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SORTED
SORTED: a curated list of interesting science ideas and links (cognitive/neuro & data science)
https://github.com/PTDZ/SORTED
Last synced: 3 days ago
JSON representation
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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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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
19
Tools
15
Open data movement
14
Open Data Science
9
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)
9
Predatory journals/publishers etc.
7
Fellowships & Grants
6
AI: writing/ information searching
6
General: research
5
Data Repositories (suitable for neuroimaging datasets)
4
Learning
4
General tools
3
Coding/ Software
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
1
deep-learning
1
remarkable-tablet
1
tutorials
1
resources
1
quickstart
1
collection
1
science
1
open-datasets
1
open-data
1
computational-science
1
simulation-neuroscience
1
neuroscience-methods
1
neuroscience-data
1
neuron-models
1
neuroimaging-data
1
neural-simulators
1
neural-simulations
1
electrophysiological-data
1