Iet Systems Biology

杂志介绍

Iet Systems Biology杂志介绍

《Iet Systems Biology》是一本以English为主的开放获取国际优秀期刊，中文名称系统生物学，本刊主要出版、报道生物-细胞生物学领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCI、SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为1.9，最新CiteScore 指数为2.8。

本刊近期中国学者发表的论文主要有：

• Research of the Abnormal Mechanism of Brain Functional Network in Early Mild Cognitive Impairment Patient

  Author: Qi, Dong; Wang, Weiping; Diao, Yapeng; Zhao, Wenxiu; Rong, Wenqin; Zhao, Haiyan

• Utilising Machine Learning and Single-Cell Analysis to Uncover SKCM Metastasis-Related Gene

  Author: Liao, Zhiwei; Chen, Weiming; He, Yingdi; Zheng, Yichen; Chen, Xiaonan; Shen, Han

• Application of Fast Integration Strategy for Multi-Omics Data and Limited Random Forest Model in Survival Prediction of Glioblastom

  Author: Liu, Ze; Wu, Yanhui; Wang, Shanshan; Lin, Fei; Wan, Lin; Song, Peng

• CFMF: A Clustering-Free Cell Marker Finder for Single-Cell Transcriptomic Dat

  Author: Yin, Shumin; Liu, Ke

英文介绍

Iet Systems Biology杂志英文介绍

IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.

The scope includes the following topics:

Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.