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 1,495 records · Page 83Linked to original sources
PubMed2006

Analysis of Oct4-dependent transcriptional networks regulating self-renewal and pluripotency in human embryonic stem cells.

The POU domain transcription factor OCT4 is a key regulator of pluripotency in the early mammalian embryo and is highly expressed in the inner cell mass of the blastocyst. Consistent with its essential role in maintaining pluripotency, Oct4 expression is rapidly downregulated during formation of the trophoblast lineage. To enhance our understanding of the molecular basis of this differentiation event in humans, we used a functional genomics approach involving RNA interference-mediated suppression of OCT4 function in a human ESC line and analysis of the resulting transcriptional profiles to identify OCT4-dependent genes in human cells. We detected altered expression of >1,000 genes, including targets regulated directly by OCT4 either positively (NANOG, SOX2, REX1, LEFTB, LEFTA/EBAF DPPA4, THY1, and TDGF1) or negatively (CDX2, EOMES, BMP4, TBX18, Brachyury [T], DKK1, HLX1, GATA6, ID2, and DLX5), as well as targets for the OCT4-associated stem cell regulators SOX2 and NANOG. Our data set includes regulators of ACTIVIN, BMP, fibroblast growth factor, and WNT signaling. These pathways are implicated in regulating human ESC differentiation and therefore further validate the results of our analysis. In addition, we identified a number of differentially expressed genes that are involved in epigenetics, chromatin remodeling, apoptosis, and metabolism that may point to underlying molecular mechanisms that regulate pluripotency and trophoblast differentiation in humans. Significant concordance between this data set and previous comparisons between inner cell mass and trophectoderm in human embryos indicates that the study of human ESC differentiation in vitro represents a useful model of early embryonic differentiation in humans.

Apoptosis↗
PubMed2006

Bioinformatics research on the SARS coronavirus (SARS_CoV) in China.

Severe acute respiratory syndrome (SARS) first appeared in 2002 in China, which fastly affected about 8000 patients over 29 countries and caused 774 fatalities. As its pathogen was identified as a new kind of coronavirus (SARS_CoV), its genome was quickly sequenced on several isolates. Studies on its functional genomics were performed by combinatorial application of all the available bioinformatics tools and the development of new programs. In this way, it was found that the four proteins were absolutely responsible for nosogenesis of SARS, i.e. spike (S) protein; small envelop (E) protein; membrane (M) protein; and nucleocaspid (N) protein. Molecular evolution studies have revealed that SARS must be originated from wild animals, and it was demonstrated that the major genetic variations in some critical genes, particularly the Spike gene, was essential for the transition from animal-to-human transmission to human-to-human transmission. Theoretical models, either Logistic model or SIR model, were developed to describe the transmission of SARS. The recorded difference of SARS spreading in Beijing and Hong Kong was also reasonably analyzed according to these models. The whole process of fruitful bioinformatics studies, along with other related scientific investigations have set up an unprecedented paradigm for human of how to battle against sudden-breaking and catastrophic epidemics.

China↗
PubMed2002

Impact of recombinant DNA technology and protein engineering on structure-based drug design: case studies of HIV-1 and HCMV proteases.

Structure-based drug design is an organized, multidisciplinary endeavor undertaken by scientists from many different scientific fields. The success of structure-based drug design was only made possible by advances in structure biology that provides the three-dimensional structure of the drug design target with which small molecular chemical ligands interact. Visualization of the conformation and interactions of a small molecule ligand bound to the protein target in the co-crystal structure of the protein:ligand complex enables the design of new chemical compounds with improved binding affinity and specificity. With the advances in molecular biology, lab automation, and computational science, genomic data have now become available for the human genome, as well as various other organisms. The pharmaceutical industry is currently putting forth tremendous effort in the area of functional genomics and structural genomics in attempts to decipher functions and structures of protein encoded by genes, with the ultimate goal of identifying novel targets for drug discovery and development. This chapter discusses the significant impact made by recombinant DNA technology and protein engineering on structural biology and, more specifically, on structure-based drug design.

Biotechnology↗
PubMed2001

[DNA arrays: technological aspects and applications].

