[{"id":156,"title":"WEBINAR: Making sense of phosphoproteomics data with Phosphomatics","url":"https://staging.dresa.org.au/materials/webinar-making-sense-of-phosphoproteomics-data-with-phosphomatics.json","description":"This record includes training materials associated with the Australian BioCommons webinar  ‘Making sense of phosphoproteomics data with Phosphomatics’. This webinar took place on 2 June 2021.\n\nMass spectrometry-based phosphoproteomics is one of the most powerful tools available for investigating the detailed molecular events that occur in response to cellular stimuli. Experiments can routinely detect and quantify thousands of phosphorylated peptides, and interpreting this data, and extracting biological meaning, remains challenging. \n\nThis webinar provides an overview of the phosphoproteomics data analysis website, Phosphomatics, that incorporates a suite of tools and resources for statistical and functional analysis that aim to simplify the process of extracting meaningful insights from experimental results.\n\nPhosphomatics can natively import search and quantitation results from major search engines including MaxQuant and Proteome Discoverer and employs intuitive ‘wizards’ to guide users through data preprocessing routines such as filtering, normalization and transformation. A graphical platform of interactive univariate and multivariate analysis features is provided that allow subgroups of the uploaded data containing phosphosites of statistical interest to be created and interrogated through further functional analysis. A range of databases have been integrated that, for example, provide ligand and inhibitor information for key proteins or highlight key modification sites known to be involved in functional state regulation. At each step, published literature is natively incorporated along with a ‘bibliography builder’ that allows references of interest to be assembled and exported in various formats. Taken together, these expanded features aim to provide a ‘one-stop-shop’ for phosphoproteomics data analysis.\n\nThe webinar is followed by a short Q\u0026amp;A session.\n\nMaterials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.\n\n \n\nFiles and materials included in this record:\n\n\n\t\n\tEvent metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.\n\t\n\t\n\tIndex of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.\n\t\n\t\n\tPhosphomatics -slides  (PDF and PPTX): Slides used in the presentation\n\t\n\n\n \n\nMaterials shared elsewhere:\n\nA recording of the webinar is available on the Australian BioCommons YouTube Channel:\n\nhttps://youtu.be/_WpeL5t2DSI","doi":"10.5281/zenodo.5126083","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":157,"title":"WEBINAR: Getting started with deep learning","url":"https://staging.dresa.org.au/materials/webinar-getting-started-with-deep-learning.json","description":"This record includes training materials associated with the Australian BioCommons webinar  ‘Getting started with deep learning’. This webinar took place on 21 July 2021.\n\nAre you wondering what deep learning is and how it might be useful in your research? This high level overview introduces deep learning ‘in a nutshell’ and provides tips on which concepts and skills you will need to know to build a deep learning application. The presentation also provides pointers to various resources you can use to get started in deep learning.\n\nThe webinar is followed by a short Q\u0026amp;A session.\n\nMaterials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event.\n\nFiles and materials included in this record:\n\n\n\t\n\tEvent metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.\n\t\n\t\n\tIndex of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.\n\t\n\t\n\tGetting Started with Deep Learning - Slides (PDF): Slides used in the presentation\n\t\n\n\n \n\nMaterials shared elsewhere:\n\nA recording of the webinar is available on the Australian BioCommons YouTube Channel:\n\nhttps://youtu.be/I1TmpnZUuiQ","doi":"10.5281/zenodo.5121004","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":158,"title":"WEBINAR: Detection of and phasing of hybrid accessions in a target capture dataset","url":"https://staging.dresa.org.au/materials/webinar-detection-of-and-phasing-of-hybrid-accessions-in-a-target-capture-dataset.json","description":"This record includes training materials associated with the Australian BioCommons webinar ‘Detection of and phasing of hybrid accessions in a target capture dataset’. This webinar took place on 10 June 2021.