A graph-traversal approach to identify influential nodes in a network

Liu, Yan; Wei, Xiaoqi; Chen, Wenfang; Hu, Lianyu; He, Zengyou

doi:10.1016/j.patter.2021.100321

Cited by 11 publications

(5 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We identified paths in the MIM using a breadth-first-search (BFS) algorithm, one of the fastest possible solutions in a directed and unweighted graph 32 . In its standard form, the algorithm enables the search for shortest paths (ܵܲ) between two elements ሺ‫,ݑ‬ ‫ݒ‬ሻ ‫א‬ ܸ as a set of existing paths ܲ ௨,௩ between ‫ݑ‬ and ‫,ݒ‬ where ‫ܮ‬ሺܲ ௨,௩ ሻ is minimized.…”

Section: Topological Modelmentioning

confidence: 99%

In silicoInvestigation of Molecular Networks Linking Gastrointestinal Diseases, Malnutrition, and Sarcopenia

Ehlers

Bannert

Stanke

et al. 2022

Preprint

View full text Add to dashboard Cite

Malnutrition is a common primary or secondary complication in gastrointestinal diseases. The patient's nutritional status also influences muscle mass and function, which can be impaired up to the degree of sarcopenia. The molecular interactions in diseases leading to sarcopenia are complex and multifaceted, affecting muscle physiology, the intestine (nutrition), and the liver at different levels. Although extensive knowledge of individual molecular factors is available, their regulatory interplay is not yet fully understood. A comprehensive overall picture of pathological mechanisms and resulting phenotypes is lacking. In silico approaches that convert existing knowledge into computationally readable formats can help to unravel such complex systems. We compiled available experimental evidence for molecular interactions involved in the development of sarcopenia into a knowledge base, referred to as the Sarcopenia Map. By including specific diseases, namely liver cirrhosis, and intestinal dysfunction, and considering their effects on nutritional status and blood secretome, we investigated their contribution to the development of sarcopenia. The Sarcopenia Map is publicly available as an open-source, interactive online resource, providing tools that allow users to explore the information on the map and perform in silico perturbation experiments.

show abstract

Section: Topological Modelmentioning

confidence: 99%

In silicoInvestigation of Molecular Networks Linking Gastrointestinal Diseases, Malnutrition, and Sarcopenia

Ehlers

Bannert

Stanke

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…We use the MOS-index as a representative of centrality indices based on order statistics and compare it with popular centrality methods and two recently proposed centrality measures: DC [25], h-index [14], CC [30], BC [31], LC [32], PR [33], IC [34], TARank (DC) [35] and IVI [36], where k is set to be 2 in TARank (DC). Fig.…”

Section: The Comparison With the State-of-the-art Centrality Measuresmentioning

confidence: 99%

The statistical nature of h-index of a network node

Liu¹,

Mudi²,

Hu³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Evaluating the importance of a network node is a crucial task in network science and graph data mining. H-index is a popular centrality measure for this task, however, there is still a lack of its interpretation from a rigorous statistical aspect. Here we show the statistical nature of h-index from the perspective of order statistics, and we obtain a new family of centrality indices by generalizing the h-index along this direction. The theoretical and empirical evidence shows that such a statistical interpretation enables us to obtain a general and versatile framework for quantifying the importance of a network node. Under this framework, many new centrality indices can be derived and some of which can be more accurate and robust than h-index. We believe that this research opens up new avenues for developing more effective indices for node importance quantification from a viewpoint that still remains unexplored.

show abstract

“…We identified paths in the MIM using a breadth-firstsearch (BFS) algorithm, one of the fastest possible solutions in a directed and unweighted graph (43). In its standard form, the algorithm enables the search for shortest paths (SP) between two elements (u, v) ∈ V as a set of existing paths P u,v between u and v, where L(P u,v ) is minimized.…”

Section: Topological Modelingmentioning

confidence: 99%

In silico investigation of molecular networks linking gastrointestinal diseases, malnutrition, and sarcopenia

et al. 2022

View full text Add to dashboard Cite

Malnutrition (MN) is a common primary or secondary complication in gastrointestinal diseases. The patient’s nutritional status also influences muscle mass and function, which can be impaired up to the degree of sarcopenia. The molecular interactions in diseases leading to sarcopenia are complex and multifaceted, affecting muscle physiology, the intestine (nutrition), and the liver at different levels. Although extensive knowledge of individual molecular factors is available, their regulatory interplay is not yet fully understood. A comprehensive overall picture of pathological mechanisms and resulting phenotypes is lacking. In silico approaches that convert existing knowledge into computationally readable formats can help unravel mechanisms, underlying such complex molecular processes. From public literature, we manually compiled experimental evidence for molecular interactions involved in the development of sarcopenia into a knowledge base, referred to as the Sarcopenia Map. We integrated two diseases, namely liver cirrhosis (LC), and intestinal dysfunction, by considering their effects on nutrition and blood secretome. We demonstrate the performance of our model by successfully simulating the impact of changing dietary frequency, glycogen storage capacity, and disease severity on the carbohydrate and muscle systems. We present the Sarcopenia Map as a publicly available, open-source, and interactive online resource, that links gastrointestinal diseases, MN, and sarcopenia. The map provides tools that allow users to explore the information on the map and perform in silico simulations.

show abstract

A graph-traversal approach to identify influential nodes in a network

Cited by 11 publications

References 56 publications

In silicoInvestigation of Molecular Networks Linking Gastrointestinal Diseases, Malnutrition, and Sarcopenia

In silicoInvestigation of Molecular Networks Linking Gastrointestinal Diseases, Malnutrition, and Sarcopenia

The statistical nature of h-index of a network node

In silico investigation of molecular networks linking gastrointestinal diseases, malnutrition, and sarcopenia

Contact Info

Product

Resources

About