and somatic mutation in cancer biology. Projects integrating reproducible science with evolutionary biology provide invaluable opportunities for student training, preparing the next generation of scientists to synthesize patterns across genomes.
Dr Matt RiTchie
Dr Matt Ritchie is a statistical bioinformatician at the WEHI who develops analysis methods for RNA-seq data and other genome-wide approaches. His lab is currently exploring data from single cell technologies and long-read sequencing platforms to study transcription and methylation. He is a keen developer of open-source R/Bioconductor software for genomic analysis.
Tools for comparing and combining RNA-seq results
In this talk I will discuss our recent efforts in RNA-mixology to design more realistic control experiments for benchmarking different RNA-seq analysis methods and protocols. I will also introduce new software for combining results from different gene set testing methods (EGSEA) and delivering results from RNA-seq analyses in a more interactive way (Glimma).
Dr Andreas Schreiber
Andreas heads the bioinformatics group at the Centre for Cancer Biology’s ACRF Cancer Genomics Facility. The group focuses on applied bioinformatics of high throughput experiments, ranging from analysis of transcriptomic, microarray or RNASeq data, gene regulation studies using ChIP and CLIPSeq, to the search for disease-associated point and structural mutations of the human genome. Embedded in the South Australian Department of Health, the facility and the bioinformatics group are closely involved with the implementation of NGS technologies into a diagnostic setting.
Andreas obtained a BSc and MSc from the University of Melbourne, followed by a PhD in theoretical nuclear/particle physics from the University of Adelaide in 1990. He completed postdocs in the Netherlands, Switzerland and Canada before returning to Australia on an ARC Research Fellowship. In 2002 he switched fields to Bioinformatics by joining the Australian Centre for Plant Functional Genomics at the Waite Campus of the University of Adelaide.
He has been with the CCB since 2011.
Taking the confusion out of fusions: Structural mutation detection in cancer research and diagnostics
Next generation sequencing (NGS) has become a standard tool in cancer research. Used with DNA, NGS has enabled e.g. genome-wide identification of point mutations, structural rearrangements and transcription factor binding sites, while with RNA one can measure transcriptome-scale gene expression, splicing variation and discover deleterious fusion genes. From a bioinformatic perspective, mutation detection algorithms have matured enough to permit widespread uptake of NGS into diagnostic laboratories, including in our own institution. With RNASeq, however, uptake into a diagnostic setting is still stymied by changing wet-lab as well as bioinformatic techniques.
In this talk, I will describe how developments in the wet-lab have caused us to reassess the bioinformatics of gene fusion detection and I will report on our efforts to improve the reliability of NGS gene fusion detection sufficiently to permit its uptake into diagnostics.
Dr Nouri Ben Zakour
Dr Nouri Ben Zakour is a principal research scientist in microbial genomics at the Westmead Institute for Medical Research in Sydney. Prior to recently joining WIMR, she received her PhD in bioinformatics from the University of Rennes (France) and further specialised in pathogenomics at the University of Edinburgh and the University of Queensland. Her research currently focuses on the evolutionary epidemiology of established and emerging multi-drug resistant clinical and veterinary bacterial pathogens. In collaboration with global research, clinical and industrial leaders, she also aims at bringing microbial genomics closer with hospitals and veterinary settings by delivering applied solutions to outbreak tracking, antibiotic resistance surveillance and therapeutic targets identification.
Evolutionary epidemiology of successful bacterial pathogens
The last 10 years have witnessed next-generation whole genome sequencing (WGS) drastically transform the fields of genomics, microbiology and epidemiology, among others. In this talk, I will explore how WGS provides invaluable insights into the pathogenesis, evolution and global dissemination of multi-drug resistant pathogens and helps us understand what it takes to be a successful bacterial pathogen. I will also touch on some of the new perspectives that this ongoing “genomics revolution” opens up for hospitals and clinical settings.