Generalized regular expressions—A language for synthesis of programs with branching in loops

AbstractRegular expressions are generalized to the effect that, besides letters from a finite alphabet, they may also contain natural numbers. Within the framework of these generalized expressions the task of the inductive synthesis of programs from its sample run is formalized. Special automata recognizing the sets defined by generalized expressions are introduced, and their equivalence problem is shown to be recursively solvable. The set-theoretic properties of the sets defined by generalized expressions are also studied

Prediction of gene expression in embryonic structures of Drosophila melanogaster.

Understanding how sets of genes are coordinately regulated in space and time to generate the diversity of cell types that characterise complex metazoans is a major challenge in modern biology. The use of high-throughput approaches, such as large-scale in situ hybridisation and genome-wide expression profiling via DNA microarrays, is beginning to provide insights into the complexities of development. However, in many organisms the collection and annotation of comprehensive in situ localisation data is a difficult and time-consuming task. Here, we present a widely applicable computational approach, integrating developmental time-course microarray data with annotated in situ hybridisation studies, that facilitates the de novo prediction of tissue-specific expression for genes that have no in vivo gene expression localisation data available. Using a classification approach, trained with data from microarray and in situ hybridisation studies of gene expression during Drosophila embryonic development, we made a set of predictions on the tissue-specific expression of Drosophila genes that have not been systematically characterised by in situ hybridisation experiments. The reliability of our predictions is confirmed by literature-derived annotations in FlyBase, by overrepresentation of Gene Ontology biological process annotations, and, in a selected set, by detailed gene-specific studies from the literature. Our novel organism-independent method will be of considerable utility in enriching the annotation of gene function and expression in complex multicellular organisms

A call for BMC Research Notes contributions promoting best practice in data standardization, sharing and publication

BMC Research Notes aims to ensure that data files underlying published articles are made available in standard, reusable formats, and the journal is calling for contributions from the scientific community to achieve this goal. Educational Data Notes included in this special series should describe a domain-specific data standard and provide an example data set with the article, or a link to data that are permanently hosted elsewhere. The contributions should also provide some evidence of the data standard's application and preparation guidance that could be used by others wishing to conduct similar experiments. The journal is also keen to receive contributions on broader aspects of scientific data sharing, archiving, and open data

MageComet—web application for harmonizing existing large-scale experiment descriptions

Motivation: Meta-analysis of large gene expression datasets obtained from public repositories requires consistently annotated data. Curation of such experiments, however, is an expert activity which involves repetitive manipulation of text. Existing tools for automated curation are few, which bottleneck the analysis pipeline

Submission of Microarray Data to Public Repositories

The Microarray Gene Expression Data Society believe that the time is right for journals to require that microarray data be deposited in public repositories, as a condition for publicatio

Genome Biol.

With genome analysis expanding from the study of genes to the study of gene regulation, 'regulatory genomics' utilizes sequence information, evolution and functional genomics measurements to unravel how regulatory information is encoded in the genome