Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Functional Genomics”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10Linked to original sources
PubMed2006

Benchmarking ortholog identification methods using functional genomics data.

BACKGROUND: The transfer of functional annotations from model organism proteins to human proteins is one of the main applications of comparative genomics. Various methods are used to analyze cross-species orthologous relationships according to an operational definition of orthology. Often the definition of orthology is incorrectly interpreted as a prediction of proteins that are functionally equivalent across species, while in fact it only defines the existence of a common ancestor for a gene in different species. However, it has been demonstrated that orthologs often reveal significant functional similarity. Therefore, the quality of the orthology prediction is an important factor in the transfer of functional annotations (and other related information). To identify protein pairs with the highest possible functional similarity, it is important to qualify ortholog identification methods. RESULTS: To measure the similarity in function of proteins from different species we used functional genomics data, such as expression data and protein interaction data. We tested several of the most popular ortholog identification methods. In general, we observed a sensitivity/selectivity trade-off: the functional similarity scores per orthologous pair of sequences become higher when the number of proteins included in the ortholog groups decreases. CONCLUSION: By combining the sensitivity and the selectivity into an overall score, we show that the InParanoid program is the best ortholog identification method in terms of identifying functionally equivalent proteins.

Algorithms↗
PubMed2006

Finding function: evaluation methods for functional genomic data.

BACKGROUND: Accurate evaluation of the quality of genomic or proteomic data and computational methods is vital to our ability to use them for formulating novel biological hypotheses and directing further experiments. There is currently no standard approach to evaluation in functional genomics. Our analysis of existing approaches shows that they are inconsistent and contain substantial functional biases that render the resulting evaluations misleading both quantitatively and qualitatively. These problems make it essentially impossible to compare computational methods or large-scale experimental datasets and also result in conclusions that generalize poorly in most biological applications. RESULTS: We reveal issues with current evaluation methods here and suggest new approaches to evaluation that facilitate accurate and representative characterization of genomic methods and data. Specifically, we describe a functional genomics gold standard based on curation by expert biologists and demonstrate its use as an effective means of evaluation of genomic approaches. Our evaluation framework and gold standard are freely available to the community through our website. CONCLUSION: Proper methods for evaluating genomic data and computational approaches will determine how much we, as a community, are able to learn from the wealth of available data. We propose one possible solution to this problem here but emphasize that this topic warrants broader community discussion.

Algorithms↗
PubMed2004

From ORFeome to biology: a functional genomics pipeline.

As several model genomes have been sequenced, the elucidation of protein function is the next challenge toward the understanding of biological processes in health and disease. We have generated a human ORFeome resource and established a functional genomics and proteomics analysis pipeline to address the major topics in the post-genome-sequencing era: the identification of human genes and splice forms, and the determination of protein localization, activity, and interaction. Combined with the understanding of when and where gene products are expressed in normal and diseased conditions, we create information that is essential for understanding the interplay of genes and proteins in the complex biological network. We have implemented bioinformatics tools and databases that are suitable to store, analyze, and integrate the different types of data from high-throughput experiments and to include further annotation that is based on external information. All information is presented in a Web database (http://www.dkfz.de/LIFEdb). It is exploited for the identification of disease-relevant genes and proteins for diagnosis and therapy.

Animals↗
PubMed2005

An integrated database of the ascidian, Ciona intestinalis: towards functional genomics.

An integrated genome database is essential for future studies of functional genomics. In this study, we update cDNA and genomic resources of the ascidian, Ciona intestinalis, and provide an integrated database of the genomic and cDNA data by extending a database published previously. The updated resources include over 190,000 ESTs (672,396 in total together with the previous ESTs) and over 1,000 full-insert sequences (6,773 in total). In addition, results of mapping information of the determined scaffolds onto chromosomes, ESTs from a full-length enriched cDNA library for indication of precise 5'-ends of genes, and comparisons of SNPs and indels among different individuals are integrated into this database, all of these results being reported recently. These advances continue to increase the utility of Ciona intestinalis as a model organism whilst the integrated database will be useful for researchers in comparative and evolutionary genomics.

Animals↗
PubMed2001

Peptide display in functional genomics.

