ArticleJournal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience2022
Trainingspace: Neuroeducation Without Borders.
Article in Journal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Interdisciplinary and Collaborative Training in Neuroscience: Insights from the Human Brain Project Education Programme.Neuroinformatics · 2024Article
- An Introduction to the Proceedings of the 2020 FUN Summer Virtual Meeting.Journal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience · 2022Article
- Pandemic Teaching: Using the Allen Cell Types Database for Final Semester Projects in an Undergraduate Neurophysiology Lab Course.Journal of undergraduate neuroscience education : JUNE : a publication of FUN, Faculty for Undergraduate Neuroscience · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advancements in the field of neuroinformatics have resulted in a massive explosion of raw data of many varieties, yet many traditional neuroscience training programs have not changed their curricula to reflect the urgent need for improved computational skills that would enable trainees to handle, organize, and interrogate such large, multimodal datasets. Thus, the objective of this project was to build an open access hub of neuroscience educational resources to fill the gap between current neuroscience curricula and the computationally focused skillset required to work with big data. To achieve this aim, we invited representatives from the world's leading neuroscience societies and large-scale brain initiatives to form the INCF Training and Education Committee that would provide oversight over the content and capabilities of the online hub. As a result, we developed TrainingSpace (https://training.incf.org/), an open access hub of nearly 500 multimedia courses, lectures, and tool tutorials covering the subspecialisms of neuroscience and neuroinformatics, as well as computer science, data science, and ethics. In addition to course content, TrainingSpace also provides users with access to publicly available datasets through KnowledgeSpace, a discoverability portal and community encyclopedia for neuroscience, as well as a question and answer forum, Neurostars.org. Since its launch in 2019, TrainingSpace has steadily increased in popularity with both trainees and trainers alike. It has also become popular with content providers that want to make their training materials available to the neuroscience community-at-large, as well as integrate their content into the larger TrainingSpace ecosystem.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.