Quantitative biology: from genes, cells to networks

Abstract

Quantitative biology is an exciting emerging field that focuses on using systematic and quantitative approaches and technologies to analyze and integrate biological systems, construct and model engineered life systems, and even manipulate biological processes and functions. The advance of high-throughput biotechnologies has shifted the paradigm of biological researches from focusing on intricacies of molecular components to understanding how biological systems function in terms of modules and networks. On October 13-17 in 2014, more than 200 participants gathered at Cold Spring Harbor Asia Conference on Quantitative Biology in Suzhou, China, to exchange and discuss recent advances in quantitatively understanding of biological systems at the scale of genes, cells, and integrated networks. The conference was led by Michael Q. Zhang (University of Texas at Dallas, USA; Tsinghua University, China), Chao Tang (Peking University, China) and Terence Hwa (University of California San Diego, USA). In this report, we highlighted a few themes among 32 oral presentations and 34 poster presentations brought by this conference. PROCEEDING AND HIGHLIGHT TALKS Regulatory interactionsThe first lecture was given by Dr. Johan Elf (Uppsala University, Sweden). Dr. Elf demonstrated an assay for measuring the rate of dissociation for a LacI repressor from an individual chromosomal operator site at the level of individual molecules in E. coli. By combining with the corresponding association rate measurement [1], Dr. Elf tested the commonly used assumption that transcription factor (TF) kinetics can be considered to be at equilibrium and that the gene expression is proportional to the time the operator is free. In the second talk of this section, Dr. Gary D. Stormo (Washington University, USA) presented his recent progress in determining optimal models for transcription factor specificity by a newly developed experimental method, Spec-seq and the corresponding algorithms for data analysis [2,3]. The Spec-seq offered unprecedented accuracy for determining relative binding affinities to thousands of binding sites in parallel, which helped uncover new findings regarding the binding characteristics of Lac repressor [4]. In Dr. Hualin Shi's lecture (Institute of Theoretical Physics, Chinese Academy of Sciences, China), he quantified sequence-function relations for small RNA mediated gene silencing using the well-characterized small RNA RyhB and its target sodB in E. coli [5]. His results support the applicability of the thermodynamic model in predicting RNA-RNA interaction and suggest that both the kinetic and thermodynamic process of base-pairing between sRNA and mRNA determines the regulatory level. Dr. Xiling Shen (Cornell University, USA) discussed how miR-34a controls the asymmetric division of colon cancer stem cells by using quantitative single-cell analysis [6]. He showed that miR-34a targets Numb to form an incoherent feedforward loop (IFFL), which enhances bimodality by orders of magnitude. In addition, he demonstrated that the IF...