70 research outputs found
Enhanced Operational Semantics in Systems Biology
We are faced with a great challenge: the cross-fertilization between the fields of formal methods for concurrency, in the computer science domain, and systems biology in the biological realm
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/)
Efficient exact pattern-matching in proteomic sequences
This paper proposes a novel algorithm for complete exact pattern-matching focusing the specificities of protein sequences (alphabet of 20 symbols) but, also highly efficient considering larger alphabets. The searching strategy uses large search windows allowing multiple alignments per iteration. A new filtering heuristic, named compatibility rule, contributed decisively to the efficiency improvement. The new algorithm’s performance is, on average, superior in comparison with its best-rated competitors
Singularly Perturbed Monotone Systems and an Application to Double Phosphorylation Cycles
The theory of monotone dynamical systems has been found very useful in the
modeling of some gene, protein, and signaling networks. In monotone systems,
every net feedback loop is positive. On the other hand, negative feedback loops
are important features of many systems, since they are required for adaptation
and precision. This paper shows that, provided that these negative loops act at
a comparatively fast time scale, the main dynamical property of (strongly)
monotone systems, convergence to steady states, is still valid. An application
is worked out to a double-phosphorylation ``futile cycle'' motif which plays a
central role in eukaryotic cell signaling.Comment: 21 pages, 3 figures, corrected typos, references remove
Efficient Reconstruction of Metabolic Pathways by Bidirectional Chemical Search
One of the main challenges in systems biology is the establishment of the metabolome: a catalogue of the metabolites and biochemical reactions present in a specific organism. Current knowledge of biochemical pathways as stored in public databases such as KEGG, is based on carefully curated genomic evidence for the presence of specific metabolites and enzymes that activate particular biochemical reactions. In this paper, we present an efficient method to build a substantial portion of the artificial chemistry defined by the metabolites and biochemical reactions in a given metabolic pathway, which is based on bidirectional chemical search. Computational results on the pathways stored in KEGG reveal novel biochemical pathways
The BioPAX community standard for pathway data sharing
Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery. © 2010 Nature America, Inc. All rights reserved
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