The completion of the human genome project has opened novel scientific avenues in functional genomics, structural genomics and proteomics. These areas have a common goal: the identification of all the proteins acting and cross-talking in a single cell at a defined moment of its lifecycle. The expansion of these areas in bioscience has been facilitated by the rapid development of high throughput screening (HTS) methods which has, in turn, attracted the business community to make investments in this novel business segment of biotechnology. By using these HTS methods, the hope is that novel targets will be validated much more rapidly speeding up the development of novel drugs. Numerous techniques and tools have emerged over the past decade for the identification of small target-specific molecular ligands that exploit a common feature: the exploration of molecular diversity using combinatorial methods. While chemists developed new methods for rapidly and efficiently synthesising and screening large collections of small molecules, biologists used recombinant DNA techniques for selecting displayed repertoires. To this end, the discovery of new low molecular weight peptides is becoming increasingly important, not only as molecular tools for the understanding of protein-protein interactions but also for the generation of lead compounds.

Cloning, Molecular↗
PubMed1999

The complexity of radiation stress responses: analysis by informatics and functional genomics approaches.

Molecular responses to genotoxic stress are complex and are mediated by a variety of regulatory pathways. One key element in cellular response is the stress gene transcription factor p53, which can regulate nearly 100 genes that have already been identified. Although p53 plays a central role in the cellular response to DNA-damaging agents such as ionizing radiation (IR), other pathways can also have important roles. One example is the transcriptional responses associated with IR-induced apoptosis, where induction of some genes is limited to p53 wild-type (wt) cells that also have the ability to undergo rapid apoptosis after irradiation. In contrast, other genes are triggered after IR in lines undergoing rapid apoptosis regardless of p53 status. From this and other examples, it is apparent that the pattern of stress gene expression is cell type specific in both primary and transformed lines. The premise will be developed that such differences in stress gene responsiveness can be employed as molecular markers using a combination of informatics and functional genomics approaches. An example is given using the panel of lines of the NCI anticancer drug screen where both the p53 status and sensitivity to a large collection of cytotoxic agents have been determined. The utility of cDNA microarray hybridization to measure IR-stress gene responses has recently been demonstrated and a large number of additional IR-stress genes have been identified. The responses of some of these genes to IR and other DNA-damaging agents varied widely in cell lines from different tissues of origin and different genetic backgrounds, highlighting the importance of cellular context to genotoxic stress responses; this also highlights the need for informatics approaches to discover and prioritize hypotheses regarding the importance of particular cellular factors. The aim of this review is to demonstrate the utility of combining an informatics approach with functional genomics in the study of stress responses.

Animals↗
PubMed2001

Comparing functional genomic datasets: lessons from DNA microarray analyses of host-pathogen interactions.

Functional genomic technologies such as high density DNA microarrays allow biologists to study the structure and behavior of thousands of genes in a single experiment. One of the fields in which microarrays have had an increasingly important impact is host-pathogen interactions. Early investigations in this area over the past two years not only emphasize the utility of this approach, but also highlight the stereotyped gene expression responses of different host cells to diverse infectious stimuli, and the potential value of broad dataset comparisons in revealing fundamental features of innate immunity. The comparative analysis of recently published datasets involving human gene expression responses to two bacterial respiratory pathogens illustrates many of these points. Comparisons between these large, highly parallel sets of experimental observations also emphasize important technical and experimental design issues as future challenges.

Bordetella pertussis↗
PubMed2005

Non-linear mapping for exploratory data analysis in functional genomics.

BACKGROUND: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory, visualisation-driven approaches. Such approaches should satisfy the following factors: Support for intuitive cluster visualisation, user-friendly and robust application, computational efficiency and generation of biologically meaningful outcomes. This research assesses a relaxation method for non-linear mapping that addresses these concerns. Its applications to gene expression and protein-protein interaction data analyses are investigated. RESULTS: Publicly available expression data originating from leukaemia, round blue-cell tumours and Parkinson disease studies were analysed. The method distinguished relevant clusters and critical analysis areas. The system does not require assumptions about the inherent class structure of the data, its mapping process is controlled by only one parameter and the resulting transformations offer intuitive, meaningful visual displays. Comparisons with traditional mapping models are presented. As a way of promoting potential, alternative applications of the methodology presented, an example of exploratory data analysis of interactome networks is illustrated. Data from the C. elegans interactome were analysed. Results suggest that this method might represent an effective solution for detecting key network hubs and for clustering biologically meaningful groups of proteins. CONCLUSION: A relaxation method for non-linear mapping provided the basis for visualisation-driven analyses using different types of data. This study indicates that such a system may represent a user-friendly and robust approach to exploratory data analysis. It may allow users to gain better insights into the underlying data structure, detect potential outliers and assess assumptions about the cluster composition of the data.

Algorithms↗
PubMed2004

Integrative bioinformatics for functional genome annotation: trawling for G protein-coupled receptors.