\n\nHybridisation plays an important role in evolution, leading to the exchange of genes between species and, in some cases, generate new lineages. The use of molecular methods has revealed the frequency and importance of reticulation events is higher than previously thought and this insight continues with the ongoing development of phylogenomic methods that allow novel insights into the role and extent of hybridisation. Hybrids notoriously provide challenges for the reconstruction of evolutionary relationships, as they contain conflicting genetic information from their divergent parental lineages. However, this also provides the opportunity to gain insights into the origin of hybrids (including autopolyploids).\n\nThis webinar explores some of the challenges and opportunities that occur when hybrids are included in a target capture sequence dataset. In particular, it describes the impact of hybrid accessions on sequence assembly and phylogenetic analysis and further explores how the information of the conflicting phylogenetic signal can be used to detect and resolve hybrid accessions. The webinar showcases a novel bioinformatic workflow, HybPhaser, that can be used to detect and phase hybrids in target capture datasets and will provide the theoretical background and concepts behind the workflow.\n\nThis webinar is part of a series of webinars and workshops developed by the Genomics for Australian Plants (GAP) Initiative that focuses on the analysis of target capture sequence data. In addition to two public webinars, the GAP bioinformatics working group is offering training workshops in the use of newly developed and existing scripts in an integrated workflow to participants in the 2021 virtual Australasian Systematic Botany Society Conference.\n\nThe materials are shared under a Creative Commons 4.0 International agreement unless otherwise specified and were current at the time of the event.\n\nFiles and materials included in this record:\n\n\n\t\n\tEvent metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.\n\t\n\t\n\tIndex of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.\n\t\n\t\n\tNauheimer_hybphaser_slides (PDF): Slides presented during the webinar\n\t\n\n\nMaterials shared elsewhere:\nA recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/japXwTAhA5U","doi":"10.5281/zenodo.5105013","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":159,"title":"WEBINAR: Conflict in multi-gene datasets: why it happens and what to do about it - deep coalescence, paralogy and reticulation","url":"https://staging.dresa.org.au/materials/webinar-conflict-in-multi-gene-datasets-why-it-happens-and-what-to-do-about-it-deep-coalescence-paralogy-and-reticulation.json","description":"This record includes training materials associated with the Australian BioCommons webinar ‘Conflict in multi-gene datasets: why it happens and what to do about it - deep coalescence, paralogy and reticulation’. This webinar took place on 20 May 2021.\n\nMulti-gene datasets used in phylogenetic analyses, such as those produced by the sequence capture or target enrichment used in the Genomics for Australian Plants: Australian Angiosperm Tree of Life project, often show discordance between individual gene trees and between gene and species trees. This webinar explores three different forms of discordance: deep coalescence, paralogy, and reticulation. In each case, it considers underlying biological processes, how discordance presents in the data, and what bioinformatic or phylogenetic approaches and tools are available to address these challenges. It covers Yang and Smith paralogy resolution and general information on options for phylogenetic analysis.\n\nThis webinar is part of a series of webinars and workshops developed by the Genomics for Australian Plants (GAP) Initiative that focused on the analysis of target capture sequence data. In addition to two public webinars, the GAP bioinformatics working group is offering training workshops in the use of newly developed and existing scripts in an integrated workflow to participants in the 2021 virtual Australasian Systematic Botany Society Conference.\n\nThe materials are shared under a Creative Commons 4.0 International agreement unless otherwise specified and were current at the time of the event.\n\nFiles and materials included in this record:\n\n\n\t\n\tEvent metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.\n\t\n\t\n\tIndex of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.\n\t\n\t\n\tSchmidt-Lebuhn - paralogy lineage sorting reticulation - slides (PDF): Slides presented during the webinar\n\t\n\n\n \n\nMaterials shared elsewhere:\n\nA recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/1bw81q898z8","doi":"10.5281/zenodo.5104998","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":160,"title":"WORKSHOP: Variant calling in humans, animals and plants with Galaxy","url":"https://staging.dresa.org.au/materials/workshop-variant-calling-in-humans-animals-and-plants-with-galaxy.json","description":"This record includes training materials associated with the Australian BioCommons workshop ‘Variant calling in humans, animals and plants with Galaxy’. This workshop took place on 25 May 2021.