Showing papers by "Chris Sander published in 2003"
TL;DR: The results reaffirm the thesis that miRNAs have an important role in establishing the complex spatial and temporal patterns of gene activity necessary for the orderly progression of development and suggest additional roles in the function of the mature organism.
Abstract: Background: The recent discoveries of microRNA (miRNA) genes and characterization of the first few target genes regulated by miRNAs in Caenorhabditis elegans and Drosophila melanogaster have set the stage for elucidation of a novel network of regulatory control. We present a computational method for wholegenome prediction of miRNA target genes. The method is validated using known examples. For each miRNA, target genes are selected on the basis of three properties: sequence complementarity using a position-weighted local alignment algorithm, free energies of RNA-RNA duplexes, and conservation of target sites in related genomes. Application to the D. melanogaster, Drosophila pseudoobscura and Anopheles gambiae genomes identifies several hundred target genes potentially regulated by one or more known miRNAs.
2,997 citations
TL;DR: FuncAssociate is a web-based tool to help researchers use Gene Ontology attributes to characterize large sets of genes derived from experiment with a Monte Carlo simulation approach that is more appropriate to determine significance than other methods, such as Bonferroni or idák p-value correction.
Abstract: Summary: FuncAssociate is a web-based tool to help researchers use Gene Ontology attributes to characterize large sets of genes derived from experiment. Distinguishing features of FuncAssociate include the ability to handle ranked input lists, and a Monte Carlo simulation approach that is more appropriate to determine significance than other methods, such as Bonferroni or ˘ Sidak p-value correction. FuncAssociate currently supports 10 organisms (Vibrio cholerae, Shewanella oneidensis, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Caenorhaebditis elegans, Drosophila melanogaster, Mus musculus, Rattus norvegicus and Homo sapiens). Availability: FuncAssociate is freely accessible at http://llama. med.harvard.edu/Software.html. Source code (in Perl and C) is freely available to academic users ‘as is’.
494 citations
TL;DR: The overall disease spectrum mainly reflects the mutability of the genetic code and corroborate earlier results that the probability of a nonsynonymous mutation causing a genetic disease increases monotonically with an increase in the degree of evolutionary conservation of the mutation site and a decrease in the solvent-accessibility of the site.
Abstract: Background
Nonsynonymous mutations in the coding regions of human genes are responsible for phenotypic differences between humans and for susceptibility to genetic disease. Computational methods were recently used to predict deleterious effects of nonsynonymous human mutations and polymorphisms. Here we focus on understanding the amino-acid mutation spectrum of human genetic disease. We compare the disease spectrum to the spectra of mutual amino-acid mutation frequencies, non-disease polymorphisms in human genes, and substitutions fixed between species.
190 citations
TL;DR: It is concluded that genome annotation may entail a considerable amount of errors, ranging from simple typographical errors to complex sequence analysis problems, and automatic systems might perform as well as the teams of experts annotating genome sequences.
Abstract: MOTIVATION: Genome-wide functional annotation either by manual or automatic means has raised considerable concerns regarding the accuracy of assignments and the reproducibility of methodologies. In addition, a performance evaluation of automated systems that attempt to tackle sequence analyses rapidly and reproducibly is generally missing. In order to quantify the accuracy and reproducibility of function assignments on a genome-wide scale, we have re-annotated the entire genome sequence of Chlamydia trachomatis (serovar D), in a collaborative manner. RESULTS: We have encoded all annotations in a structured format to allow further comparison and data exchange and have used a scale that records the different levels of potential annotation errors according to their propensity to propagate in the database due to transitive function assignments. We conclude that genome annotation may entail a considerable amount of errors, ranging from simple typographical errors to complex sequence analysis problems. The most surprising result of this comparative study is that automatic systems might perform as well as the teams of experts annotating genome sequences
85 citations
29 citations