scholarly journals Identification of Novel Thyroid Cancer-Related Genes and Chemicals Using Shortest Path Algorithm

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Yang Jiang ◽  
Peiwei Zhang ◽  
Li-Peng Li ◽  
Yi-Chun He ◽  
Ru-jian Gao ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Shortest Path ◽  
Disease Genes ◽  
Shortest Path Algorithm ◽  
The Past ◽  
Disease Identification ◽  
Effective Treatments

Thyroid cancer is a typical endocrine malignancy. In the past three decades, the continued growth of its incidence has made it urgent to design effective treatments to treat this disease. To this end, it is necessary to uncover the mechanism underlying this disease. Identification of thyroid cancer-related genes and chemicals is helpful to understand the mechanism of thyroid cancer. In this study, we generalized some previous methods to discover both disease genes and chemicals. The method was based on shortest path algorithm and applied to discover novel thyroid cancer-related genes and chemicals. The analysis of the final obtained genes and chemicals suggests that some of them are crucial to the formation and development of thyroid cancer. It is indicated that the proposed method is effective for the discovery of novel disease genes and chemicals.

scholarly journals A Graphic Method for Identification of Novel Glioma Related Genes

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Yu-Fei Gao ◽  
Yang Shu ◽  
Lei Yang ◽  
Yi-Chun He ◽  
Li-Peng Li ◽  
...  
Keyword(s):  
Shortest Path ◽  
Protein Interaction ◽  
Biological Process ◽  
Weighted Graph ◽  
Intracranial Tumor ◽  
Graphic Method ◽  
Shortest Path Algorithm ◽  
Protein Protein Interaction ◽  
Serious Disease ◽  
Effective Treatments

Glioma, as the most common and lethal intracranial tumor, is a serious disease that causes many deaths every year. Good comprehension of the mechanism underlying this disease is very helpful to design effective treatments. However, up to now, the knowledge of this disease is still limited. It is an important step to understand the mechanism underlying this disease by uncovering its related genes. In this study, a graphic method was proposed to identify novel glioma related genes based on known glioma related genes. A weighted graph was constructed according to the protein-protein interaction information retrieved from STRING and the well-known shortest path algorithm was employed to discover novel genes. The following analysis suggests that some of them are related to the biological process of glioma, proving that our method was effective in identifying novel glioma related genes. We hope that the proposed method would be applied to study other diseases and provide useful information to medical workers, thereby designing effective treatments of different diseases.

Algorithm 1015

2021 ◽  
Vol 47 (2) ◽  
pp. 1-27
Author(s):  
Stefan Guthe ◽  
Daniel Thuerck
Keyword(s):  
Shortest Path ◽  
Assignment Problem ◽  
Parallel Implementation ◽  
Shortest Path Algorithm ◽  
Cost Matrix ◽  
The Past ◽  
Path Search ◽  
Dual Variables ◽  
The Cost ◽  
Real World Problems

We present a new algorithm for solving the dense linear (sum) assignment problem and an efficient, parallel implementation that is based on the successive shortest path algorithm. More specifically, we introduce the well-known epsilon scaling approach used in the Auction algorithm to approximate the dual variables of the successive shortest path algorithm prior to solving the assignment problem to limit the complexity of the path search. This improves the runtime by several orders of magnitude for hard-to-solve real-world problems, making the runtime virtually independent of how hard the assignment is to find. In addition, our approach allows for using accelerators and/or external compute resources to calculate individual rows of the cost matrix. This enables us to solve problems that are larger than what has been reported in the past, including the ability to efficiently solve problems whose cost matrix exceeds the available systems memory. To our knowledge, this is the first implementation that is able to solve problems with more than one trillion arcs in less than 100 hours on a single machine.

Utilizing Restricted Direction Strategy and Binary Heap Technology to Optimize Dijkstra Algorithm in WebGIS

2009 ◽  
Vol 419-420 ◽  
pp. 557-560 ◽  
Author(s):  
Rui Li
Keyword(s):  
Shortest Path ◽  
Operating Efficiency ◽  
Dijkstra Algorithm ◽  
Shortest Path Algorithm ◽  
Research Focus ◽  
Network Information ◽  
The Core ◽  
Highway Network ◽  
Core Issue ◽  
Storage Structures

Shortest path is the core issue in application of WebGIS. Improving the efficiency of the algorithm is an urgent requirement to be resolved at present. By the lossy algorithm analyzing, which is the current research focus of the shortest path algorithm to optimize, utilizing adjacency table of storage structures, restricted direction strategy and binary heap technology to optimize the algorithm, thereby reduce the scale of algorithm to improve the operating efficiency of algorithm. This scheme has been applied in the simulation of the data downloaded from the Guangdong Provincial Highway Network Information System and satisfactory results have been obtained.

scholarly journals Shortest path algorithm for optimal sectioning of hydrocarbon transport pipeline

2016 ◽  
Vol 49 (12) ◽  
pp. 532-537
Author(s):  
A. Cano-Acosta ◽  
John Fontecha ◽  
Nubia Velasco ◽  
Felipe Muñoz-Giraldo
Keyword(s):  
Shortest Path ◽  
Shortest Path Algorithm ◽  
Hydrocarbon Transport
Sign in / Sign up

Export Citation Format

Share Document