G protein-coupled receptors (GPCR) are amongst the best studied and most functionally diverse types of cell-surface protein. The importance of GPCRs as mediates or cell function and organismal developmental underlies their involvement in key physiological roles and their prominence as targets for pharmacological therapeutics. In this review, we highlight the requirement for integrated protocols which underline the different perspectives offered by different sequence analysis methods. BLAST and FastA offer broad brush strokes. Motif-based search methods add the fine detail. Structural modelling offers another perspective which allows us to elucidate the physicochemical properties that underlie ligand binding. Together, these different views provide a more informative and a more detailed picture of GPCR structure and function. Many GPCRs remain orphan receptors with no identified ligand, yet as computer-driven functional genomics starts to elaborate their functions, a new understanding of their roles in cell and developmental biology will follow.

Algorithms↗
PubMed1998

Localization of genes encoding egg modifiers of paternal genome function to mouse chromosomes one and two.

It is now well established that genomic imprinting effects in mammals require a combination of epigenetic modifications imposed during gametogenesis and additional modifications imposed after fertilization. The earliest post-fertilization modifications to be imposed on the genome are those thought to be mediated by factors in the egg cytoplasm. Strain-dependent differences in the actions of these egg modifiers in mice reveal an important potential for genetic variability in the imprinting process, and also provide valuable genetic systems with which to identify some of the factors that participate in imprinting. Previous studies documented a strain-dependent difference in the modification of paternal genome function between the C57BL/6 and DBA/2 mouse strains. This difference is revealed as a difference in developmental potential of androgenetic embryos produced with eggs from females of the two strains by nuclear transplantation. The specificity of the effect for the paternal genome is consistent with an effect on imprinted genes. The egg phenotype is largely independent of the genotype of the fertilizing sperm, and the C57BL/6 phenotype is dominant in reciprocal F1 hybrids. Genetic studies demonstrated that the difference in egg phenotypes between the two strains is most likely controlled by two independently segregating loci. We now report the results of experiments in which the egg phenotypes of the available BxD recombinant inbred mouse strains have been determined. The results of the analysis are consistent with the two locus model, and we have identified candidate chromosomal locations for the two loci. These data demonstrate clearly that differences in how the egg cytoplasm modifies the incoming paternal genome are indeed genetically determined, and vary accordingly.

Animals↗
PubMed2006

Ontology-driven approaches to analyzing data in functional genomics.

Ontologies are fundamental knowledge representations that provide not only standards for annotating and indexing biological information, but also the basis for implementing functional classification and interpretation models. This chapter discusses the application of gene ontology (GO) for predictive tasks in functional genomics. It focuses on the problem of analyzing functional patterns associated with gene products. This chapter is divided into two main parts. The first part overviews GO and its applications for the development of functional classification models. The second part presents two methods for the characterization of genomic information using GO. It discusses methods for measuring functional similarity of gene products, and a tool for supporting gene expression clustering analysis and validation.

Cluster Analysis↗
PubMed2001

Taking a functional genomics approach in molecular medicine.

The elucidation of genetic components of human diseases at the molecular level provides crucial information for developing future causal therapeutic intervention. High-throughput genome sequencing and systematic experimental approaches are fuelling strategic programs designed to investigate gene function at the biochemical, cellular and organism levels. Bioinformatics is one important tool in functional genomics, although showing clear limitations in predicting ab initio gene structures, gene function and protein folds from raw sequence data. Systematic large-scale data-set generation, using the same type of experiments that are used to decipher the function of single genes, are being applied on entire genomes. Comparative genomics, establishment of gene catalogues, and investigation of cellular and tissue molecular profiles are providing essential tools for understanding gene function in complex biological networks.

Animals↗
PubMed2005

Functional genomic analysis of cell division by endoribonuclease-prepared siRNAs.

The emergence of RNA interference (RNAi) technology has revolutionized functional genomic analyses in cell biology, including the study of cell division. In particular, the introduction of short interfering RNAs (siRNAs) and short hairpin RNAs (shRNAs) has facilitated loss-of-function studies in mammalian cell lines. We have pioneered the rapid and cost-efficient generation of libraries of endoribonuclease-prepared short interfering RNAs (esiRNAs) for large-scale genetic screens in mammalian tissue culture cells. Our first pilot screen of 5305 genes in human HeLa cells identified novel genes required for cell division, establishing esiRNA as a sophisticated method for loss-of-function screens. Future genome-wide studies with esiRNA, using image-based assays and video microscopy, will help provide novel insights on the molecular mechanisms that govern cell division in mammalian cells.

Animals↗
PubMed1997

Gene trapping and functional genomics.

