<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
This record includes training materials associated with the Australian BioCommons webinar ‘MaveDB: discovery and interpretation of high-throughput functional assay data’. This webinar took place on 26 March 2024. Event description Multiplexed assays of variant effect (MAVEs) are a family of experimental techniques that measure all single amino acid or single nucleotide changes in a gene or other functional element. MaveDB is an international community database that enables discovery and reuse of data from these experiments. It provides a platform for integrating large-scale measurements of sequence variant impact with applications that can be used to interpret the data for basic and clinical research. In this webinar we consider: What are MAVEs and how are the experiments performed? How much MAVE data is available in MaveDB and how is it organised? Who can submit datasets to MaveDB? What are some of the clinical applications for MAVEs and how is the data being used to understand patient variants? Speaker: Dr Alan Rubin, Senior Research Officer, WEHI Host: Dr Melissa Burke, Australian BioCommons Materials 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. MAVEDB_slides: A PDF copy of the slides presented during the webinar. Materials shared elsewhere: A recording of this webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/BXGQ2IuDnGE
FOS: Computer and information sciences, Bioinformatics, Functional annotation, Genetic variation, Clinical genetics
FOS: Computer and information sciences, Bioinformatics, Functional annotation, Genetic variation, Clinical genetics
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |