A Faster Algorithm for Detecting Network Motifs

2005 ◽  
pp. 165-177 ◽  
Author(s):  
Sebastian Wernicke
Keyword(s):  
Network Motifs

Pathogenic Genes Selection Model of Genetic Disease based on Network Motifs Slicing Feedback

2019 ◽  
Vol 16 (5) ◽  
pp. 392-401
Author(s):  
Shengli Zhang ◽  
Zekun Tong ◽  
Haoyu Yin ◽  
Yifan Feng
Keyword(s):  
Genetic Disease ◽  
Drug Targets ◽  
Selection Model ◽  
Network Motifs ◽  
Gene Set ◽  
Pathway Network ◽  
Gene Pathway ◽  
Pathogenic Genes ◽  
Pathogenic Gene ◽  
Selection Of

Background: Finding the pathogenic gene is very important for understanding the pathogenesis of the disease, locating effective drug targets and improving the clinical level of medical treatment. However, the existing methods for finding the pathogenic genes still have limitations, for instance the computational complexity is high, and the combination of multiple genes and pathways has not been considered to search for highly related pathogenic genes and so on. Methods: We propose a pathogenic genes selection model of genetic disease based on Network Motifs Slicing Feedback (NMSF). We find a point set which makes the conductivity of the motif minimum then use it to substitute for the original gene pathway network. Based on the NMSF, we propose a new pathogenic genes selection model to expand pathogenic gene set. Results: According to the gene set we have obtained, selection of key genes will be more accurate and convincing. Finally, we use our model to screen the pathogenic genes and key pathways of liver cancer and lung cancer, and compare the results with the existing methods. Conclusion: The main contribution is to provide a method called NMSF which simplifies the gene pathway network to make the selection of pathogenic gene simple and feasible. The fact shows our result has a wide coverage and high accuracy and our model has good expeditiousness and robustness.

scholarly journals Study on Structural Characteristics of China’s Passenger Airline Network Based on Network Motifs Analysis

2019 ◽  
Vol 11 (9) ◽  
pp. 2484 ◽  
Author(s):  
Ying Jin ◽  
Ye Wei ◽  
Chunliang Xiu ◽  
Wei Song ◽  
Kaixian Yang
Keyword(s):  
Airline Industry ◽  
Structural Characteristics ◽  
Building Blocks ◽  
Development Stage ◽  
Network Motifs ◽  
Characteristic Analysis ◽  
Airline Networks ◽  
Airline Network ◽  
Industry Sustainability ◽  
Advanced Development

The air passenger transport network system is an important agent of social and economic connections between cities. Studying on the airline network structure and providing optimization strategies can improve the airline industry sustainability evolution. As basic building blocks of broad networks, the concept of network motifs is cited in this paper to apply to the structural characteristic analysis of the passenger airline network. The ENUMERATE SUBGRAPHS (G, k) algorithm is used to identify the motifs and anti-motifs of the passenger airline network in China. A total of 37 airline companies are subjected to motif identification and exploring the structural and functional characteristics of the airline networks corresponding to different motifs. These 37 airline companies are classified according to the motif concentration curves into three development stages, which include mono-centric divergence companies at the low-level development stage, transitional companies at the intermediate development stage, and multi-centric and hierarchical companies at the advanced development stage. Finally, we found that adjusting the number of proper network motifs is useful to optimize the overall structure of airline networks, which is profitable for air transport sustainable development.

scholarly journals Built to Last: Functional and Structural Mechanisms in the Moth Olfactory Network Mitigate Effects of Neural Injury

2021 ◽  
Vol 11 (4) ◽  
pp. 462
Author(s):  
Charles B. Delahunt ◽  
Pedro D. Maia ◽  
J. Nathan Kutz
Keyword(s):  
Brain Injuries ◽  
Hebbian Learning ◽  
Neuronal Damage ◽  
Neural Systems ◽  
Network Motifs ◽  
Neural Firing ◽  
Neural Injury ◽  
Axonal Pathology ◽  
Structural Mechanisms ◽  
Axonal Swellings

Most organisms suffer neuronal damage throughout their lives, which can impair performance of core behaviors. Their neural circuits need to maintain function despite injury, which in particular requires preserving key system outputs. In this work, we explore whether and how certain structural and functional neuronal network motifs act as injury mitigation mechanisms. Specifically, we examine how (i) Hebbian learning, (ii) high levels of noise, and (iii) parallel inhibitory and excitatory connections contribute to the robustness of the olfactory system in the Manduca sexta moth. We simulate injuries on a detailed computational model of the moth olfactory network calibrated to data. The injuries are modeled on focal axonal swellings, a ubiquitous form of axonal pathology observed in traumatic brain injuries and other brain disorders. Axonal swellings effectively compromise spike train propagation along the axon, reducing the effective neural firing rate delivered to downstream neurons. All three of the network motifs examined significantly mitigate the effects of injury on readout neurons, either by reducing injury’s impact on readout neuron responses or by restoring these responses to pre-injury levels. These motifs may thus be partially explained by their value as adaptive mechanisms to minimize the functional effects of neural injury. More generally, robustness to injury is a vital design principle to consider when analyzing neural systems.

scholarly journals Network motifs in integrated cellular networks of transcription-regulation and protein-protein interaction

2004 ◽  
Vol 101 (16) ◽  
pp. 5934-5939 ◽  
Author(s):  
E. Yeger-Lotem ◽  
S. Sattath ◽  
N. Kashtan ◽  
S. Itzkovitz ◽  
R. Milo ◽  
...  
Keyword(s):  
Transcription Regulation ◽  
Cellular Networks ◽  
Protein Interaction ◽  
Network Motifs ◽  
Protein Protein Interaction

scholarly journals Simple network motifs can capture key characteristics of the floral transition inArabidopsis

2013 ◽  
Vol 8 (11) ◽  
pp. e26149 ◽  
Author(s):  
Nick Pullen ◽  
Katja E Jaeger ◽  
Philip A Wigge ◽  
Richard J Morris
Keyword(s):  
Floral Transition ◽  
Network Motifs ◽  
Key Characteristics ◽  
Simple Network

scholarly journals Pattern formation by dynamically interacting network motifs

2009 ◽  
Vol 106 (9) ◽  
pp. 3213-3218 ◽  
Author(s):  
J. Lembong ◽  
N. Yakoby ◽  
S. Y. Shvartsman
Keyword(s):  
Pattern Formation ◽  
Network Motifs
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