\n\nVariant calling in polyploid organisms, including humans, plants and animals, can help determine single or multi-variant contributors to a phenotype. Further, sexual reproduction (as compared to asexual) combines variants in a novel manner; this can be used to determine previously unknown variant - phenotype combinations but also to track lineage and lineage associated traits (GWAS studies), that all rely on highly accurate variant calling. The ability to confidently call variants in polyploid organisms is highly dependent on the balance between the frequency of variant observations against the background of non-variant observations, and even further compounded when one considers multi-variant positions within the genome. These are some of the challenges that will be explored in the workshop.\n\nIn this online workshop we focused on the tools and workflows available for variant calling in polyploid organisms in Galaxy Australia. The workshop provided opportunities for hands-on experience using Freebayes for variant calling and SnpEff and GEMINI for variant annotation. The workshop made use of data from a case study on diagnosing a genetic disease however the tools and workflows are equally applicable to other polyploid organisms and biological questions.\n\nAccess to all of the tools covered in this workshop was via Galaxy Australia, an online platform for biological research that allows people to use computational data analysis tools and workflows without the need for programming experience.\n\nThe materials are shared under a Creative Commons 4.0 International agreement unless otherwise specified and were current at the time of the event.\n \n\nFiles and materials included in this record:\n\n\n\t\n\tEvent metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.\n\t\n\t\n\tIndex of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.\n\t\n\t\n\tSchedule (PDF): schedule for the workshop\n\t\n\t\n\tVariant calling - humans, animals, plants - slides (PPTX and PDF): slides used in the workshop\n\t\n\n\n \n\nMaterials shared elsewhere:\n\nThe tutorial used in this workshop is available via the Galaxy Training Network.\n\n\nWolfgang Maier, Bérénice Batut, Torsten Houwaart, Anika Erxleben, Björn Grüning, 2021 Exome sequencing data analysis for diagnosing a genetic disease (Galaxy Training Materials). https://training.galaxyproject.org/training-material/topics/variant-analysis/tutorials/exome-seq/tutorial.html Online; accessed 25 May 2021","doi":"10.5281/zenodo.5076668","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":161,"title":"WEBINAR: Getting started with command line bioinformatics","url":"https://staging.dresa.org.au/materials/webinar-getting-started-with-command-line-bioinformatics.json","description":"This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with command line bioinformatics’. This webinar took place on 22 June 2021. \n\nBioinformatics skills are in demand like never before and biologists are stepping up to the challenge of learning to analyse large and ever growing datasets. Learning how to use the command line can open up many options for data analysis but getting started can be a little daunting for those without a background in computer science.\n\nParice Brandies and Carolyn Hogg have recently put together ten simple rules for getting started with command-line bioinformatics to help biologists begin their computational journeys. In this webinar Parice walks you through their hints and tips for getting started with the command line. She covers topics like learning tech speak, evaluating your data and workflows, assessing computational requirements, computing options, the basics of software installation, curating and testing scripts, a bit of bash and keeping good records. The webinar will be followed by a short Q\u0026amp;A session.\n\nThe slides were created by Parice Brandies and are based on the publication ‘Ten simple rules for getting started with command-line bioinformatics’ (https://doi.org/10.1371/journal.pcbi.1008645). The slides are shared under a Creative Commons Attribution 4.0 International unless otherwise specified and were current at the time of the webinar.\n\nFiles and materials included in this record:\n\n\n\t\n\tEvent metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.\n\t\n\t\n\tIndex of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.