The Human Genome Project has allowed considerable progress in the construction of physical and genetic maps and the identification of genes involved in human sicknesses. The accelerated accumulation of biological information and knowledge is due in large part to the sequencing projects of other organisms, which in fact paved the way for the Human Genome Project. In parallel, recently developed techniques which take advantage of genomic sequences allow large scale molecular analyses resulting in the functional annotation of many of the proteins represented by these genes. This is the goal of functional genomics. These progresses are at the origin of the present revolution in biomedical research. DNA microarrays are playing a dominant role compared to the other developing technologies since they are relatively easy to make and use and are applicable to numerous scientific inquiries. They allow the simultaneous analysis of several thousands of genes in biological samples from sick or healthy tissues, at the genome or transcriptome level. The data obtained is expected to result in major advances in the health sciences. In addition to an improved understanding of the complex molecular interaction networks of healthy cells and tissues, a more precise genetic characterization of the molecular mechanisms involved in pathology should result in the identification of new therapeutic targets and the development of new medicines. The genetic profiles thus obtained should also permit the definition of new pathologic subclasses not recognizable by traditional clinical factors, as well as new markers for susceptibility to certain illnesses, and new prognostic markers or methods of predicting responses to treatment. In this article, we present the different approaches and potential applications of DNA microarray technology, in particular as applied to cancer research.

Chromosome Mapping↗
PubMed2003

Genetic alterations and polymorphisms in gastric cancer.

The etiology of gastric cancer (GC) is multifactorial, and is likely to involve the actions of genes at multiple levels along the multistage carcinogenesis process. This article reviews the considerable progress that has been achieved in understanding the genetics of GC. The genetic effects consist of inherited genetic factors that predispose to GC, and the genetic targets of neoplastic progression that confer altered growth capacity to neoplastic cells. Inherited genotypes include germline mutations of high-penetrance genes directly associated with hereditary GC syndromes and genetic polymorphisms that indirectly affect the susceptibility to GC after exposure to carcinogens or Helicobacter pylori infection. Based on accumulation of different oncogenes or tumor suppressor genes alterations, 2 broad classes of genetic pathways called suppressor and mutator phenotypes are defined that participate in the development and progression of GC. Examples of genes involved in pathogenesis of GC include p53, adenomatous polyposis coli (APC), beta-catenin, E-cadherin, transforming growth factor (TGF)-betaRII, and hMLH1. Delineating genes involved in different subtypes of GC can reflect the heterogeneity and biologic characteristics of GC. Elucidation of the role of inherited genotypes and genetic alterations at different stages of gastrocarcinogenesis may provide a more coherent picture of the mechanism of this devastating disease and facilitate the development of novel approaches to effective prevention and intervention. Advances in high throughput technologies and functional genomics have rapidly increased our understanding of gene structure and function and its role in disease.

Disease Progression↗
PubMed2006

Designer genes: Filling the gap in transplantation.

Accelerated evolution of the field of functional genomics has been greatly facilitated by high-throughput microarray-based gene function studies, relating to the parallel and serial expression measurements of genomes. Microarray experimentation is being applied for the study of basic research questions, drug target discovery, pharmacology, toxicogenomics, target selectivity, disease biomarker determination, development of prognostic tests, and disease subclass determination. This article will review the current applications of microarray technology in the field of organ transplantation and discuss the potential impact of this technology on transplantation medicine.

Genetic Engineering↗
PubMed2000

Impact of transposable elements on the human genome.

Presence of transposable elements (TEs) in the human genome has profound effects on genome function, structure and evolution. TE mobility and inter-TE recombination are the origin of a large spectrum of mutations and genome reorganization leading to diseases. From the data provided by the Human Genome Project and from information on the detection and dynamics of TEs within and between species acquired during the last two decades, we now know that these elements are not only involved in mutagenesis but can also participate in many cellular functions including recombination, gene regulation, protein-coding RNA messages and, possibly, cellular stress response and centromere function. TEs also promote a general genome shuffling process that has been important for the evolution of several gene families and for the development of new regulatory pathways.

Centromere↗
PubMed2006

Proteomics-based validation of genomic data: applications in colorectal cancer diagnosis.

Multiple factors are involved in the translation of functional genomic results into proteins for proteome research and target validation on tumoral tissues. In this report, genes were selected by using DNA microarrays on a panel of colorectal cancer (CRC) paired samples. A large number of up-regulated genes in colorectal cancer patients were investigated for cellular location, and those corresponding to membrane or extracellular proteins were used for a non-biased expression in Escherichia coli. We investigated different sources of cDNA clones for protein expression as well as the influence of the protein size and the different tags with respect to protein expression levels and solubility in E. coli. From 29 selected genes, 21 distinct proteins were finally expressed as soluble proteins with, at least, one different fusion protein. In addition, seven of these potential markers (ANXA3, BMP4, LCN2, SPARC, SPP1, MMP7, and MMP11) were tested for antibody production and/or validation. Six of the seven proteins (all except SPP1) were confirmed to be overexpressed in colorectal tumoral tissues by using immunoblotting and tissue microarray analysis. Although none of them could be associated to early stages of the tumor, two of them (LCN2 and MMP11) were clearly overexpressed in late Dukes' stages (B and C). This proteomic study reveals novel clues for the assembly of a robust and highly efficient high throughput system for the validation of genomic data. Moreover it illustrates the different difficulties and bottlenecks encountered for performing a quick conversion of genomic results into clinically useful proteins.

