The use of open-access data, models and tools has become increasingly prevalent in modern neuroscience. These resources are commonly used to supplement new experiments, but there is also an increasing number of studies, which rely exclusively on such publicly available open-access data and models to generate new results. Benefits of this kind of approach are many: Reuse of data and models saves time, effort and money, increases transparency and reproducibility, and encourages collaborations between researchers working in different institutions. Furthermore, the data can often originate from large, well-funded projects, which can have benefits like high-quality data and large sample sizes. Another emerging trend is freely available computational resources, aiming towards making highly computationally intensive data analysis or neural simulations more available to the broad scientific community. This growing culture for openness and sharing is giving researchers quick and easy access to high-quality neuroscience data, models, tools and computational resources, especially benefiting researchers early in their career, or from countries that have poor science funding.
The current Research Topic thus welcomes papers that will focus on the use of open-access data, models or resources from different online neuroscience repositories or platforms. This topic will cover a broad range of neuroscience research areas, in experimental, computational, and clinical neuroscience, expanding from cell and brain tissue image analysis, to simulated neural activity, and to genomic, transcriptomic and proteomic research. The authors should use (or present how other researchers could use) publicly available and open-access data, models or resources for the purpose of their research. In addition to generating new results, the main impact of this Research Topic will be to raise awareness on the importance and numerous possibilities that open-access data sharing allows in neuroscience research.
This Research Topic will welcome all types of articles related to basic and clinical neuroscience research on open-access data, models and tools. Topics of interest include diverse neuroscience research areas based on open-access data:
1. Morphometric analysis of brain cell and tissue samples
2. Analysis of brain cell and tissue images, including microscopic images and MRI images
3. Exploration and analysis of gene expression, transcriptomic and proteomic datasets
4. Functional analysis of EEG datasets
5. Neuronal modeling and neural networks
6. Machine learning techniques and algorithms
7. Novel and freely available computational resources and platforms used for neuroscience research
The use of open-access data, models and tools has become increasingly prevalent in modern neuroscience. These resources are commonly used to supplement new experiments, but there is also an increasing number of studies, which rely exclusively on such publicly available open-access data and models to generate new results. Benefits of this kind of approach are many: Reuse of data and models saves time, effort and money, increases transparency and reproducibility, and encourages collaborations between researchers working in different institutions. Furthermore, the data can often originate from large, well-funded projects, which can have benefits like high-quality data and large sample sizes. Another emerging trend is freely available computational resources, aiming towards making highly computationally intensive data analysis or neural simulations more available to the broad scientific community. This growing culture for openness and sharing is giving researchers quick and easy access to high-quality neuroscience data, models, tools and computational resources, especially benefiting researchers early in their career, or from countries that have poor science funding.
The current Research Topic thus welcomes papers that will focus on the use of open-access data, models or resources from different online neuroscience repositories or platforms. This topic will cover a broad range of neuroscience research areas, in experimental, computational, and clinical neuroscience, expanding from cell and brain tissue image analysis, to simulated neural activity, and to genomic, transcriptomic and proteomic research. The authors should use (or present how other researchers could use) publicly available and open-access data, models or resources for the purpose of their research. In addition to generating new results, the main impact of this Research Topic will be to raise awareness on the importance and numerous possibilities that open-access data sharing allows in neuroscience research.
This Research Topic will welcome all types of articles related to basic and clinical neuroscience research on open-access data, models and tools. Topics of interest include diverse neuroscience research areas based on open-access data:
1. Morphometric analysis of brain cell and tissue samples
2. Analysis of brain cell and tissue images, including microscopic images and MRI images
3. Exploration and analysis of gene expression, transcriptomic and proteomic datasets
4. Functional analysis of EEG datasets
5. Neuronal modeling and neural networks
6. Machine learning techniques and algorithms
7. Novel and freely available computational resources and platforms used for neuroscience research
