Tetracycline-controlled transgene activation using the ROSA26-iM2-GFP knock-in mouse strain permits GFP monitoring of DOX-regulated transgene-expression

Background  

Conditional gene activation is an efficient strategy for studying gene function in genetically modified animals. Among the presently available gene switches, the tetracycline-regulated system has attracted considerable interest because of its unique potential for reversible and adjustable gene regulation.     

Motif-guided sparse decomposition of gene expression data for regulatory module identification

Background  

Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for example, gene clustering is a popular method for grouping genes with similar gene expression patterns. However, traditional gene clustering often yields unsatisfactory results for regulatory module identification because the resulting gene clusters are co-expressed but not necessarily co-regulated.     

A new measure for functional similarity of gene products based on Gene Ontology

Background  

Gene Ontology (GO) is a standard vocabulary of functional terms and allows for coherent annotation of gene products. These annotations provide a basis for new methods that compare gene products regarding their molecular function and biological role.     

A systemic gene silencing method suitable for high throughput,reverse genetic analyses of gene function in fern gametophytes

Background  

Ceratopteris richardii is a useful experimental system for studying gametophyte development and sexual reproduction in plants. However, few tools for cloning mutant genes or disrupting gene function exist for this species. The feasibility of systemic gene silencing as a reverse genetics tool was examined in this study.     

Integrative inference of gene-regulatory networks in Escherichia coli using information theoretic concepts and sequence analysis

Background  

Although Escherichia coli is one of the best studied model organisms, a comprehensive understanding of its gene regulation is not yet achieved. There exist many approaches to reconstruct regulatory interaction networks from gene expression experiments. Mutual information based approaches are most useful for large-scale network inference.     

Construction and model-based analysis of a promoter library for <Emphasis Type="Italic">E. coli</Emphasis>: an indispensable tool for metabolic engineering

Background  

Nowadays, the focus in metabolic engineering research is shifting from massive overexpression and inactivation of genes towards the model-based fine tuning of gene expression. In this context, the construction of a library of synthetic promoters of Escherichia coli as a useful tool for fine tuning gene expression is discussed here.     

sscMap: An extensible Java application for connecting small-molecule drugs using gene-expression signatures

Background  

Connectivity mapping is a process to recognize novel pharmacological and toxicological properties in small molecules by comparing their gene expression signatures with others in a database. A simple and robust method for connectivity mapping with increased specificity and sensitivity was recently developed, and its utility demonstrated using experimentally derived gene signatures.     

A method for analyzing censored survival phenotype with gene expression data

Background  

Survival time is an important clinical trait for many disease studies. Previous works have shown certain relationship between patients' gene expression profiles and survival time. However, due to the censoring effects of survival time and the high dimensionality of gene expression data, effective and unbiased selection of a gene expression signature to predict survival probabilities requires further study.     

Phylogenetic reconstruction of ancestral character states for gene expression and mRNA splicing data

Background  

As genomes evolve after speciation, gene content, coding sequence, gene expression, and splicing all diverge with time from ancestors with close relatives. A minimum evolution general method for continuous character analysis in a phylogenetic perspective is presented that allows for reconstruction of ancestral character states and for measuring along branch evolution.     

Identification of the <Emphasis Type="Italic">C. elegans</Emphasis>anaphase promoting complex subunit Cdc26 by phenotypic profiling and functional rescue in yeast

Background  

RNA interference coupled with videorecording of C. elegans embryos is a powerful method for identifying genes involved in cell division processes. Here we present a functional analysis of the gene B0511.9, previously identified as a candidate cell polarity gene in an RNAi videorecording screen of chromosome I embryonic lethal genes.     

The <Emphasis Type="Italic">MB2</Emphasis> gene family of <Emphasis Type="Italic">Plasmodium</Emphasis> species has a unique combination of S1 and GTP-binding domains

Background  

Identification and characterization of novel Plasmodium gene families is necessary for developing new anti-malarial therapeutics. The products of the Plasmodium falciparum gene, MB2, were shown previously to have a stage-specific pattern of subcellular localization and proteolytic processing.     

Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks

Background  

Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are used to discretize microarray data. Selection of the discretization method is often arbitrary and no systematic comparison of different discretization has been conducted, in the context of gene regulatory network inference from time series gene expression data.     

Predicting DNA-binding sites of proteins from amino acid sequence

Background  

Understanding the molecular details of protein-DNA interactions is critical for deciphering the mechanisms of gene regulation. We present a machine learning approach for the identification of amino acid residues involved in protein-DNA interactions.     

Automatic generation of gene finders for eukaryotic species

Background  

The number of sequenced eukaryotic genomes is rapidly increasing. This means that over time it will be hard to keep supplying customised gene finders for each genome. This calls for procedures to automatically generate species-specific gene finders and to re-train them as the quantity and quality of reliable gene annotation grows.     

Correction: Disease candidate gene identification and prioritization using protein interaction networks

Background  

Although most of the current disease candidate gene identification and prioritization methods depend on functional annotations, the coverage of the gene functional annotations is a limiting factor. In the current study, we describe a candidate gene prioritization method that is entirely based on protein-protein interaction network (PPIN) analyses.     

Gene knockdown by RNAi in the pea aphid <Emphasis Type="Italic">Acyrthosiphon pisum</Emphasis>

Background  

RNA interference (RNAi) is a powerful method to inhibit gene expression in a sequence specific manner.     

eGIFT: Mining Gene Information from the Literature

Background  

With the biomedical literature continually expanding, searching PubMed for information about specific genes becomes increasingly difficult. Not only can thousands of results be returned, but gene name ambiguity leads to many irrelevant hits. As a result, it is difficult for life scientists and gene curators to rapidly get an overall picture about a specific gene from documents that mention its names and synonyms.     

Multiconstrained gene clustering based on generalized projections

Background  

Gene clustering for annotating gene functions is one of the fundamental issues in bioinformatics. The best clustering solution is often regularized by multiple constraints such as gene expressions, Gene Ontology (GO) annotations and gene network structures. How to integrate multiple pieces of constraints for an optimal clustering solution still remains an unsolved problem.