Similar to managing software packages, managing the ontology life cycle involves multiple complex workflows such as preparing releases, continuous quality control checking and dependency management. To manage these processes, a diverse set of tools is required, from command-line utilities to powerful ontology-engineering environmentsr. Particularly in the biomedical domain, which has developed a set of highly diverse yet inter-dependent ontologies, standardizing release practices and metadata and establishing shared quality standards are crucial to enable interoperability. The Ontology Development Kit (ODK) provides a set of standardized, customizable and automatically executable workflows, and packages all required tooling in a single Docker image. In this paper, we provide an overview of how the ODK works, show how it is used in practice and describe how we envision it driving standardization efforts in our community. Database URL: https://github.com/INCATools/ontology-development-kit

The metabotropic glutamate receptor 5 (mGlu5) and N -methyl- d -aspartate (NMDA) receptor are critical for processes underlying synaptic plasticity, s

It is well accepted that it is part of a scientist’s duty to communicate science, yet most practicing scientists lack the training and opportunity to do so. In this article, we use the framework of science talks in bars to highlight the importance of locality and environment. We propose that science communication programs should be developed around the locales of the target community as an effective strategy to counter the rising mistrust in science and scientists.

Large-scale single-cell ‘omics profiling is being used to define a complete catalogue of brain cell types, something that traditional methods struggle with due to the diversity and complexity of the brain. But this poses a problem: How do we organise such a catalogue - providing a standard way to refer to the cell types discovered, linking their classification and properties to supporting data? Cell ontologies provide a partial solution to these problems, but no existing ontology schemas support the definition of cell types by direct reference to supporting data, classification of cell types using classifications derived directly from data, or links from cell types to marker sets along with confidence scores. Here we describe a generally applicable schema that solves these problems and its application in a semi-automated pipeline to build a data-linked extension to the Cell Ontology representing cell types in the Primary Motor Cortex of humans, mice and marmosets. The methods and resulting ontology are designed to be scalable and applicable to similar whole-brain atlases currently in preparation.

Deep brain stimulation (DBS) is a promising treatment for many memory-related disorders including dementia, anxiety, and addiction. However, the use of DBS can be a paradoxical conundrum-dementia treatments aim to improve memory, whereas anxiety or addiction treatments aim to suppress maladaptive memory. In this review, the key hypotheses on how DBS affects memory are highlighted. We consolidate the findings and conclusions from the current research on the effects of DBS on memory in attempt to make sense of the bidirectional nature of DBS in disrupting and enhancing memory. Based on the current literature, we hypothesize that the timing of DBS plays a key role in its contradictory effects, and therefore, we propose a consolidated model of how DBS can both disrupt and enhance memory.