Bio Saga Blog - A Chronicle of Life Sciences & Informatics

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A new paper written by researchers from the Institute for Systems Biology describes a computational approach for studying regulatory activities in cells that relies on integrated networks of transcriptional and metabolic data. The study, published in PLOS Computational Biology earlier this month, describes software called the Gene Expression and Metabolism Integrated for Network Inference (GEMINI) which uses an integrated model of network and metabolic data to explore growth phenotypes in Saccharomyces cerevisiae . GEMINI builds on work from the same researchers published in 2010 in the Proceedings of the National Academy of Sciences . That paper describes the Probabilistic Regulation of Metabolism (PROM), which provides a mechanism for integrating transcriptional regulatory networks and metabolic networks in a single in silico model and using it to make predictions about phenotypes such as flux and growth rate. While based on PROM, GEMINI is designed to tackle a slightly dif...

Listeria TDRM Database http://www.lmtdrm.com/ . Please keep your comments and suggestions flowing in  kamesh@pronetinformatix.com The genus  Listeria  consists of a group of gram-positive bacteria of low G+C content closely related to  Bacillus, Clostridium, Enterococcus, Streptococcus,  and  Staphylococcus .  Listeria spp.   are facultative anaerobic rods of 0.4 by 1 to 1.5 µm that do not form spores, have no capsule and are motile at 10 to 25°C.  Listeria spp .  is isolated from a diversity of environmental sources, including soil, water, effluents, a large variety of foods, and the feces of humans and animals. The genus  Listeria  currently includes eight species:  L. monocytogenes ,  L. ivanovii ,  L. seeligeri , L.rocourtiace ,  L. innocua ,  L. welshimeri ,  L. marthii   and  L. grayi . Two of these species  L. monocytogenes  and  L. ivanovii  are potential...

Pathway analysis has become the first choice for gaining insight into the underlying biology of differentially expressed genes and proteins, as it reduces complexity and has increased explanatory power. We discuss the evolution of knowledge base–driven pathway analysis over its first decade, distinctly divided into three generations. We also discuss the limitations that are specific to each generation, and how they are addressed by successive generations of methods. We identify a number of annotation challenges that must be addressed to enable development of the next generation of pathway analysis methods. Furthermore, we identify a number of methodological challenges that the next generation of methods must tackle to take advantage of the technological advances in genomics and proteomics in order to improve specificity, sensitivity, and relevance of pathway analysis. Do you wish to know more?

Scientists at the University of Sheffield have shown how bacteria could be used as a future fuel. The research, published in the journal Bioinformatics, could have significant implications for the environment and the way we produce sustainable fuels in the future. Like all living creatures, bacteria sustain themselves through their metabolism, a huge sequence of chemical reactions that transform nutrients into energy and waste. Using mathematical computer models, the Sheffield team have mapped the metabolism of a type of bacteria called Nostoc. Nostoc fixes nitrogen and, in doing so, releases hydrogen that can then potentially be used as fuel. Fixing nitrogen is an energy intensive process and it wasn´t entirely clear exactly how the bacterium produces the energy it needs in order to perform. Now the new computer system has been used to map out how this happens. Until now, scientists have had difficulties identifying bacteria metabolic pathways. The bacterial metabolism is a huge netwo...