La Folie, Quo Vadis, Evo-Devo?

I spend a lot of time at meetings; it is probably a normal part of the ageing process. It also seems that some names are put onto a generic list of people who are often included in discussions on a wide range of topics. Personally I think that it is preferable, when asked, to anticipate in meetings or serve on committees rather than to remain on the outside and complain about the outcome. And if you do not fall asleep during the meeting but actively participate you will probably be invited to more. However, many meetings would be significantly more productive—and even more enjoyable—if all participants could adhere to some basic standards of behaviour.
I am serious about not sleeping. It always amazes me to see someone take a little nap right in the middle of a debate. Of course, the inevitable ringing of a mobile phone eventually wakes these sleepers up. There was a time when mobile phones were a rarity, followed quickly by the phase when their ring tones became the Muzak of meetings. Finally, and to everyone’s relief, the ‘mute’ button was discovered, but now a vibration signals a committee member to catapult out of the chair to the lobby while talking on the phone. This is a real disruption during discussions and it shows that the priority given to the phone puts the meeting in second place.

Systems biology is a new field in the molecular life sciences. It is new as molecular biology was in the fifties and as cell biology was in the seventies. In my definition, systems biology is a science that aims to elucidate the general principles that govern the emergence of biological function from the interactions of components of living systems. Biological function is defined as all it takes for an organism to survive momentarily and under various stresses that reflect what its ancestors have been subject to in evolution. The components are the biological macromolecules, largely (although not completely) encoded by the genome, or higher order aggregates of such components. Indeed, biology appears to be organized in a modular fashion. This is clear in the sense of structure, with examples such as the structure of catalytic units (enzymes), confinement units (membranous vesicles), and inheritable information (chromatin). It is less clear perhaps in the sense of units of function such as metabolic pathways, endocytosis and division. Yet, if only to make understanding by the human mind possible, systems biology also aims to understand cell function in terms of those well- and ill-defined higher order modules.

Transcriptional regulation networks in cells orchestrate gene expression. In this network the 'nodes' are operons, and each 'edge' is directed from an operon that encodes a transcription factor to an operon that it directly regulates (an operon is one or more genes transcribed on the same mRNA). We asked whether one can decompose such networks into basic building blocks. To accomplish this, we generalize the concept of motifs, widely used in analyzing sequences, to the level of networks. We define 'network motifs', patterns of interconnections that recur in many different parts of a network, at frequencies much higher than in randomized networks that preserve the number of incoming an outgoing edges for each node. We developed algorithms for detecting network motifs and applied them to one of the best-characterized regulation network, that of transcriptional interactions in Escherichia coli. We find that much of the network is composed of repeated appearances of three highly significant motifs. Each network motif has a specific function in determining gene expression, such as generating temporal expression programs and governing the responses to fluctuating external signals. The motifs also allow an easily interpretable view of the entire known transcriptional network of the organism. This work is available in pdf form. The transcriptional database contains 577 interactions between 116 TFs and 419 operons. It was based on an existing database (RegulonDB). We enhanced RegulonDB by an extensive literature search, adding 35 new TFs, including alternative sigma factors, and over a hundred new interactions from the literature. The dataset consists of established interactions in which a TF directly binds a regulatory site.

http://www.wretch.cc/album/show.php?i=tear2001&b=1&f=1135926837&p=1

http://www.wretch.cc/album/show.php?i=tear2001&b=1&f=1135926836&p=0
Network biology offers a quantifiable description of the networks that characterize various biological systems.Here we define the most basic network measures that allow us to compare and characterize different complex networks.

D. Rind

With the discovery of DNA, the completion of genome sequencing of a number of organisms, and the advent of powerful high-throughput measurement technologies such as microarrays, it is now commonly said that biology has gone through a revolution. But I also have heard it said that biology is only about to go through a scientific revolution, much as physics did in the 17th century. In messianic hopes, people foretell the coming of the Newton of biology, but it is up to us, the scientific community, to set the stage for that to happen.

作者: Joaquin (被收買了...orz) 看板: P_EL_HARZART
標題: 出國

作者: Joaquin (被收買了...orz) 看板: P_EL_HARZART
標題: 風城exile

作者: Joaquin (被收買了...orz) 看板: P_EL_HARZART
標題: 傻了