\n\t\n\t\n\tGetting started with command line bioinformatics - slides (PDF): Slides presented during the webinar\n\t\n\n\nMaterials shared elsewhere:\n\nA recording of the webinar is available on the Australian BioCommons YouTube Channel\n\nhttps://youtu.be/p7pA4OLB2X4","doi":"10.5281/zenodo.5068997","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":16,"title":"Getting Started with Deep Learning","url":"https://staging.dresa.org.au/materials/getting-started-with-deep-learning.json","description":"This lecture provides a high level overview of how you could get started with developing deep learning applications. It introduces deep learning in a nutshell and then provides advice relating to the concepts and skill sets you would need to know and have in order to build a deep learning application. The lecture also provides pointers to various resources you could use to gain a stronger foothold in deep learning.\r\nThis lecture is targeted at researchers who may be complete beginners in machine learning, deep learning, or even with programming, but who would like to get into the space to build AI systems hands-on.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":15,"title":"Semi-Supervised Deep Learning","url":"https://staging.dresa.org.au/materials/semi-supervised-deep-learning.json","description":"Modern deep neural networks require large amounts of labelled data to train. Obtaining the required labelled data is often an expensive and time consuming process. Semi-supervised deep learning involves the use of various creative techniques to train deep neural networks on partially labelled data. If successful, it allows better training of a model despite the limited amount of labelled data available.\r\n\r\nThis workshop is designed to be instructor led and covers various semi-supervised learning techniques available in the literature. The workshop consists of a lecture introducing at a high level a selection of techniques that are suitable for semi-supervised deep learning. We discuss how these techniques can be implemented and the underlying assumptions they require. The lecture is followed by a hands-on session where attendees implement a semi-supervised learning technique to train a neural network. We observe and discuss the changing performance and behaviour of the network as varying degrees of labelled and unlabelled data is provided to the network during training.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":14,"title":"Visualisation and Storytelling","url":"https://staging.dresa.org.au/materials/visualisation-and-storytelling.json","description":"This workshop explores how data visualisation techniques could be utilised to better understand data and to communicate research efforts and outcomes. The workshop covers a broad range of techniques from simple and static 2D graphics to advanced 3D visualisations in order to provide a broad overview of the tools available for data analysis, presentation and storytelling. We explore, among others, animated charts and graphs, web visualisation tools such as scrollytellers, and the possibilities of 3D, interactive, and even immersive visualisations. We use real world, concrete examples along the way in order to tangibly illustrate how these visualisations can be created and how viewers perceive and interact with them. We also introduce the various tools and skill sets you would need to be proficient at presenting your data to the world.\r\nBy the conclusion of this workshop, you would gain familiarity with the various possibilities for presenting your own research data and outcomes. You would have a more intuitive understanding of the strengths and weaknesses of various modes of data visualisation and storytelling, and would have a starting point to obtain the right skill sets relevant to developing your visualisations of choice.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":13,"title":"Introduction to Gadi - Part 2","url":"https://staging.dresa.org.au/materials/introduction-to-gadi-part-2.json","description":"Gadi is Australia’s most powerful supercomputer, a highly parallel cluster comprising more than 150,000 processor cores on ten different types of compute nodes. Gadi accommodates a wide range of tasks, from running climate models to genome sequencing, from designing molecules to astrophysical modelling. \r\nIntroduction to Gadi - Part 2 naturally follows on from Part 1, and is designed for beginners or users looking for a refresher on Gadi basics.\r\nTo register for this training, click here: https://bit.ly/IntroGadi2","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":12,"title":"Deep Learning for Natural Language Processing","url":"https://staging.dresa.org.au/materials/deep-learning-for-natural-language-processing.json","description":"This workshop is designed to be instructor led and consists of two parts.\r\nPart 1 consists of a lecture-demo about text processing and a hands-on session for attendees to learn how to clean a dataset.