Bio Saga Blog - A Chronicle of Life Sciences & Informatics

Ridiculed by some, Gaia theory - the idea that all living and non-living components on earth work together to promote life - is gaining support. Earth is a perfect planet for life but, according to Gaia theory, this is no coincidence. From the moment life first appeared on Earth it has worked hard to make Earth a more comfortable place to live. Gaia theory suggests that the Earth and its natural cycles can be thought of like a living organism. When one natural cycle starts to go out of kilter other cycles work to bring it back, continually optimising the conditions for life on Earth. Named after the Greek Earth goddess, Gaia, the theory was developed in the 1960s by scientist Dr James Lovelock. At the time, Lovelock was working for Nasa, looking at methods of detecting life on Mars. The theory came about as a way of explaining why the Earth's atmosphere contains high levels of nitrogen and oxygen. Initially, Gaia theory was ignored, and then later ridiculed by scientists such as Ri...

In a paper called "Metagenome Annotation Using a Distributed Grid of Undergraduate Students" I just love this title! It's nerdy and cute, all at the same time. Says Sandra Porter . The paper describes a class where students from Marseilles University investigate the function of unidentified genes from a Global Ocean Sampling experiment. All the sequences are obtained from the environmental sequence division at the NCBI . French researchers describe their strategy for teaching undergraduate-level bioinformatics using cutting-edge genomic data and a Web-based learning tool. The students then annotated real metagenomic sequences from the Global Ocean Sampling experiment. "In return for their much-needed help sorting out oodles of DNA data, the undergrads gain a practical knowledge of the work involved in doing bioinformatics and metagenomics, and, most importantly of all, they get to experience what it's like to do real research," says Karen James at the Be...

A team of American and French researchers used systems biology to identify gene signatures predicting human immune responses to the yellow fever vaccine, YF-17D. The work appeared in an advanced online publication in Nature Immunology yesterday. Using high-throughput gene expression measurements, multiplex analysis of cytokines and chemokines, and multi-parameter flow cytometry, investigators tested samples taken from more than a dozen individuals in the days and weeks following their yellow fever vaccination. Computational modeling allowed them to come up with signatures predicting CD8+ T-cell and neutralizing antibody responses to YF-17D — insights into vaccine immunogenicity that may inform future vaccine research and development. “The identification of gene signatures that correlate with, and are capable of predicting, the magnitudes of the antigen-specific CD8+ T-cell and neutralizing antibody responses provides the first methodological evidence that vaccine-induced immune r...

The Computational Biology Unit (CBU) has been established to conduct top-level European research in bioinformatics, and to serve functional genomics research in Norway with relevant training and services. CBU is searching for an additional group leader. The group leader will carry out research in the field of computational biology/bioinformat ics and contribute to the overall objectives of CBU. The group leader should have a PhD and post-doctoral experience including a solid publication record in a relevant subject. Candidates will be evaluated with emphasis on their ability to raise external funding and to supervise and carry out research projects. The research profile of the candidate should be within a relevant area for CBU. Candidates with profiles in direction of systems biology will be preferred. The group leader will direct a research group consisting of Ph.D. and post-doctoral scientists. The CBU and its partners currently have bioinformatics research activities in the fields ...

The first effort to sequence a complete cancer genome has underscored the power of second-generation sequencing while further establishing the lack of a “killer software app” in the field. In the study, published this week in Nature , a team of 48 scientists at the Genome Center of Washington University and elsewhere sequenced a female patient’s acute myeloid leukemia genome and compared it to the genome of her biopsied skin as well as reference genomes to uncover 10 cancer-associated mutations — eight of which were previously unknown. The team used two high-throughput sequencing platforms — the Illumina Genome Analyzer and the Roche/454 FLX platform — and software tools such as Maq, Cross_Match, BLAT, and Decision Tree analysis. The team also did its own scripting and algorithm development in the course of the project, Rick Wilson, director of the Genome Sequencing Center at Washington University School of Medicine, said. The AML sequencing team applied several established soft...