{"links":{"self":"http://dataportal.arc.gov.au/NCGP/API/grants/DE260100775"},"data":{"type":"grant-details","id":"DE260100775","attributes":{"code":"DE260100775","administering-organisation":"The University of Queensland","announcement-administering-organisation":"The University of Queensland","scheme-name":"Discovery Early Career Researcher Award","grant-status":"Active","funding-commencement-year":2026,"years-funded":3,"project-start-date":"2026-07-01","anticipated-end-date":"2029-06-30","grant-summary":"Compressed Data Structures for Scalable Genomic Search. This project aims to develop novel compressed indexes and querying algorithms for efficiently processing genomic sequence data at massive scales. The project expects to improve data representations for supporting membership, pattern matching, and ranking tasks over biological sequences used in the life sciences and medicine. Expected outcomes include novel compressed structures for representing sequences; querying algorithms which can operate with reduced computational resources; and an enhanced capability for handling dynamic and evolving biological sequence data. The outcomes of this project can benefit a range of scientific research discovery applications by improving analytical capacity while reducing the time and resources required. ","funding-current":503812.00,"funding-at-announcement":499845,"investigators-current":[{"title":"Dr","firstName":"Joel","familyName":"Mackenzie","roleName":"Discovery Early Career Researcher Award","roleCode":"DECRA","isFellowship":true,"orcidIdentifier":"0000-0001-7992-4633 "}],"investigators-at-announcement":[{"title":"Dr","firstName":"Joel","familyName":"Mackenzie","roleName":"Discovery Early Career Researcher Award","roleCode":"DECRA","isFellowship":true,"orcidIdentifier":"0000-0001-7992-4633 "}],"organisations-current":[{"organisationName":"The University of Queensland","roleName":"Administering Organisation","state":"QLD"}],"organisations-at-announcement":[{"organisationName":"The University of Queensland","roleName":"Administering Organisation","state":"QLD"}],"field-of-research":[{"isPrimary":true,"code":"4605","name":"Data Management and Data Science","type":"FOR20"},{"isPrimary":false,"code":"460501","name":"Data Engineering and Data Science","type":"FOR20"},{"isPrimary":false,"code":"460503","name":"Data Models, Storage and Indexing","type":"FOR20"},{"isPrimary":false,"code":"461305","name":"Data Structures and Algorithms","type":"FOR20"}],"socio-economic-objective":[{"code":"280115","name":"Expanding Knowledge In the Information and Computing Sciences","type":"SEO20"}],"international-collaboration":["Canada","Finland","Italy","United States of America"],"lief-register":[],"achievement-summary":null,"national-interest-test-statement":"Large-scale sequence data is ubiquitous in domains such as bioinformatics, web search, social media, finance, and transport, and is crucial for data-driven decision making. However, this data is now being generated faster than it can be processed, so it is imperative that we devise efficient compressed storage mechanisms that are future proof in supporting fast and scalable querying and analytics.\n\nThis project is expected to benefit Australian and international industry by developing cheaper and more scalable data representations for massive sequence data with a specific focus on biological sequences. The expected outcomes include novel structures for handling this data, enhancing information access, discovery, and analytics in applications with highly repetitive sequence data, including genomics and bioinformatics, data mining, natural language processing, and cybersecurity.\n\nSupporting efficient storage and querying of higher data volumes will reduce the time and cost of discovery in the sciences. The lower computational costs of these structures will benefit Australian businesses economically through reduced hardware requirements, and will in turn bring environmental benefit through reduced electricity and carbon emissions for sequence-oriented big-data applications. This project will also benefit the Australian workforce by providing enhanced knowledge and improving best practices in the domain of efficient data structures and algorithms."}}}