Classical genetics depends upon investigation of function by random destruction with little information on structure. Modern mapping using random polymorphisms, cloning and sequencing investigates structure without function. The genome projects with their rapid gene discovery are, however, redefining classical genetic approaches. The efficient translation of this wealth of new information into insights in biological function at molecular, cellular and organismal levels requires large-scale approaches to the generation of mutants. Gene trapping in embryonic stem (ES) cells allows an efficient approach to the functional analysis of the murine genome. The usually separate processes of gene discovery, mapping, the observation of the expression pattern and the mutant phenotype in vivo, can be integrated by the use of an indexed library of insertionally mutated ES cell clones. It should be possible to generate mutants for a large proportion of the genes of the mammalian genome.

Animals↗
PubMed2005

High-throughput RNA interference strategies for target discovery and validation by using synthetic short interfering RNAs: functional genomics investigations of biological pathways.

During the past five years, RNA interference (RNAi) has emerged as arguably the best functional genomics tool available to date, providing direct, causal links between individual genes and loss-of-function phenotypes through robust, broadly applicable, and readily upscalable methodologies. Originally applied experimentally in C. elegans and Drosophila, RNAi is now widely used in mammalian cell systems also. The development of commercially available libraries of short interfering RNAs (siRNAs) and other RNAi silencing reagents targeting entire classes of human genes provide the opportunity to carry out genome-scale screens to discover and characterize gene functions directly in human cells. A key challenge of these studies, also faced by earlier genomics or proteomics approaches, resides in reaching an optimal balance between the necessarily high throughput and the desire to achieve the same level of detailed analysis that is routine in conventional small-scale studies. This chapter discusses technical aspects of how to perform such screens, what parameters to monitor, and which readouts to apply. Examples of homogenous assays and multiplexed high-content microscopy-based screens are demonstrated.

Apoptosis↗
PubMed2006

Transcriptional profiling and functional genomics reveal a role for AHR transcription factor in nephrogenesis.

Transcriptional profiling and functional genomics experiments using E11.5 metanephros organ cultures from Ahr(-/-) and Ahr(+/+) have shown that aryl hydrocarbon receptor (AHR) transcription factor is involved in the regulation of mesenchymal-to-epithelial transition (MET) during nephrogenesis. This response is mediated by alterations in the post-transcriptional control of Wilms' tumor suppressor (Wt1) gene and Wt1 splicing. In this article, biologically relevant gene predictor sets of the nephrogenic response were calculated for target genes of interest. The predictability of the gene set for each target was quantified by the coefficient of determination which provided a good criterion for identification of predictor sets that define the complex gene-gene interactions co-regulated by Ahr and Wt1. A subset of the signature genes was found to be co-regulated by Ahr and Wt1 and was responsible for shifts in renal cell transdifferentiation.

Animals↗
PubMed2002

Green fluorescent protein as a convenient and versatile marker for studies on functional genomics in Drosophila.

Gene function can be deduced from lack or gain of activity. For the manipulation of gene doses or activity in Drosophila, a set of P-based vectors was constructed containing green fluorescent protein as marker. pBLUEi, pGREENi and pYELLi were designed for large insert transformation. Mosaicism was generated in vivo with pFlipG which is also ideal for targeted gene disruption. Tissue-specific gene silencing in vivo was performed with the vector set pHIBS and pUdsGFP. pHIBS allows easy cloning and shuttling of double-headed constructs. With pUdsGFP, double stranded RNA can be produced in defined patterns and the area of interference simultaneously visualized by green fluorescence. We demonstrate nearly complete silencing of a ubiquitously expressed gene in a tissue-specific manner.

Animals↗
PubMed2004

Yeast as a touchstone in post-genomic research: strategies for integrative analysis in functional genomics.

The new complexity arising from the genome sequencing projects requires new comprehensive post-genomic strategies: advanced studies in regulatory mechanisms, application of new high-throughput technologies at a genome-wide scale, at the different levels of cellular complexity (genome, transcriptome, proteome and metabolome), efficient analysis of the results, and application of new bioinformatic methods in an integrative or systems biology perspective. This can be accomplished in studies with model organisms under controlled conditions. In this review a perspective of the favourable characteristics of yeast as a touchstone model in post-genomic research is presented. The state-of-the art, latest advances in the field and bottlenecks, new strategies, new regulatory mechanisms, applications (patents) and high-throughput technologies, most of them being developed and validated in yeast, are presented. The optimal characteristics of yeast as a well-defined system for comprehensive studies under controlled conditions makes it a perfect model to be used in integrative, "systems biology" studies to get new insights into the mechanisms of regulation (regulatory networks) responsible of specific phenotypes under particular environmental conditions, to be applied to more complex organisms (e.g. plants, human).

Forecasting↗