Sugar signals and molecular networks controlling plant growth

濡傞锛岀硸淇″彿鍜屼唬璋㈢綉缁滄帶鍒舵鐗╃敓闀跨殑缁艰堪

Bioinformatic and systems biology tools to generate testable models of signalling pathways and their targets

鍒╃敤鐢熺墿淇℃伅瀛﹀伐鍏凤紝缁撳悎杞綍缁勫铔嬬櫧缁勫鐨勪俊鎭紝濡備綍鏈夋晥寤虹珛淇″彿浼犲閫斿緞鐨勭綉缁滄ā鍨嬶紵璇ユ枃绔犺鐨勬槸鎷熷崡鑺ワ紝娑夊強寰堝缃戝潃銆佹暟鎹簱銆佽蒋浠讹紝鏈夊叴瓒ｇ殑鍙傝�冨惂銆�

Over the last years a number of bioinformatic software programs have been developed in the area of molecular biology. The application of these bioinformatic tools to the wealth of existing transcriptomic and proteomic data can be used to predict the structure and hierarchy of signalling pathways and gene networks. In genetically tractable model organisms such as Arabidopsis thaliana, these hyphotheses can be validated experimentally and modified in reiterative cycles, giving hypothesis-driven research high feasibility. These predictive systems biology approaches significantly reduce the scale, time and manpower usually required in classical approaches. Here, we provide an overview on the use of currently available tools in deciphering signalling pathways in Arabidopsis research.