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Authors: Dow, Ellen (orcid: 0000-000...  or Conradsen, Cara (orcid: 000...  or Titus Tang 

WEBINAR: KBase - A knowledge base for systems biology

This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021.

Event description 

Developed for bench biologists and bioinformaticians, The Department of Energy Systems...

Keywords: Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology

WEBINAR: KBase - A knowledge base for systems biology https://dresa.org.au/materials/webinar-kbase-a-knowledge-base-for-systems-biology-653d9753-989d-4194-9230-6e2d90652955 This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021. Event description  Developed for bench biologists and bioinformaticians, The Department of Energy Systems Biology Knowledgebase (KBase) is a free, open source, software and data science platform designed to meet the grand challenge of systems biology: predicting and designing biological function. This webinar will provide an overview of the KBase mission and user community, as well as a tour of the online platform and basic functionality. You’ll learn how KBase can support your research: Upload data, run analysis tools (Apps), share your analysis with collaborators, and publish your data and reproducible workflows. We’ll highlight a brand new feature that enables users to link environment and measurement data to sequencing data. You’ll also find out how KBase supports findable, accessible, interoperable, and reusable (FAIR) research by providing open, reproducible, shareable bioinformatics workflows. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index 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. Q&A for Australian BioCommons KBase Webinar [PDF]: Document containing answers to questions asked during the webinar and links to additional resources Introduction to KBase: Australian BioCommons Webinar [PDF]: Slides presented during the webinar Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/tJ94i9gOJfU The slides are also available as Google slides:  https://tinyurl.com/KBase-webinar-slides Melissa Burke (melissa@biocommons.org.au) Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology
WORKSHOP: R: fundamental skills for biologists

This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.

 

Event description

Biologists need data analysis skills to be able to...

Keywords: Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation

WORKSHOP: R: fundamental skills for biologists https://dresa.org.au/materials/workshop-r-fundamental-skills-for-biologists-81aa00db-63ad-4962-a7ac-b885bf9f676b This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.   Event description Biologists need data analysis skills to be able to interpret, visualise and communicate their research results. While Excel can cover some data analysis needs, there is a better choice, particularly for large and complex datasets.  R is a free, open-source software and programming language that enables data exploration, statistical analysis, visualisation and more. The large variety of R packages available for analysing biological data make it a robust and flexible option for data of all shapes and sizes.  Getting started can be a little daunting for those without a background in statistics and programming. In this workshop we will equip you with the foundations for getting the most out of R and RStudio, an interactive way of structuring and keeping track of your work in R. Using biological data from a model of influenza infection, you will learn how to efficiently and reproducibly organise, read, wrangle, analyse, visualise and generate reports from your data in R. Topics covered in this workshop include: Spreadsheets, organising data and first steps with R Manipulating and analysing data with dplyr Data visualisation Summarized experiments and getting started with Bioconductor   This workshop is presented by the Australian BioCommons and Saskia Freytag from WEHI  with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index 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. Schedule (PDF): A breakdown of the topics and timings for the workshop Recommended resources (PDF): A list of resources recommended by trainers and participants Q_and_A(PDF): Archive of questions and their answers from the workshop Slack Channel. Materials shared elsewhere:   This workshop follows the tutorial ‘Introduction to data analysis with R and Bioconductor’ which is publicly available. https://saskiafreytag.github.io/biocommons-r-intro/ This is derived from material produced as part of The Carpentries Incubator project https://carpentries-incubator.github.io/bioc-intro/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
WORKSHOP: R: fundamental skills for biologists

This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022.

Event description

Biologists need data analysis skills to be able to...

Keywords: Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation

WORKSHOP: R: fundamental skills for biologists https://dresa.org.au/materials/workshop-r-fundamental-skills-for-biologists This record includes training materials associated with the Australian BioCommons workshop ‘R: fundamental skills for biologists’. This workshop took place over four, three-hour sessions on 1, 8, 15 and 22 June 2022. **Event description** Biologists need data analysis skills to be able to interpret, visualise and communicate their research results. While Excel can cover some data analysis needs, there is a better choice, particularly for large and complex datasets.  R is a free, open-source software and programming language that enables data exploration, statistical analysis, visualisation and more. The large variety of R packages available for analysing biological data make it a robust and flexible option for data of all shapes and sizes.  Getting started can be a little daunting for those without a background in statistics and programming. In this workshop we will equip you with the foundations for getting the most out of R and RStudio, an interactive way of structuring and keeping track of your work in R. Using biological data from a model of influenza infection, you will learn how to efficiently and reproducibly organise, read, wrangle, analyse, visualise and generate reports from your data in R. Topics covered in this workshop include: - Spreadsheets, organising data and first steps with R - Manipulating and analysing data with dplyr - Data visualisation - Summarized experiments and getting started with Bioconductor This workshop is presented by the Australian BioCommons and Saskia Freytag from WEHI  with the assistance of a network of facilitators from the national Bioinformatics Training Cooperative. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. **Files and materials included in this record:** - Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. - Index 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. - Schedule (PDF): A breakdown of the topics and timings for the workshop - Recommended resources (PDF): A list of resources recommended by trainers and participants - Q_and_A(PDF): Archive of questions and their answers from the workshop Slack Channel. **Materials shared elsewhere:** This workshop follows the tutorial ‘Introduction to data analysis with R and Bioconductor’ which is publicly available. https://saskiafreytag.github.io/biocommons-r-intro/ This is derived from material produced as part of The Carpentries Incubator project https://carpentries-incubator.github.io/bioc-intro/ Melissa Burke (melissa@biocommons.org.au) Bioinformatics, Analysis, Statistics, R software, RStudio, Data visualisation
WEBINAR: KBase - A knowledge base for systems biology

This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021.

Event description

Developed for bench biologists and bioinformaticians, The Department of Energy...

Keywords: Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology

WEBINAR: KBase - A knowledge base for systems biology https://dresa.org.au/materials/webinar-kbase-a-knowledge-base-for-systems-biology This record includes training materials associated with the Australian BioCommons webinar ‘KBase - A knowledge base for systems biology’. This webinar took place on 22 September 2021. **Event description** Developed for bench biologists and bioinformaticians, The Department of Energy Systems Biology Knowledgebase (KBase) is a free, open source, software and data science platform designed to meet the grand challenge of systems biology: predicting and designing biological function. This webinar will provide an overview of the KBase mission and user community, as well as a tour of the online platform and basic functionality. You’ll learn how KBase can support your research: Upload data, run analysis tools (Apps), share your analysis with collaborators, and publish your data and reproducible workflows. We’ll highlight a brand new feature that enables users to link environment and measurement data to sequencing data. You’ll also find out how KBase supports findable, accessible, interoperable, and reusable (FAIR) research by providing open, reproducible, shareable bioinformatics workflows. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. **Files and materials included in this record:** - Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. - Index 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. - Q&A for Australian BioCommons KBase Webinar [PDF]: Document containing answers to questions asked during the webinar and links to additional resources - Introduction to KBase: Australian BioCommons Webinar [PDF]: Slides presented during the webinar **Materials shared elsewhere:** A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/tJ94i9gOJfU The slides are also available as Google slides:  https://tinyurl.com/KBase-webinar-slides Melissa Burke (melissa@biocommons.org.au) Systems Biology, FAIR Research, Open Source Software, Metagenomics, Microbiology
Deep Learning for Natural Language Processing

This workshop is designed to be instructor led and consists of two parts.
Part 1 consists of a lecture-demo about text processing and a hands-on session for attendees to learn how to clean a dataset.
Part 2 consists of a lecture introducing Recurrent Neural Networks and a hands-on session for...

Keywords: Deep learning, NLP, Machine learning

Resource type: presentation, tutorial

Deep Learning for Natural Language Processing https://dresa.org.au/materials/deep-learning-for-natural-language-processing This workshop is designed to be instructor led and consists of two parts. Part 1 consists of a lecture-demo about text processing and a hands-on session for attendees to learn how to clean a dataset. Part 2 consists of a lecture introducing Recurrent Neural Networks and a hands-on session for attendees to train their own RNN. The Powerpoints contain the lecture slides, while the Jupyter notebooks (.ipynb) contain the hands-on coding exercises. This 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. datascienceplatform@monash.edu Deep learning, NLP, Machine learning
Getting Started with Deep Learning

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...

Keywords: Deep learning, Machine learning

Resource type: presentation

Getting Started with Deep Learning https://dresa.org.au/materials/getting-started-with-deep-learning 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. This 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. datascienceplatform@monash.edu Deep learning, Machine learning
Semi-Supervised Deep Learning

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...

Keywords: Deep learning, Machine learning, semi-supervised

Resource type: presentation, tutorial

Semi-Supervised Deep Learning https://dresa.org.au/materials/semi-supervised-deep-learning 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. This 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. datascienceplatform@monash.edu Deep learning, Machine learning, semi-supervised
Introduction to Deep Learning and TensorFlow

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.
Part 1 - Introduction to Deep Learning and TensorFlow
Part 2 - Introduction to Convolutional Neural Networks
The Powerpoints contain...

Keywords: Deep learning, convolutional neural network, tensorflow, Machine learning

Resource type: presentation, tutorial

Introduction to Deep Learning and TensorFlow https://dresa.org.au/materials/introduction-to-deep-learning-and-tensorflow 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. Part 1 - Introduction to Deep Learning and TensorFlow Part 2 - Introduction to Convolutional Neural Networks The Powerpoints contain the lecture slides, while the Jupyter notebooks (.ipynb) contain the hands-on coding exercises. This 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). In 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. datascienceplatform@monash.edu Deep learning, convolutional neural network, tensorflow, Machine learning
WEBINAR: Getting started with deep learning

This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with deep learning’. This webinar took place on 21 July 2021.

Are you wondering what deep learning is and how it might be useful in your research? This high level overview introduces...

Keywords: Deep learning, Bioinformatics, Machine learning

Resource type: video, presentation

WEBINAR: Getting started with deep learning https://dresa.org.au/materials/webinar-getting-started-with-deep-learning This record includes training materials associated with the Australian BioCommons webinar ‘Getting started with deep learning’. This webinar took place on 21 July 2021. Are 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. The webinar is followed by a short Q&A session. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index 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. Getting Started with Deep Learning - Slides (PDF): Slides used in the presentation Materials shared elsewhere: A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/I1TmpnZUuiQ Melissa Burke (melissa@biocommons.org.au) Deep learning, Bioinformatics, Machine learning