Activity of Japanese Society of Grassland Science

The Japanese Society of Grassland Science (JSGS) was founded in 1954 for the purposes of progressing grassland and forage crop sciences and fostering grassland agriculture and better management of grassland for animal production in Japan. From the first, the members of JSGS have included interdisciplinary scientists from forage crop science, forestry, animal science, agribusiness and many related fields. In the 50 years since its foundation, JSGS has made large contributions to the progress of both science and industry in Japan. The number of JSGS members is now declining slightly, but there are still about 950 including 800 individual members and 150 organisations or private companies. The profile of the current members is mainly scientists working in university or governmental and private research institutes

DDBJ dealing with mass data produced by the second generation sequencer

DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) collected and released 2 368 110 entries or 1 415 106 598 bases in the period from July 2007 to June 2008. The releases in this period include genome scale data of Bombyx mori, Oryzas latipes, Drosophila and Lotus japonicus. In addition, from this year we collected and released trace archive data in collaboration with National Center for Biotechnology Information (NCBI). The first release contains those of O. latipes and bacterial meta genomes in human gut. To cope with the current progress of sequencing technology, we also accepted and released more than 100 million of short reads of parasitic protozoa and their hosts that were produced by using a Solexa sequencer

Consistency and diversity of spike dynamics in the neurons of bed nucleus of Stria Terminalis of the rat: a dynamic clamp study

Neurons display a high degree of variability and diversity in the expression and regulation of their voltage-dependent ionic channels. Under low level of synaptic background a number of physiologically distinct cell types can be identified in most brain areas that display different responses to standard forms of intracellular current stimulation. Nevertheless, it is not well understood how biophysically different neurons process synaptic inputs in natural conditions, i.e., when experiencing intense synaptic bombardment in vivo. While distinct cell types might process synaptic inputs into different patterns of action potentials representing specific "motifs'' of network activity, standard methods of electrophysiology are not well suited to resolve such questions. In the current paper we performed dynamic clamp experiments with simulated synaptic inputs that were presented to three types of neurons in the juxtacapsular bed nucleus of stria terminalis (jcBNST) of the rat. Our analysis on the temporal structure of firing showed that the three types of jcBNST neurons did not produce qualitatively different spike responses under identical patterns of input. However, we observed consistent, cell type dependent variations in the fine structure of firing, at the level of single spikes. At the millisecond resolution structure of firing we found high degree of diversity across the entire spectrum of neurons irrespective of their type. Additionally, we identified a new cell type with intrinsic oscillatory properties that produced a rhythmic and regular firing under synaptic stimulation that distinguishes it from the previously described jcBNST cell types. Our findings suggest a sophisticated, cell type dependent regulation of spike dynamics of neurons when experiencing a complex synaptic background. The high degree of their dynamical diversity has implications to their cooperative dynamics and synchronization

eGenomics: Cataloguing our complete genome collection III

This meeting report summarizes the proceedings of the “eGenomics: Cataloguing our Complete Genome Collection III” workshop held September 11–13, 2006, at the National Institute for Environmental eScience (NIEeS), Cambridge, United Kingdom. This 3rd workshop of the Genomic Standards Consortium was divided into two parts. The first half of the three-day workshop was dedicated to reviewing the genomic diversity of our current and future genome and metagenome collection, and exploring linkages to a series of existing projects through formal presentations. The second half was dedicated to strategic discussions. Outcomes of the workshop include a revised “Minimum Information about a Genome Sequence” (MIGS) specification (v1.1), consensus on a variety of features to be added to the Genome Catalogue (GCat), agreement by several researchers to adopt MIGS for imminent genome publications, and an agreement by the EBI and NCBI to input their genome collections into GCat for the purpose of quantifying the amount of optional data already available (e.g., for geographic location coordinates) and working towards a single, global list of all public genomes and metagenomes

Predicting Secondary Structures, Contact Numbers, and Residue-wise Contact Orders of Native Protein Structure from Amino Acid Sequence by Critical Random Networks

Prediction of one-dimensional protein structures such as secondary structures and contact numbers is useful for the three-dimensional structure prediction and important for the understanding of sequence-structure relationship. Here we present a new machine-learning method, critical random networks (CRNs), for predicting one-dimensional structures, and apply it, with position-specific scoring matrices, to the prediction of secondary structures (SS), contact numbers (CN), and residue-wise contact orders (RWCO). The present method achieves, on average, $Q_3$ accuracy of 77.8% for SS, correlation coefficients of 0.726 and 0.601 for CN and RWCO, respectively. The accuracy of the SS prediction is comparable to other state-of-the-art methods, and that of the CN prediction is a significant improvement over previous methods. We give a detailed formulation of critical random networks-based prediction scheme, and examine the context-dependence of prediction accuracies. In order to study the nonlinear and multi-body effects, we compare the CRNs-based method with a purely linear method based on position-specific scoring matrices. Although not superior to the CRNs-based method, the surprisingly good accuracy achieved by the linear method highlights the difficulty in extracting structural features of higher order from amino acid sequence beyond that provided by the position-specific scoring matrices.Comment: 20 pages, 1 figure, 5 tables; minor revision; accepted for publication in BIOPHYSIC

Collective dynamics of two-mode stochastic oscillators

We study a system of two-mode stochastic oscillators coupled through their collective output. As a function of a relevant parameter four qualitatively distinct regimes of collective behavior are observed. In an extended region of the parameter space the periodicity of the collective output is enhanced by the considered coupling. This system can be used as a new model to describe synchronization-like phenomena in systems of units with two or more oscillation modes. The model can also explain how periodic dynamics can be generated by coupling largely stochastic units. Similar systems could be responsible for the emergence of rhythmic behavior in complex biological or sociological systems.Comment: 4 pages, RevTex, 5 figure