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BRAPH 2: a flexible, open-source, reproducible, community-oriented, easy-to-use framework for network analyses in neurosciences

Chang, Y.-W.; Zufiria-Gerboles, B.; Gomez-Ruiz, P. E.; Canal-Garcia, A.; Zhao, H.; Mijalkov, M.; Braga Pereira, J.; Volpe, G.

2025-04-14 neuroscience
10.1101/2025.04.11.648455 bioRxiv
Show abstract

As network analyses in neuroscience continue to grow in both complexity and size, flexible methods are urgently needed to provide unbiased, reproducible insights into brain function. BRAPH 2 is a versatile, open-source framework that meets this challenge by offering streamlined workflows for advanced statistical models and deep learning in a community-oriented environment. Through its Genesis compiler, users can build specialized distributions with custom pipelines, ensuring flexibility and scalability across diverse research domains. These powerful capabilities will ensure reproducibility and accelerate discoveries in neuroscience.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

1
Neuroinformatics
○ 46 papers in training set
Top 0.1%
12.4%
Similar papers in this journal
2
PLOS Computational Biology
● 1863 papers in training set
Top 5%
7.7%
Similar papers in this journal
3
Frontiers in Neuroinformatics
○ 41 papers in training set
Top 0.1%
6.1%
Similar papers in this journal
4
Nature Methods
○ 385 papers in training set
Top 2%
6.1%
Similar papers in this journal
5
Imaging Neuroscience
● 282 papers in training set
Top 1%
4.3%
Similar papers in this journal
6
Patterns
○ 78 papers in training set
Top 0.3%
4.2%
7
NeuroImage
○ 903 papers in training set
Top 3%
3.4%
8
PLOS ONE
● 5266 papers in training set
Top 35%
3.4%
9
Network Neuroscience
● 126 papers in training set
Top 0.6%
3.2%
50% of probability mass above
10
GigaScience
◐ 212 papers in training set
Top 1%
3.2%
11
Scientific Reports
○ 3612 papers in training set
Top 39%
2.6%
12
Aperture Neuro
● 20 papers in training set
Top 0.1%
2.6%
13
eLife
● 5828 papers in training set
Top 43%
2.4%
14
Frontiers in Psychiatry
○ 87 papers in training set
Top 0.9%
2.4%
15
eneuro
● 439 papers in training set
Top 3%
2.4%
16
Human Brain Mapping
○ 329 papers in training set
Top 2%
2.3%
17
Nature Computational Science
○ 55 papers in training set
Top 0.4%
2.3%
18
IEEE Journal of Biomedical and Health Informatics
● 37 papers in training set
Top 0.5%
2.3%
19
SoftwareX
○ 15 papers in training set
Top 0.1%
2.1%
20
Nature Communications
○ 5641 papers in training set
Top 49%
1.3%
21
BMC Bioinformatics
○ 457 papers in training set
Top 4%
1.3%
22
Alzheimer's & Dementia
177 papers in training set
Top 2%
1.1%
23
Brain Informatics
○ 10 papers in training set
Top 0.2%
1.1%
24
Frontiers in Neuroscience
○ 256 papers in training set
Top 5%
1.1%
25
Communications Biology
○ 993 papers in training set
Top 25%
1.0%
26
Journal of Neuroscience Methods
○ 122 papers in training set
Top 2%
1.0%
27
Medical Image Analysis
○ 35 papers in training set
Top 0.7%
0.8%
28
Journal of the American Medical Informatics Association
◐ 71 papers in training set
Top 2%
0.8%
29
Frontiers in Neuroimaging
○ 11 papers in training set
Top 0.2%
0.8%
30
PLOS Biology
● 486 papers in training set
Top 14%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.