Archive by category | Networks

[Research highlight] modENCODE releases extensive functional investigation of fly and worm genomes

Recently, a series of publications by members of the modENCODE consortium were released online at Science, Nature, and Genome Research. These works collectively describe a massive effort to functionally characterize and annotate the Drosophila melanogaster and Caenorhabditis elegans genomes, including in-depth analyses of genes and transcripts, epigenetic marks, transcription factor binding, and replication timing, across a range of developmental and tissue sources.  Read more

Keystone Symposium – Omics Meets Cell Biology (II)

Keystone Symposium – Omics Meets Cell Biology (II)

Before I carry on with a summary of the second part of the Keystone Symposium ‘Omics Meets Cell Biology’, I should clarify that this post and the previous one dedicated to this conference are not intended to provide an comprehensive account of all the talks but rather to communicate some general (and subjective) impressions of the meeting. To keep these posts reasonably short (and sometimes due to a lack of memory…), I had to omit several of the excellent presentations given at this meeting. The full program and complete list of speakers is available at the Keystone Symposium website.  Read more

Keystone Symposium – Omics Meets Cell Biology (I)

Keystone Symposium – Omics Meets Cell Biology (I)

At the Keystone Symposium ‘OMICS Meets Cell Biology’, held this week in Breckenridge, Colorado, attendees had initially to face two major challenges: the first was to survive the cocktail mixing jet lag and altitude sickness and the second one—oh, it hurts!— was to resist the temptation to just forget all about science and focus exclusively on the concepts revolving around snow, slopes and fun sports…  … Read more

The role of neutral mutations in the evolution of phenotypes

The role of neutral mutations in the evolution of phenotypes

In a recent opinion piece, Andreas Wagner tries to reconcile the tension between proponents of neutral evolution and selectionism (Wagner 2008). He argues that “neutral mutations prepare the ground for later evolutionary innovation”. Wagner illustrates this point using a network model of genotype-phenotype relationships (Wagner 2005). In a so-called ‘neutral network’, nodes correspond to distinct genotypes associated with the same phenotype and are connected by an edge if the respective genotypes differ only by a single mutation event (eg point mutation). Examples of neutral networks include different genotypes coding for RNA or protein structures. In this representation, highly connected networks correspond to robust phenotypes that are not very sensitive to changes in genotype. Wagner notes the zinc finger fold as an impressive example of a highly connected neutral network as its structure remains essentially the same even after mutating all but seven of its 26 residues to alanine.  Read more

Top-down mapping of gene regulatory pathways

Top-down mapping of gene regulatory pathways

In a very recent lecture (see full video from NIH VideoCasting) given for the NIH Systems Biology Special Interest Group, Trey Ideker presents a great overview of the various strategies his group has been developing in the recent years in order to integrate multiple types of large scale datasets. While one of the most pervasive ‘meme’ about high-throughput measurement is that they are “notoriously unreliable” (see Hakes et al, 2008, for a recent example), Trey beautifully illustrates how predictive computational models and novel biological insights can be generated by sophisticated data integration strategies. Three types of applications are presented in his talk:  … Read more

The Human (Genetic) Disease Network

The Human (Genetic) Disease Network

The relationship between genetic mutations and human diseases is often complex and ambiguous: a given disease can be associated with mutations in distinct genes and, conversely, mutations in a given gene can be associated with several diseases. Can this many-to-many relationship be exploited to construct a human disease network and extract information on the human disease landscape?  Read more

Semantic zooming of networks

One can only agree with Euan Adie, that “the way we present genomic and proteomic data on the web sucks” (read post on Nascent). And this holds for biological networks: depiction of protein-protein interactions as colorful hairballs results in impressive figures but is not obligatorily very useful. While the network representation is a powerful abstract representation of biological processes, it is trivial to say that a graph (with its jungle of nodes and edges) is far from resembling even remotely to an actual living cell as you see it under the microscope… In the crude visualization of biological process as simple graphs, space, time, multi-scale structure and biological context are missing.  Read more