SORTED
SORTED: A curated collection of interesting ideas, tools, and resources in neuroscience, data management, and data science, all in the spirit of Open Science. Additionally, it includes interesting miscellaneous links related to AI tools and productivity.
https://github.com/PTDZ/SORTED
Last synced: 2 days ago
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Reading corner
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Articles
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Paper
- Paper
- Article
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
- Article
- Paper
- Paper
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
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Design
- The Design of Everyday Things - friendly.
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Programming
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Relaxing on a hammock under a tree...
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Unreliable Science (*and how to try overcome this issue)
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Other
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Other articles
- Paper - user’s perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results"
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Open data movement
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Platforms
- OpenNeuro - compliant MRI, PET, MEG, EEG, and iEEG data
- OpenNeuro PET - compliant PET data
- NeuroVault
- BossDB
- GigaDB
- Machine learning datasets
- Harvard Dataverse
- Dryad - use of all research data.
- GIN
- Zenodo
- NeMO - omic Archive (NeMO Archive) is a data repository specifically focused on the storage and dissemination of omic data generated from the BRAIN Initiative, SCORCH consortium and related brain research projects
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Journals
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Other lists
- Wikipedia: List of neuroscience databases
- Most Cited Deep Learning Papers - Most Cited Deep Learning Papers
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Open Data Science
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Journals (for Data Notes)
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Data Repositories (suitable for neuroimaging datasets)
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Tools
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General: research
- BIDS
- Protocols.io
- DataLad
- ADDI - workbench): Alzheimer's Disease Data Initiative; "a free data sharing platform, data science tools, funding opportunities, and global collaborations, ADDI is advancing scientific breakthroughs and accelerating progress towards new treatments and cures for AD and related dementias"
- The Human Protein Atlas - based program initiated in 2003 with the aim to map all the human proteins in cells, tissues, and organs using an integration of various omics technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics, and systems biology."
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Coding/ Software
- Dask
- Docker - level virtualization to deliver software in packages called containers
- Statistics in R
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Neuroscience
- Neurosynth - scale, automated synthesis of functional magnetic resonance imaging (fMRI) data
- NEMAR
- BrainIAK
- ENIGMA toolbox - and macroscale data, Multiscale analytical workflows, 100+ ENIGMA-derived statistical maps
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AI: writing/ information searching
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Miscellaneous for Researchers
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General tools
- Sample Consent Forms for neuroimaging research
- Most Wiedzy/ Bridge of Knowledge - based system with collection of publications, studies, projects and a lot of other types of resources from a number of different subject areas (open-access)
- Journal Citation Reports - neutral data"
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Neuroscience
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Learning
- ReproNim Statistics Module - values and their issues / Statistical power in neuroimaging and statistical reproducibility / The positive Predictive Value / Cultural and psychological issues
- Seeing Theory
- Neuroscience Tutorials
- DataCamp
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Fellowships & Grants
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Coding/ Software
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Data visualisation
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AI: writing/ information searching
- BrainPainter
- HSLuv - friendly alternative to HSL
- Information is beautiful
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Publishing
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Predatory journals/publishers etc.
- Think-Check-Submit - sector initiative aims to educate researchers, promote integrity, and build trust in credible research and publications
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Initiatives, research groups, associations, labs, companies
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Predatory journals/publishers etc.
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Summer Schools
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Summer Schools / Courses / Hackathons etc.
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Other
- Neurohackademy
- Neuromatch - week program)) & Neuromatch Conference (a conference for the computational neuroscience community)
- Google Summer of Code
- DataCamp
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Conferences / Symposia
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Other
- AI in aging and age-related diseases - 13 November 2022, on-line and on-demand; deadline: 3 October 2022
- NEURONUS Neuroscience Forum - 17.10.2022)
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Initiatives, research groups, associations...
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Other
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Interesting companies & labs, internships, job advertisements, grants & travel grants
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Additional Resources:
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Journals (for Data Notes)
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Miscellaneous
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Other
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AI tools
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Predatory journals/publishers etc.
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Biohacking
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Predatory journals/publishers etc.
- Biohacking Brain Health
- Bulletproof Blog
- SelfHacked - based information on health, biohacking, and self-improvement.
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Productivity
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Predatory journals/publishers etc.
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Categories
Reading corner
129
Miscellaneous for Researchers
20
Tools
15
Open data movement
14
Open Data Science
8
Interesting companies & labs, internships, job advertisements, grants & travel grants
8
Additional Resources:
4
Summer Schools / Courses / Hackathons etc.
4
Data visualisation
3
Initiatives, research groups, associations, labs, companies
3
Biohacking
3
Initiatives, research groups, associations...
2
Conferences / Symposia
2
Productivity
1
AI tools
1
Miscellaneous
1
Publishing
1
Sub Categories
Articles
113
Other
18
Platforms
11
Unreliable Science (*and how to try overcome this issue)
11
Neuroscience
10
Journals (for Data Notes)
8
Predatory journals/publishers etc.
7
Fellowships & Grants
6
AI: writing/ information searching
6
General: research
5
Data Repositories (suitable for neuroimaging datasets)
4
Coding/ Software
4
Learning
4
General tools
3
Summer Schools
2
Other lists
2
Relaxing on a hammock under a tree...
1
Programming
1
Other articles
1
Design
1
Journals
1
Keywords
awesome
4
awesome-list
4
neuroscience
3
computational-neuroscience
2
open-science
2
list
2
brain
2
eeg
1
intelligence
1
machine-learning
1
matlab
1
meg
1
mooc
1
deep-neural-networks
1
nirs
1
python
1
computational-biology
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deep-learning
1
remarkable-tablet
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tutorials
1
resources
1
quickstart
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collection
1
science
1
open-datasets
1
open-data
1
computational-science
1
simulation-neuroscience
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neuroscience-methods
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neuroscience-data
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neuron-models
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neuroimaging-data
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neural-simulators
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neural-simulations
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electrophysiological-data
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