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Upcoming Webinars

Upcoming ISCBacademy Webinars



Join us for our upcoming ISCBacademy Webinars.  Check back regularly for updates

 


The ISCB Competency Framework: what is it and how does it support bioinformatics education and training?
By Cath Brooksbank

January 26, 2021 at 9:00AM EST

Demand for the application of data science techniques to life science research is accompanied by an increased need for bioinformatics expertise across a broad range of professionals – from lab-based molecular life-scientists through computer scientists to software engineers; furthermore, the applications of data-driven biology are just as varied, encompassing fundamental life-science, medicine, agriculture and environmental science. Educating and training the individuals who choose career paths in this varied and fast-moving field is therefore challenging, and educators can struggle to keep up with the needs of employers. 

The ISCB competency framework was developed by the ISCB Education Committee in consultation with a global community of bioinformatics professionals to bridge this gap. It provides a minimum information standard defining the competencies required, and the levels they’re required at, for a range of roles that require bioinformatics expertise, and it provides a tool to support bioinformatics educators to develop courses and curricula that meet the needs of employers.

In this webinar I will explain why the ISCB adopted a competency-based approach, describe the newly released version 3 of the framework, summarise how educators and trainers can use the framework to develop new learning interventions or update pre-existing ones, and outline how the ISCB is planning to support a competency-based approach to bioinformatics education and training in the future, both through continuing improvement of the framework and through initiatives to encourage the recognition of courses and curricula that make use of it.

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SaGePhy: A phylogenetic simulation framework for gene and subgene evolution
By Soumya Kundu

January 28, 2021 at 11:00AM EST

SaGePhy (pronounced sage-phy) is a software package for improved phylogenetic simulation of gene and subgene evolution. SaGePhy can be used to generate species trees, gene trees, and subgene or (protein) domain trees using a probabilistic birth–death process that allows for gene and subgene duplication, horizontal gene and subgene transfer, and gene and subgene loss. SaGePhy implements a range of important features not generally found in other phylogenetic simulation frameworks; these include the ability to simulate (i) subgene or domain level events inside one or more gene families, (ii) both additive and replacing horizontal gene and subgene/domain transfers, (iii) distance-biased horizontal transfers, and (iv) probabilistic sampling of species tree and gene tree nodes, respectively, for gene- and domain-family birth. SaGePhy therefore makes it possible to perform more realistic simulation of gene and subgene/domain evolution.

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Responsibilities for the Stewardship of Indigenous Data in Open Science
by Stephanie Russo Carroll

February 11, 2021 at 1:00PM EST

As big data, open data, and open science advance to increase access to complex and large datasets for innovation, discovery, and decision-making, Indigenous Peoples’ rights to control and access their data within these data environments remain limited. Indigenous Data Sovereignty focuses on the protection of Indigenous rights and interests in the control and governance of Indigenous data. Indigenous data interests stretch across diverse disciplinary fields connecting community data governance ambitions with institutional and individual responsibilities in practice. Given this reach, a range of initiatives have been developed to strategically build new capabilities for strengthening control and governance of Indigenous data. These initiatives draw on a variety of methods and tactics across law, policy, ethics, and infrastructure. Applying these new tools and mechanisms in open science shifts Indigenous Peoples from invisibility within data ecosystems to vibrant contributors to open science.

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