Chromosomes are structures that carry genes in all our cells. Every human cell has 46 chromosomes. In the nucleus of eukaryotic cells, DNA is highly folded and compacted with specific proteins into a dynamic polymer called chromatin. Gene expression, chromosome division, DNA replication, and repair all act, not on DNA alone, but on this chromatin template. The discovery that enzymes can (re)organise chromatin into accessible and inaccessible configurations revealed mechanisms that considerably e ....Chromosomes are structures that carry genes in all our cells. Every human cell has 46 chromosomes. In the nucleus of eukaryotic cells, DNA is highly folded and compacted with specific proteins into a dynamic polymer called chromatin. Gene expression, chromosome division, DNA replication, and repair all act, not on DNA alone, but on this chromatin template. The discovery that enzymes can (re)organise chromatin into accessible and inaccessible configurations revealed mechanisms that considerably extend the information potential of the genetic code. In addition, it is now established that chromatin structural features can influence gene expression. In vitro studies support a model in which chromatin functions as a barrier for the access to DNA. Therefore this organization has to be tighly regulated and dynamic to allow the protein-DNA interactions critical for nuclear functions. Importantly genome organisation provides in addition to genetic information another layer of information, so called epigenetic, which by definition means that it is stably inherited throughout cellular divisions, yet it is not encoded genetically. Thus each cell type will display a specific epigenome. We have recently constructed small human minichromosomes, which are much easier to study than the much larger normal chromosomes. The present project proposes to define the epigenetic feature across an entire human chromosome using our minichhromosomes as working models. The outcome will be a significant gain in our knowledge on the processes underlying epigenetic regulation, the organisation of specialised chromatin domain, and behaviour of the chromosomes.Read moreRead less
Application Of A Machine Learning Approach For Effective Stock Management Of Farmed Abalone
Funder
Fisheries Research and Development Corporation
Funding Amount
$115,649.00
Summary
Determining the number and size distribution of abalone present at various stages of production is critical information for effective stock management. Currently the Australian abalone aquaculture industry spends in the order of $25,000 per annum, per farm, gathering this information by hand. However, the resulting data is of mediocre quality, is limited in its scope, and collecting the data causes stress to the animals (as it is removed from the water) which can compromise growth and survival. ....Determining the number and size distribution of abalone present at various stages of production is critical information for effective stock management. Currently the Australian abalone aquaculture industry spends in the order of $25,000 per annum, per farm, gathering this information by hand. However, the resulting data is of mediocre quality, is limited in its scope, and collecting the data causes stress to the animals (as it is removed from the water) which can compromise growth and survival. Automated counting and measuring of abalone will increase farm efficiency and productivity in the short term and, in the longer term, will provide an advanced platform for further R & D improvements including accurate data collection during experimental trials (e.g. feeds, temperature). Artificial intelligence and machine learning has now matured to a point that accurately counting and measuring abalone is possible using this approach, however specific application to the abalone industry is yet to be achieved. This project would involve the development, training and validation of a machine learning model to identify, segment and measure quantitative abalone traits in production systems and, render the product data to be accessible and applicable for farmers. Objectives: 1. To develop and implement artificial intelligence as a method for accurately measuring and counting abalone at nursery, weaning and grow out. Read moreRead less
ARDC: Food Security Data Challenges: Increasing Food Security Through Liberation Of Fishing And Aquaculture Data
Funder
Fisheries Research and Development Corporation
Funding Amount
$1,001,708.12
Summary
The development of digital and data systems (DSS) across fisheries & aquaculture, as well as the agriculture sector more broadly is disparate. How data is collected, how it is stored, and how it can subsequently be used is greatly influenced by factors such as sector digital maturity, or available funding to develop (or upgrade) DSS.
This project seeks to develop a national fisheries and aquaculture data ingestion and storage system (Activity 1), ensuring that information derived from f ....The development of digital and data systems (DSS) across fisheries & aquaculture, as well as the agriculture sector more broadly is disparate. How data is collected, how it is stored, and how it can subsequently be used is greatly influenced by factors such as sector digital maturity, or available funding to develop (or upgrade) DSS.
This project seeks to develop a national fisheries and aquaculture data ingestion and storage system (Activity 1), ensuring that information derived from fisheries and aquaculture activities is findable, accessible, interoperable and reusable (FAIR). The ingestion and storage system will be bolstered by a complementary data catalogue (detailing the data sets available on the platform) (Activity 2) and analytical tools (able to gain insights without moving data outside the storage platform) (Activity 6). The platform will be underpinned by metadata (Activity 3) and a robust governance framework (Activity 4). Use of the system will be tested through 3 case studies, supporting capacity and capability improvement of the sector (Activity 5).
