scholarly journals Activity-Dependent Human Brain Coding/Noncoding Gene Regulatory Networks

Genetics ◽  
2012 ◽  
Vol 192 (3) ◽  
pp. 1133-1148 ◽  
Author(s):  
Leonard Lipovich ◽  
Fabien Dachet ◽  
Juan Cai ◽  
Shruti Bagla ◽  
Karina Balan ◽  
...  
2017 ◽  
Vol 145 ◽  
pp. S142
Author(s):  
Aslihan Dincer ◽  
Bin Zhang ◽  
Joel Dudley ◽  
David Gavin ◽  
Eric Schadt ◽  
...  

2015 ◽  
Vol 5 (11) ◽  
pp. e679-e679 ◽  
Author(s):  
A Dincer ◽  
D P Gavin ◽  
K Xu ◽  
B Zhang ◽  
J T Dudley ◽  
...  

Author(s):  
Nikolas Bernaola ◽  
Mario Michiels ◽  
Pedro Larrañaga ◽  
Concha Bielza

AbstractWe present FGES-Merge, a new method for learning the structure of gene regulatory networks via merging locally learned Bayesian networks, based on the fast greedy equivalent search algorithm. The method is competitive with the state of the art in terms of the recall of the true structure while also improving upon it in terms of speed, scaling up to the tens of thousands of variables and being able to use empirical knowledge about the topological structure of gene regulatory networks. We apply this method to learning the gene regulatory network for the full human genome using data from samples of different brain structures (from the Allen Human Brain Atlas). Our goal is to develop a Bayesian network model that predicts interactions between genes in a way that is clear to experts, following the current trends in interpretable artificial intelligence. To achieve this, we also present a new open-access visualization tool that facilitates the exploration of massive networks and can aid in finding nodes of interest for experimental tests.


2021 ◽  
pp. 1-19
Author(s):  
Loreta Medina ◽  
Antonio Abellán ◽  
Ester Desfilis

The pallium is the largest part of the telencephalon in amniotes, and comparison of its subdivisions across species has been extremely difficult and controversial due to its high divergence. Comparative embryonic genoarchitecture studies have greatly contributed to propose models of pallial fundamental divisions, which can be compared across species and be used to extract general organizing principles as well as to ask more focused and insightful research questions. The use of these models is crucial to discern between conservation, convergence or divergence in the neural populations and networks found in the pallium. Here we provide a critical review of the models proposed using this approach, including tetrapartite, hexapartite and double-ring models, and compare them to other models. While recognizing the power of these models for understanding brain architecture, development and evolution, we also highlight limitations and comment on aspects that require attention for improvement. We also discuss on the use of transcriptomic data for understanding pallial evolution and advise for better contextualization of these data by discerning between gene regulatory networks involved in the generation of specific units and cell populations versus genes expressed later, many of which are activity dependent and their expression is more likely subjected to convergent evolution.


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