Implicit methods for qualitative modeling of gene regulatory networks.

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

DNA banking for plant breeding, biotechnology and biodiversity evaluation.

The manipulation of DNA is routine practice in botanical research and has made a huge impact on plant breeding, biotechnology and biodiversity evaluation. DNA is easy to extract from most plant tissues and can be stored for long periods in DNA banks. Curation methods are well developed for other botanical resources such as herbaria, seed banks and botanic gardens, but procedures for the establishment and maintenance of DNA banks have not been well documented. This paper reviews the curation of DNA banks for the characterisation and utilisation of biodiversity and provides guidelines for DNA bank management. It surveys existing DNA banks and outlines their operation. It includes a review of plant DNA collection, preservation, isolation, storage, database management and exchange procedures. We stress that DNA banks require full integration with existing collections such as botanic gardens, herbaria and seed banks, and information retrieval systems that link such facilities, bioinformatic resources and other DNA banks. They also require efficient and well-regulated sample exchange procedures. Only with appropriate curation will maximum utilisation of DNA collections be achieved.

Semantic domains and supersens tagging for domain-specific ontology learning

In this paper we propose a novel unsupervised approach to learning domain-specific ontologies from large open-domain text collections. The method is based on the joint exploitation of Semantic Domains and Super Sense Tagging for Information Retrieval tasks. Our approach is able to retrieve domain specific terms and concepts while associating them with a set of high level ontological types, named supersenses, providing flat ontologies characterized by very high accuracy and pertinence to the domain.

Application of text-mining for updating protein post-translational modification annotation in UniProtKB.

BACKGROUND: The annotation of protein post-translational modifications (PTMs) is an important task of UniProtKB curators and, with continuing improvements in experimental methodology, an ever greater number of articles are being published on this topic. To help curators cope with this growing body of information we have developed a system which extracts information from the scientific literature for the most frequently annotated PTMs in UniProtKB. RESULTS: The procedure uses a pattern-matching and rule-based approach to extract sentences with information on the type and site of modification. A ranked list of protein candidates for the modification is also provided. For PTM extraction, precision varies from 57% to 94%, and recall from 75% to 95%, according to the type of modification. The procedure was used to track new publications on PTMs and to recover potential supporting evidence for phosphorylation sites annotated based on the results of large scale proteomics experiments. CONCLUSIONS: The information retrieval and extraction method we have developed in this study forms the basis of a simple tool for the manual curation of protein post-translational modifications in UniProtKB/Swiss-Prot. Our work demonstrates that even simple text-mining tools can be effectively adapted for database curation tasks, providing that a thorough understanding of the working process and requirements are first obtained. This system can be accessed at http://eagl.unige.ch/PTM/.

Textual autocorrelation : formalism and illustrations

Abstract Textual autocorrelation is a broad and pervasive concept, referring to the similarity between nearby textual units: lexical repetitions along consecutive sentences, semantic association between neighbouring lexemes, persistence of discourse types (narrative, descriptive, dialogal...) and so on. Textual autocorrelation can also be negative, as illustrated by alternating phonological or morpho-syntactic categories, or the succession of word lengths. This contribution proposes a general Markov formalism for textual navigation, and inspired by spatial statistics. The formalism can express well-known constructs in textual data analysis, such as term-document matrices, references and hyperlinks navigation, (web) information retrieval, and in particular textual autocorrelation, as measured by Moran's I relatively to the exchange matrix associated to neighbourhoods of various possible types. Four case studies (word lengths alternation, lexical repulsion, parts of speech autocorrelation, and semantic autocorrelation) illustrate the theory. In particular, one observes a short-range repulsion between nouns together with a short-range attraction between verbs, both at the lexical and semantic levels. Résumé: Le concept d'autocorrélation textuelle, fort vaste, réfère à la similarité entre unités textuelles voisines: répétitions lexicales entre phrases successives, association sémantique entre lexèmes voisins, persistance du type de discours (narratif, descriptif, dialogal...) et ainsi de suite. L'autocorrélation textuelle peut être également négative, comme l'illustrent l'alternance entre les catégories phonologiques ou morpho-syntaxiques, ou la succession des longueurs de mots. Cette contribution propose un formalisme markovien général pour la navigation textuelle, inspiré par la statistique spatiale. Le formalisme est capable d'exprimer des constructions bien connues en analyse des données textuelles, telles que les matrices termes-documents, les références et la navigation par hyperliens, la recherche documentaire sur internet, et, en particulier, l'autocorélation textuelle, telle que mesurée par le I de Moran relatif à une matrice d'échange associée à des voisinages de différents types possibles. Quatre cas d'étude illustrent la théorie: alternance des longueurs de mots, répulsion lexicale, autocorrélation des catégories morpho-syntaxiques et autocorrélation sémantique. On observe en particulier une répulsion à courte portée entre les noms, ainsi qu'une attraction à courte portée entre les verbes, tant au niveau lexical que sémantique.

Antiepileptika bei Frauen im gebärfähigen Alter und in der Schwangerschaft : Vergleich der Fachinformationen in Deutschland und der Schweiz mit dem aktuellen Wissensstand [Antiepileptics in women of childbearing age and during pregnancy : Comparison of specialized information with the current state of knowledge in Germany and Switzerland].

BACKGROUND: Healthcare professionals regularly read the summary of product characteristics (SmPC) as one of the various sources of information on the risks of drug use in women of childbearing age and during pregnancy. The aim of this article is to present an overview of the teratogenic potential of various antiepileptic drugs and to compare these data with the information provided by the SmPCs. METHODS: A literature search on the teratogenic risks of 19 antiepileptic agents was conducted and the results were compared with the information on the use in women of childbearing age and during pregnancy provided by the SmPCs of 38 commercial products available in Switzerland and Germany. RESULTS: The teratogenic risk is discussed in all available SmPCs. Quantification of the risk for birth defects and the numbers of documented pregnancies are mostly missing. Reproductive safety information in SmPCs showed poor concordance with risk levels reported in the literature. Recommendations concerning the need to monitor plasma levels and possibly perform dose adjustments during pregnancy to prevent treatment failure were missing in five Swiss and two German SmPCs. DISCUSSION: The information regarding use in women of childbearing age and during pregnancy provided by the SmPCs is heterogeneous and poorly reflects the current state of knowledge. Regular updates of SmPCs are warranted in order for these documents to be of reliable use for health care professionals.