Acute-Phase Proteins↗
PubMed2006

A regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data.

BACKGROUND: As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heterogeneous data sources. METHODS: In this paper, we address this issue by proposing a general framework for gene function prediction based on the k-nearest-neighbor (KNN) algorithm. The choice of KNN is motivated by its simplicity, flexibility to incorporate different data types and adaptability to irregular feature spaces. A weakness of traditional KNN methods, especially when handling heterogeneous data, is that performance is subject to the often ad hoc choice of similarity metric. To address this weakness, we apply regression methods to infer a similarity metric as a weighted combination of a set of base similarity measures, which helps to locate the neighbors that are most likely to be in the same class as the target gene. We also suggest a novel voting scheme to generate confidence scores that estimate the accuracy of predictions. The method gracefully extends to multi-way classification problems. RESULTS: We apply this technique to gene function prediction according to three well-known Escherichia coli classification schemes suggested by biologists, using information derived from microarray and genome sequencing data. We demonstrate that our algorithm dramatically outperforms the naive KNN methods and is competitive with support vector machine (SVM) algorithms for integrating heterogenous data. We also show that by combining different data sources, prediction accuracy can improve significantly CONCLUSION: Our extension of KNN with automatic feature weighting, multi-class prediction, and probabilistic inference, enhance prediction accuracy significantly while remaining efficient, intuitive and flexible. This general framework can also be applied to similar classification problems involving heterogeneous datasets.

Algorithms↗
PubMed2000

Current awareness.

In order to keep subscribers up-to-date with the latest developments in their field, this current awareness service is provided by John Wiley & Sons and contains newly-published material on comparative and functional genomics. Each bibliography is divided into 16 sections. 1 Reviews & symposia; 2 General; 3 Large-scale sequencing and mapping; 4 Genome evolution; 5 Comparative genomics; 6 Gene families and regulons; 7 Pharmacogenomics; 8 Large-scale mutagenesis programmes; 9 Functional complementation; 10 Transcriptomics; 11 Proteomics; 12 Protein structural genomics; 13 Metabolomics; 14 Genomic approaches to development; 15 Technological advances; 16 Bioinformatics. Within each section, articles are listed in alphabetical order with respect to author. If, in the preceding period, no publications are located relevant to any one of these headings, that section will be omitted

Animals↗
PubMed2006

Genome-wide atlas of gene expression in the adult mouse brain.

Molecular approaches to understanding the functional circuitry of the nervous system promise new insights into the relationship between genes, brain and behaviour. The cellular diversity of the brain necessitates a cellular resolution approach towards understanding the functional genomics of the nervous system. We describe here an anatomically comprehensive digital atlas containing the expression patterns of approximately 20,000 genes in the adult mouse brain. Data were generated using automated high-throughput procedures for in situ hybridization and data acquisition, and are publicly accessible online. Newly developed image-based informatics tools allow global genome-scale structural analysis and cross-correlation, as well as identification of regionally enriched genes. Unbiased fine-resolution analysis has identified highly specific cellular markers as well as extensive evidence of cellular heterogeneity not evident in classical neuroanatomical atlases. This highly standardized atlas provides an open, primary data resource for a wide variety of further studies concerning brain organization and function.

Animals↗
PubMed2026

DNA-aware evaluation and debiasing of sequence-to-function models.

