Condensin goes with the family but not with the flow

Condensin and cohesin are loaded onto yeast chromosomes by a common mechanism at RNA polymerase III transcribed genes. Whereas cohesin translocates from these loading sites to mediate cohesion at secondary locations, condensin remains, bringing distant sites together into clusters.     

Ciliate biology: dynamin goes nuclear

Dynamin and dynamin-related proteins (DRPs) mediate an array of membrane fission processes. A Tetrahymena DRP has adopted a new role, assisting in nuclear differentiation, a finding that further highlights these proteins - and this ciliate - as biological innovators.     

The flow of cytometry into systems biology.

Biomedical research is evolving to address biological systems as molecular pathways integrated into complex networks. Tools for molecular and cell analysis are also evolving to address the new challenges and opportunities of this approach. Flow cytometry is a versatile analytical platform, capable of high speed quantitative measurements of cells and other particles. These capabilities are being exploited and extended in a range of new applications stemming from opportunities presented by the advances of genomics, proteomics and systems biology, which are in turn impacting clinical diagnosis, vaccine development and drug discovery. In this review, we highlight some of these advances and consider the future evolution of flow cytometry technology.     

Software for systems biology: from tools to integrated platforms

Understanding complex biological systems requires extensive support from software tools. Such tools are needed at each step of a systems biology computational workflow, which typically consists of data handling, network inference, deep curation, dynamical simulation and model analysis. In addition, there are now efforts to develop integrated software platforms, so that tools that are used at different stages of the workflow and by different researchers can easily be used together. This Review describes the types of software tools that are required at different stages of systems biology research and the current options that are available for systems biology researchers. We also discuss the challenges and prospects for modelling the effects of genetic changes on physiology and the concept of an integrated platform.     

Bridging the gaps in systems biology

Systems biology aims at creating mathematical models, i.e., computational reconstructions of biological systems and processes that will result in a new level of understanding—the elucidation of the basic and presumably conserved “design” and “engineering” principles of biomolecular systems. Thus, systems biology will move biology from a phenomenological to a predictive science. Mathematical modeling of biological networks and processes has already greatly improved our understanding of many cellular processes. However, given the massive amount of qualitative and quantitative data currently produced and number of burning questions in health care and biotechnology needed to be solved is still in its early phases. The field requires novel approaches for abstraction, for modeling bioprocesses that follow different biochemical and biophysical rules, and for combining different modules into larger models that still allow realistic simulation with the computational power available today. We have identified and discussed currently most prominent problems in systems biology: (1) how to bridge different scales of modeling abstraction, (2) how to bridge the gap between topological and mechanistic modeling, and (3) how to bridge the wet and dry laboratory gap. The future success of systems biology largely depends on bridging the recognized gaps.     

Software agents in molecular computational biology

Progress made in applying agent systems to molecular computational biology is reviewed and strategies by which to exploit agent technology to greater advantage are investigated. Communities of software agents could play an important role in helping genome scientists design reagents for future research. The advent of genome sequencing in cattle and swine increases the complexity of data analysis required to conduct research in livestock genomics. Databases are always expanding and semantic differences among data are common. Agent platforms have been developed to deal with generic issues such as agent communication, life cycle management and advertisement of services (white and yellow pages). This frees computational biologists from the drudgery of having to re-invent the wheel on these common chores, giving them more time to focus on biology and bioinformatics. Agent platforms that comply with the Foundation for Intelligent Physical Agents (FIPA) standards are able to interoperate. In other words, agents developed on different platforms can communicate and cooperate with one another if domain-specific higher-level communication protocol details are agreed upon between different agent developers. Many software agent platforms are peer-to-peer, which means that even if some of the agents and data repositories are temporarily unavailable, a subset of the goals of the system can still be met. Past use of software agents in bioinformatics indicates that an agent approach should prove fruitful. Examination of current problems in bioinformatics indicates that existing agent platforms should be adaptable to novel situations.     

Integrating systems biology with clinical research

A report on the conference 'Systems Genomics 2008', Heidelberg, Germany, 2-3 May 2008.     

Imaging in systems biology

Most systems biology approaches involve determining the structure of biological circuits using genomewide "-omic" analyses. Yet imaging offers the unique advantage of watching biological circuits function over time at single-cell resolution in the intact animal. Here, we discuss the power of integrating imaging tools with more conventional -omic approaches to analyze the biological circuits of microorganisms, plants, and animals.     

Structures in systems biology

Oil and water do not normally mix, and apparently structural biology and systems biology look like two different universes. It can be argued that structural biology could play a very important role in systems biology. Although at the final stage of understanding a signal transduction pathway, a cell, an organ or a living system, structures could be obviated, we need them to be able to reach that stage. Structures of macromolecules, especially molecular machines, could provide quantitative parameters, help to elucidate functional networks or enable rational designed perturbation experiments for reverse engineering. The role of structural biology in systems biology should be to provide enough understanding so that macromolecules can be translated into dots or even into equations devoid of atoms.     

Putting the systems back into systems biology

In recent years the term "systems biology" has become widespread in the biological literature, but most of the papers in which these words appear have surprisingly little to do with older notions of biological systems: they often seem to imply little more than reductionist biology applied on a large scale, with a little attention to interactions between some of the components, but with minimal attention to the kinetic properties of enzymes, which supplied much of the reductionist foundation of biochemistry. A systemic approach to biology ought to put the emphasis on the entire system; insofar as it is concerned with components at all, it is to explain their roles in meeting the needs of the system as a whole. Genuinely systemic thinking allows us to understand how biochemical systems are regulated, and why clumsy attempts to manipulate them for biotechnological purposes may fail. At a more abstract level, it is necessary for understanding the nature of life, because as long as an organism is treated as no more than a collection of components, one cannot ask the right questions, and certainly cannot answer them.     

Interfacing systems biology and synthetic biology

A report of BioSysBio 2009, the IET conference on Synthetic Biology, Systems Biology and Bioinformatics, Cambridge, UK, 23-25 March 2009.