neurogenomics/rworkflows: v1

<h1>rworkflows 1.0.0</h1> <h2>New features</h2> <ul> <li>Synchronise <code>rworkflows</code> package versioning with <code>rworkflows</code> action Release versioning.</li> <li><code>use_vignette_docker</code>/<code>use_vignette_getstarted</code><ul> <li>Autofill <code>package</code> arg if not provided.</li> </ul> </li> </ul> <h2>Bug fixes</h2> <ul> <li><em>inst/template/docker.Rmd</em><ul> <li>Remove the need to include <code>construct_cont</code>, as not everyone will have <code>rworkfows</code> installed on the machine where the vignette is being rendered.</li> </ul> </li> <li><em>use_vignette_docker</em><ul> <li>Add <em>-autolink_bare_uris</em> bit to avoid CRAN check errors.</li> </ul> </li> <li>Change <code>\itemize</code> --> <code>describe</code> to avoid CRAN check errors.</li> </ul&gt

neurogenomics/rworkflows: v1

<h1>rworkflows 1.0.0</h1> <h2>New features</h2> <ul> <li>Synchronise <code>rworkflows</code> package versioning with <code>rworkflows</code> action Release versioning.</li> <li><code>use_vignette_docker</code>/<code>use_vignette_getstarted</code><ul> <li>Autofill <code>package</code> arg if not provided.</li> </ul> </li> </ul> <h2>Bug fixes</h2> <ul> <li><em>inst/template/docker.Rmd</em><ul> <li>Remove the need to include <code>construct_cont</code>, as not everyone will have <code>rworkfows</code> installed on the machine where the vignette is being rendered.</li> </ul> </li> <li><em>use_vignette_docker</em><ul> <li>Add <em>-autolink_bare_uris</em> bit to avoid CRAN check errors.</li> </ul> </li> </ul&gt

neurogenomics/rworkflows: v0

Continuous integration for R packages. Automates testing ✅, documentation website building , & containerised deployment

neurogenomics/rworkflows: v0

Continuous integration for R packages. Automates testing ✅, documentation website building , & containerised deployment

neurogenomics/rworkflows: v1

Continuous integration for R packages. Automates testing ✅, documentation website building , & containerised deployment

P197.02 - Assessment of the Active Kinome in Hippocampal Subfields

This study will use a functional proteomic approach to examine the active kinome in the hippocampus. The active kinome is the global activity of all protein kinases in a system. The hippocampus is subject to dynamic change based on regulatory needs within the system and can therefore contribute to neuroplasticity at a cellular level. The hippocampus has distinct subfields (DG, CA1, CA2, CA3, CA4) and plays a major role in learning and memory. The hippocampal subfields are discrete and have distinct anatomy. Thus, we hypothesize that each subfield has a unique active kinome profile. Differential protein kinase regulation may be essential for molecular plastic changes within the brain. This plasticity is vital for cognitive ability. By identifying the protein kinase activity in each hippocampal subfield, comparisons can be made between subkinomes to better understand signaling pathways associated with memory and learning within the brain. The subfields will be isolated via laser capture microdissection (LCM) and run on the PamGene kinome array. Analysis of the array data will be performed using bioinformatic pipelines. Bioinformatic analyses will identify the kinase activity profiles enriched in different hippocampal subfields . The pipelines used in kinomic analysis are Upstream Kinase Analysis (UKA) and Kinome Random Sampling Analyzer (KRSA). Additionally, pathways will be visualized using Bayesian Network Modeling (KINNET). Hippocampal subfield specific pathways will also be generated. The key kinases investigated and the pathways they belong to will then be compared and contrasted between subfields to paint a clearer picture of how they communicate with one another. These studies will extend our knowledge of signalling mechanisms in the hippocampus and provide a roadmap for interrogating the hippocampus in discrete subfields