The production of and use of data cuts across industry and government, and covers activities throughout the fisheries supply chain (from pre-fishing quota management, to post-fishing processing and subsequent traceability). Consequently there is no one organisation across fishing and aquaculture that is best placed to co-ordinate and trial this technology. FRDC is capable to the leadership required to ensure a fit for purpose product for end users, additionally the leverage of Australia Research Data Commons investment will contribute to the development of a nationally coherent eResearch infrastructure
This project received investment from the Australian Research Data Commons (ARDC). The ARDC is funded by the National Collaborative Research Infrastructure Strategy (NCRIS). Objectives: 1. Develop a new cloud-based fisheries data storage platform to enable ingestion, management, and sharing of datasets 2. Develop a CKAN-based data catalogue, a searchable fisheries data source allowing users to browse, combine, share, and access exchangeable data assets 3. Create best practice metadata standards that will be identified, documented, and then operationalised through the data catalogue and storage platform 4. Develop and operationalise a fisheries-focused data governance framework 5. Enhance capacity and capacity to use the platform through demonstration of 3 unique case studies 6. Develop use-case relevant suite of reporting and analysis tools to allow researchers to gain insights without moving data outside the storage platform Read moreRead less
Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering ap ....Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering applications which will both reduced the bandwidth required and make the internet safer for users. Finally, it will enable rapid deployment of sensor networks for monitoring and detection, such as for environmental monitoring and safeguarding Australia's borders.Read moreRead less
Investigating The Use Of A Remote Operated Underwater Vehicle (ROUV) For Surveying Abalone On Reefs In The Western Zone Abalone Fishery, Victoria.
Funder
Fisheries Research and Development Corporation
Funding Amount
$160,000.00
Summary
Provide a tactical and strategic response to the recent outbreak. Develop a cost effective assessment tool to validate the spread of the virus and build a long term mechanism to undertake fisheries independent surveys. Objectives: 1. To validate a remotely operated underwater vehicle (ROUV) survey tool 2. Assess options to integrate video from ROUV technology and other sources with existing diver data to develop fisheries independent surveys 3. To validate non surveye ....Provide a tactical and strategic response to the recent outbreak. Develop a cost effective assessment tool to validate the spread of the virus and build a long term mechanism to undertake fisheries independent surveys. Objectives: 1. To validate a remotely operated underwater vehicle (ROUV) survey tool 2. Assess options to integrate video from ROUV technology and other sources with existing diver data to develop fisheries independent surveys 3. To validate non surveyed abalone populations Read moreRead less
Developing Biomass Assessment Approaches, Harvest Methodologies And Biosecurity Knowledge For Wild-harvest Of Seaweeds In Southern Australia
Funder
Fisheries Research and Development Corporation
Funding Amount
$576,519.00
Summary
After many years of interest but little on ground activity apart from a few established operations based on the harvest of beach-cast material, the seaweed industry is starting to gain momentum in southern Australia. There is particular interest in the farming of Asparagopsis for its methane reducing properties in ruminants, but also in several species for human consumption and other uses, including the golden kelp Ecklonia radiata. While much of the focus is on the development of an aquacultu ....After many years of interest but little on ground activity apart from a few established operations based on the harvest of beach-cast material, the seaweed industry is starting to gain momentum in southern Australia. There is particular interest in the farming of Asparagopsis for its methane reducing properties in ruminants, but also in several species for human consumption and other uses, including the golden kelp Ecklonia radiata. While much of the focus is on the development of an aquaculture industry, this needs to be supported by the wild harvest of seedstock, at least in the early years, and there is also some interest in wild-harvest for product. However, the knowledge base and tools available for managers to regulate this emerging industry are limited. This proposal aims to start filling in some of these gaps. The first is to develop an understanding of the biomass present in targeted areas, and importantly, the development of a rapid assessment tool to do this, which can then be used to form the basis of a stock assessment methodology as the industry expands. The second is to develop harvest methodologies that allow for the recovery of local stocks, and which can be used to inform rotational harvest strategies by documenting how long recovery takes. The third is to develop an understanding of some of the biosecurity issues likely to be faced by industry and regulators, which will allow managers to make informed decisions around translocation policies to both prevent the spread of disease, and to maintain the genetic integrity of natural populations. Objectives: 1. Develop a rapid assessment tool for species specific subtidal macroalgal biomass, initially for Asparagopsis armata, A. taxiformis and E. radiata. 2. Develop harvesting methods for the above species that ensure that local populations are not depleted, and that ecosystem function is not compromised. 3. Review literature on macroalgae diseases, pests, health management strategies and population structure. 4. Identify information and approaches to define health management units. 5. Collate information and build an initial basic approach to translocation. Read moreRead less