生物谷报道：现代的生物信息学技术已经使人类更清晰认识到生命的机制。最新一期PNAS报道了中国台湾学者李文雄（音译）最新研究成果，采用统计学方法成功鉴定出酵母的细胞周期中的转录因子网络。通过生物信息学手段成功预测了50个酵母细胞周期转录因子之间相互作用的规律。这一研究成果将为生物信息学在生命科学领域中的更深入应用提供更广泛的基础的。
生物信息学的应用解决了传统的生物学方法所不能解决的生命网络和系统生物学等问题。
专栏：系统生物学进展
Fig. 1. The regulatory behaviors of 50 known or putative yeast cell cycle TFs. The descriptions are from Tables 1, 2, 3, 4 and 9 and the literature. TF in red (blue) means that genes in G are expressed significantly higher (lower) than genes in G-. TF in black means that, although it is not identified by the first method (detection of individual TFs), it is detected by the second method (detection of synergistic pairs). A TF filled with green means a known cell cycle TF, yellow means highly confident, and gray means plausible. An edge connecting two TFs implies that the two TFs are synergistic according to our analysis. An edge (,) in red (blue) means that TFs and have positive (negative) synergy; plausible pairs are in thin lines, and highly confident pairs are in thick lines. A synergistic pair in green means supported by literature, and a synergistic pair in yellow means consistent with predictions of other studies.
