雜志介紹

Iet Systems Biology雜志介紹

《Iet Systems Biology》是一本以English為主的開(kāi)放獲取國(guó)際優(yōu)秀期刊，中文名稱系統(tǒng)生物學(xué)，本刊主要出版、報(bào)道生物學(xué)-CELL BIOLOGY領(lǐng)域的研究動(dòng)態(tài)以及在該領(lǐng)域取得的各方面的經(jīng)驗(yàn)和科研成果，介紹該領(lǐng)域有關(guān)本專業(yè)的最新進(jìn)展，探討行業(yè)發(fā)展的思路和方法，以促進(jìn)學(xué)術(shù)信息交流，提高行業(yè)發(fā)展。該刊已被國(guó)際權(quán)威數(shù)據(jù)庫(kù)SCIE收錄，為該領(lǐng)域相關(guān)學(xué)科的發(fā)展起到了良好的推動(dòng)作用，也得到了本專業(yè)人員的廣泛認(rèn)可。該刊最新影響因子為1.9，最新CiteScore 指數(shù)為4.2。

本刊近期中國(guó)學(xué)者發(fā)表的論文主要有：

• Multiscale modeling biological systems.

  Author: Liu ZP, Chen L.

• Crosstalk between pathways enhances the controllability of signalling networks.

  Author: Wang D, Jin S, Zou X.

• Kinetic model of metabolic network for xiamenmycin biosynthetic optimisation.

  Author: Xu MJ, Chen YC, Xu J, Ao P, Zhu XM.

• Knowledge-based three-body potential for transcription factor binding site prediction.

  Author: Qin W, Zhao G, Carson M, Jia C, Lu H.

英文介紹

Iet Systems Biology雜志英文介紹

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.