{"title":"各种复杂生物网络可视化工具的研究","authors":"H. Alzahrani, S. Fernstad","doi":"10.1177/14738716231181545","DOIUrl":null,"url":null,"abstract":"Network biology has become crucial to understanding the complex structural characteristics of biological systems. Consequently, advanced visualization approaches are needed to support the investigation of such structures, and several network visualization tools have subsequently been developed to help researchers analyze intricate biological networks. While these tools support a range of analytical and interactive features, it is sometimes unclear to a data analyst or visualization designer which features are of most relevance to biologists. Thus, this study investigates and identifies essential factors for the visualization of complex biological networks using a mixed methodology approach. Based on the findings, essential factors were categorized as either generic and heuristic, where the former concern different analytical and interactive functionalities, such as an efficient layout, advanced search capabilities, plugin availability, graph analysis and user-friendliness, while the latter concern usability, such as information coding, flexibility, orientation and help.1 Furthermore, the findings indicate that 12 of the 15 generic factors identified were moderately important, while all 10 heuristic factors identified herein were moderately important.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":"22 1","pages":"323 - 339"},"PeriodicalIF":1.8000,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An investigation into various visualization tools for complex biological networks\",\"authors\":\"H. Alzahrani, S. Fernstad\",\"doi\":\"10.1177/14738716231181545\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Network biology has become crucial to understanding the complex structural characteristics of biological systems. Consequently, advanced visualization approaches are needed to support the investigation of such structures, and several network visualization tools have subsequently been developed to help researchers analyze intricate biological networks. While these tools support a range of analytical and interactive features, it is sometimes unclear to a data analyst or visualization designer which features are of most relevance to biologists. Thus, this study investigates and identifies essential factors for the visualization of complex biological networks using a mixed methodology approach. Based on the findings, essential factors were categorized as either generic and heuristic, where the former concern different analytical and interactive functionalities, such as an efficient layout, advanced search capabilities, plugin availability, graph analysis and user-friendliness, while the latter concern usability, such as information coding, flexibility, orientation and help.1 Furthermore, the findings indicate that 12 of the 15 generic factors identified were moderately important, while all 10 heuristic factors identified herein were moderately important.\",\"PeriodicalId\":50360,\"journal\":{\"name\":\"Information Visualization\",\"volume\":\"22 1\",\"pages\":\"323 - 339\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2023-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Visualization\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1177/14738716231181545\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Visualization","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1177/14738716231181545","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
An investigation into various visualization tools for complex biological networks
Network biology has become crucial to understanding the complex structural characteristics of biological systems. Consequently, advanced visualization approaches are needed to support the investigation of such structures, and several network visualization tools have subsequently been developed to help researchers analyze intricate biological networks. While these tools support a range of analytical and interactive features, it is sometimes unclear to a data analyst or visualization designer which features are of most relevance to biologists. Thus, this study investigates and identifies essential factors for the visualization of complex biological networks using a mixed methodology approach. Based on the findings, essential factors were categorized as either generic and heuristic, where the former concern different analytical and interactive functionalities, such as an efficient layout, advanced search capabilities, plugin availability, graph analysis and user-friendliness, while the latter concern usability, such as information coding, flexibility, orientation and help.1 Furthermore, the findings indicate that 12 of the 15 generic factors identified were moderately important, while all 10 heuristic factors identified herein were moderately important.
期刊介绍:
Information Visualization is essential reading for researchers and practitioners of information visualization and is of interest to computer scientists and data analysts working on related specialisms. This journal is an international, peer-reviewed journal publishing articles on fundamental research and applications of information visualization. The journal acts as a dedicated forum for the theories, methodologies, techniques and evaluations of information visualization and its applications.
The journal is a core vehicle for developing a generic research agenda for the field by identifying and developing the unique and significant aspects of information visualization. Emphasis is placed on interdisciplinary material and on the close connection between theory and practice.
This journal is a member of the Committee on Publication Ethics (COPE).