8,769 research outputs found
Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?
The organization and mining of malaria genomic and post-genomic data is
highly motivated by the necessity to predict and characterize new biological
targets and new drugs. Biological targets are sought in a biological space
designed from the genomic data from Plasmodium falciparum, but using also the
millions of genomic data from other species. Drug candidates are sought in a
chemical space containing the millions of small molecules stored in public and
private chemolibraries. Data management should therefore be as reliable and
versatile as possible. In this context, we examined five aspects of the
organization and mining of malaria genomic and post-genomic data: 1) the
comparison of protein sequences including compositionally atypical malaria
sequences, 2) the high throughput reconstruction of molecular phylogenies, 3)
the representation of biological processes particularly metabolic pathways, 4)
the versatile methods to integrate genomic data, biological representations and
functional profiling obtained from X-omic experiments after drug treatments and
5) the determination and prediction of protein structures and their molecular
docking with drug candidate structures. Progresses toward a grid-enabled
chemogenomic knowledge space are discussed.Comment: 43 pages, 4 figures, to appear in Malaria Journa
Application of regulatory sequence analysis and metabolic network analysis to the interpretation of gene expression data
We present two complementary approaches for the interpretation of clusters of
co-regulated genes, such as those obtained from DNA chips and related methods.
Starting from a cluster of genes with similar expression profiles, two basic
questions can be asked:
1. Which mechanism is responsible for the coordinated transcriptional response
of the genes? This question is approached by extracting motifs that are shared
between the upstream sequences of these genes. The motifs extracted are putative
cis-acting regulatory elements.
2. What is the physiological meaning for the cell to express together these
genes? One way to answer the question is to search for potential metabolic
pathways that could be catalyzed by the products of the genes. This can be
done by selecting the genes from the cluster that code for enzymes, and trying
to assemble the catalyzed reactions to form metabolic pathways.
We present tools to answer these two questions, and we illustrate their use with
selected examples in the yeast Saccharomyces cerevisiae. The tools are available
on the web (http://ucmb.ulb.ac.be/bioinformatics/rsa-tools/;
http://www.ebi.ac.uk/research/pfbp/; http://www.soi.city.ac.uk/~msch/)
Topological network alignment uncovers biological function and phylogeny
Sequence comparison and alignment has had an enormous impact on our
understanding of evolution, biology, and disease. Comparison and alignment of
biological networks will likely have a similar impact. Existing network
alignments use information external to the networks, such as sequence, because
no good algorithm for purely topological alignment has yet been devised. In
this paper, we present a novel algorithm based solely on network topology, that
can be used to align any two networks. We apply it to biological networks to
produce by far the most complete topological alignments of biological networks
to date. We demonstrate that both species phylogeny and detailed biological
function of individual proteins can be extracted from our alignments.
Topology-based alignments have the potential to provide a completely new,
independent source of phylogenetic information. Our alignment of the
protein-protein interaction networks of two very different species--yeast and
human--indicate that even distant species share a surprising amount of network
topology with each other, suggesting broad similarities in internal cellular
wiring across all life on Earth.Comment: Algorithm explained in more details. Additional analysis adde
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