\r\nPart 2 consists of a lecture introducing Recurrent Neural Networks and a hands-on session for attendees to train their own RNN.\r\nThe Powerpoints contain the lecture slides, while the Jupyter notebooks (.ipynb) contain the hands-on coding exercises.\r\n\r\nThis workshop introduces natural language as data for deep learning. We discuss various techniques and software packages (e.g. python strings, RegEx, NLTK, Word2Vec) that help us convert, clean, and formalise text data “in the wild” for use in a deep learning model. We then explore the training and testing of a Recurrent Neural Network on the data to complete a real world task. We will be using TensorFlow v2 for this purpose.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":10,"title":"Introduction to Deep Learning and TensorFlow","url":"https://staging.dresa.org.au/materials/introduction-to-deep-learning-and-tensorflow.json","description":"This workshop is intended to run as an instructor guided live event and consists of two parts. Each part consists of a lecture and a hands-on coding exercise.\r\nPart 1 - Introduction to Deep Learning and TensorFlow\r\nPart 2 - Introduction to Convolutional Neural Networks\r\nThe Powerpoints contain the lecture slides, while the Jupyter notebooks (.ipynb) contain the hands-on coding exercises.\r\n\r\nThis workshop is an introduction to how deep learning works and how you could create a neural network using TensorFlow v2. We start by learning the basics of deep learning including what a neural network is, how information passes through the network, and how the network learns from data through the automated process of gradient descent. Workshop attendees would build, train and evaluate a neural network using a cloud GPU (Google Colab).\r\nIn part 2, we look at image data and how we could train a convolution neural network to classify images. Workshop attendees will extend their knowledge from the first part to design, train and evaluate this convolutional neural network.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":9,"title":"Introduction to Gadi - part 1","url":"https://staging.dresa.org.au/materials/introduction-to-gadi-part-i.json","description":"Gadi is Australia’s most powerful supercomputer, a highly parallel cluster comprising more than 150,000 processor cores on ten different types of compute nodes. Gadi accommodates a wide range of tasks, from running climate models to genome sequencing, from designing molecules to astrophysical modelling. \r\nIntroduction to Gadi - Part 1 is designed for new users, or users that want a refresher on the basics of Gadi.\r\nTo register for this training, click here: https://bit.ly/IntroGadi1\r\nIf you have any questions regarding this training, please contact training.nci@anu.edu.au.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":8,"title":"Galaxy 101 For Everyone","url":"https://staging.dresa.org.au/materials/galaxy-101-for-everyone.json","description":"This practical aims at familiarising you with the Galaxy user interface. It will teach you how to perform basic tasks such as importing data, running tools, working with histories, creating workflows and sharing your work.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":2,"title":"InfoQ eMag: Modern Data Engineering","url":"https://staging.dresa.org.au/materials/infoq-emag-modern-data-engineering.json","description":"Data architecture is being disrupted, echoing the evolution of software architecture over the past decade. The changes coming to data engineering will look and sound familiar to those who have watched monoliths be broken up into microservices: DevOps to DataOps; API Gateway to Data Gateway; Service Mesh to Data Mesh. While this will have benefits in agility and productivity, it will come with a cost of understanding and supporting a next-generation data architecture.\r\n\r\nData engineers and software architects will benefit from the guidance of the experts in this eMag as they discuss various aspects of breaking down traditional silos that defined where data lived, how data systems were built and managed, and how data flows in and out of the system.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]},{"id":1,"title":"The InfoQ eMag: Kubernetes and Cloud Architectures","url":"https://staging.dresa.org.au/materials/the-infoq-emag-kubernetes-and-cloud-architectures.json","description":"Does it feel to you like the modern application stack is constantly shifting with new technologies and practices emerging at a blistering pace? It does to me. Every week I seem to come across a new web framework, open-sourcedata integration framework, or architectural anti-pattern that used to be a best practice. But then I stop, take a breath, and see some underlying stability.","doi":"","remote_updated_date":null,"remote_created_date":null,"scientific_topics":[],"operations":[]}]