A Multi-Parameter Analysis of Cellular Coordination of Major Transcriptome Regulation Mechanisms.

To understand cellular coordination of multiple transcriptome regulation mechanisms, we simultaneously measured transcription rate (TR), mRNA abundance (RA) and translation activity (TA). This revealed multiple insights. First, the three parameters displayed systematic statistical differences.

Relationship between gene duplicability and diversifiability in the topology of biochemical networks.

Background: Selective gene duplicability, the extensive expansion of a small number of gene families, is universal. Quantitatively, the number of genes (P(K)) with K duplicates in a genome decreases precipitously as K increases, and often follows a power law (P(k)∝k-α). Functional diversification, either neo- or sub-functionalization, is a major evolution route for duplicate genes.

Optimization of time-course experiments for kinetic model discrimination.

Systems biology relies heavily on the construction of quantitative models of biochemical networks. These models must have predictive power to help unveiling the underlying molecular mechanisms of cellular physiology, but it is also paramount that they are consistent with the data resulting from key experiments. Often, it is possible to find several models that describe the data equally well, but provide significantly different quantitative predictions regarding particular variables of the network.

Metabolic impact of redox cofactor perturbations in Saccharomyces cerevisiae.

Redox cofactors play a pivotal role in coupling catabolism with anabolism and energy generation during metabolism. There exists a delicate balance in the intracellular level of these cofactors to ascertain an optimal metabolic output. Therefore, cofactors are emerging to be attractive targets to induce widespread changes in metabolism.