Learn More
Dorsal hippocampal theta rhythm (theta) and extracellular unit activity from CA1 pyramidal layer were recorded in awake guinea pigs, both during standing and during walking on a conveyor belt at increasing speeds. Amplitude, frequency and rhythmicity of theta increased linearly with the movement speed. In this preparation we found the same three types of(More)
MOTIVATION Exploration and analysis of interactome networks at systems level requires unification of the biomolecular elements and annotations that come from many different high-throughput or small-scale proteomic experiments. Only such integration can provide a non-redundant and consistent identification of proteins and interactions. APID2NET is a new tool(More)
As bioinformatics becomes increasingly central to research in the molecular life sciences, the need to train non-bioinformaticians to make the most of bioinformatics resources is growing. Here, we review the key challenges and pitfalls to providing effective training for users of bioinformatics services, and discuss successful training strategies shared by(More)
BACKGROUND Using oligonucleotide microarrays, we compared transcriptional profiles corresponding to the initial cell cycle stages of mouse fibroblasts lacking the small GTPases H-Ras and/or N-Ras with those of matching, wild-type controls. RESULTS Serum-starved wild-type and knockout ras fibroblasts had very similar transcriptional profiles, indicating(More)
Agile Protein Interaction DataAnalyzer (APID) is an interactive bioinformatics web tool developed to integrate and analyze in a unified and comparative platform main currently known information about protein-protein interactions demonstrated by specific small-scale or large-scale experimental methods. At present, the application includes information coming(More)
A wealth of molecular interaction data is available in the literature, ranging from large-scale datasets to a single interaction confirmed by several different techniques. These data are all too often reported either as free text or in tables of variable format, and are often missing key pieces of information essential for a full understanding of the(More)
BACKGROUND Analysis of gene expression data using genome-wide microarrays is a technique often used in genomic studies to find coexpression patterns and locate groups of co-transcribed genes. However, most studies done at global "omic" scale are not focused on human samples and when they correspond to human very often include heterogeneous datasets, mixing(More)
Decades of research into cell biology, molecular biology, biochemistry, structural biology, and biophysics have produced a remarkable compendium of knowledge on the function and molecular properties of individual proteins. This knowledge is well recorded and manually curated into major protein databases like UniProt [1,2]. However , proteins rarely act(More)
BACKGROUND Genome-wide expression studies have developed exponentially in recent years as a result of extensive use of microarray technology. However, expression signals are typically calculated using the assignment of "probesets" to genes, without addressing the problem of "gene" definition or proper consideration of the location of the measuring probes in(More)