MOTIVATION: Genome sequence-to-function (S2F) models are widely used to interpret base-resolution functional genomics assays. Most S2F models are trained and evaluated against observed counts and profile-shapes using statistical objectives and fidelity metrics. These choices are well motivated, but they are DNA-independent. At the same time, experimental measurements arise from DNA-dependent assays with distinct characteristics. This mismatch motivates a complementary DNA-aware evaluation of S2F-predicted and experimental functional genomic tracks. RESULTS: We study DNA-dependency of experimental and S2F-predicted tracks using track-conditional genome language models (cgLMs). cgLMs predict masked nucleotides from a conditioning track under controlled DNA visibility. Across ATAC-seq and TF ChIP-seq peaks from GM12878 and K562, cgLM-probing reveals a consistent masked DNA-decodability gap between many experimental and S2F-predicted tracks. In particular, single-task (e.g. BPNet) and multi-task (e.g. AlphaGenome) S2F-predicted tracks enabled cgLMs to recover masked nucleotides with significantly higher accuracy and confidence than matched experimental tracks. Analyses of nonpeak and dinucleotide-shuffled sequences show that this gap is not confined to peaks and is not captured by standard DNA-agnostic profile-shape fidelity metrics alone. ChromBPNet Tn5-denoised predictions were an exception and behaved closer to the experimental regime, suggesting that staged training may reduce the gap. We then convert this diagnostic into a critic-derived objective, DNA-dependency matching (DDM), using a frozen multi-headed cgLM critic. We introduce Critic-Guided Profile-Shape Editing (CGPSE), a preliminary post hoc debiasing framework for frozen S2F models. In GM12878 ATAC-seq, CGPSE partially reduces the masked DNA-decodability gap for AlphaGenome and BPNet predictions, while exposing a tradeoff with profile-shape fidelity. AVAILABILITY AND IMPLEMENTATION: https://github.com/li-lab-mcgill/dna-aware-s2f-eval.

DNA↗
PubMed1988

Correlation of physical maps and some genetic functions in the genomes of the kappa-theta phage family of Bacillus licheniformis.

Natural recombinant genomes between several, phenotypically distinct forms of phages kappa and theta were isolated and characterized by DNA restriction fragment mapping and electron microscopic heteroduplex analysis. The phenotypes of the recombinants were correlated with the physical maps of the genomes, and several genetic functions were therefore defined and mapped. All genes necessary for the assembly of infectious virus particles map in a contiguous tract of DNA comprising about 20 kb, or nearly one third of the genome length. No DNA homology occurs within these domains of the two genomes, so that homologous recombination does not take place here and phenotypic mixing of the phages is eo ipso excluded. Other regions of heterology contain regulatory genes responsible for the lytic or temperature character of the phages, and for exclusion of phage kappa by 9.

Bacillus↗
PubMed2004

High-throughput phenomics: experimental methods for mapping fluxomes.

Many technologies have been developed to help explain the phenotypic consequences of genetic and/or environmental modifications in areas like functional genomics, pharmaceutical research and metabolic engineering. The missing link in contemporary functional analyses that focus on the analysis of cellular components is the capacity to directly observe functional units. By linking genes and proteins to higher level biological functions, the molecular fluxes through metabolic networks (the fluxome) determine the cellular phenotype. Quantitative monitoring of such whole network operations by methods of metabolic flux analysis, thus bridges the gap by providing a global perspective of the integrated regulation at the transcriptional, translational and metabolic level. This review highlights recent developments towards high-throughput flux analysis.

Animals↗
PubMed2005

Use of genome information for the study of the pathogenesis of fungal infections and the development of diagnostic tools.

One of the most exciting advances in Mycology is the application of genomic approaches. The advent of genomics, together with post-genomic studies, promises to revolutionize the studies on the pathogenesis of fungal infections. Approaches include comparative genomics to identify sequences that contribute to infection and disease and functional genomics and proteomics to analyze global patterns of gene and protein expression involved in fungal pathogenesis.

DNA, Fungal↗
PubMed2002

The systemic paradigm and its relevance to the modelling of biological functions.

If we are to make advances in the design of information systems for the processing of functional genomic data, we must carefully examine the concepts of gene and function. Therefore, we must consider the biological models that are used to acquire these data from an epistemological point of view. This article introduces three elements of this view: (i) we reviewed the major concepts and the axioms of the systemic paradigm; (ii) we considered their relevance for the modelling of the biological functions within the framework of an intracellular signalling process; (iii) we present an operational input founded on this methodological viewpoint to illustrate the coherence of a theoretical framework and the use of its formalism for the description and the representation of biological activities. This formalism will guide the modelling and the interpretation of molecular interactions in terms of organisational operations producing and transforming the genetic information; thus, providing a better understanding of the complex relationship between the generation, the circulation and the computation of information when biological systems are set up.

Animals↗
PubMed2003

Diagnostic testing in hepatitis C virus infection: viral kinetics and genomics.

Virological tools play a major role in the diagnosis of hepatitis C virus (HCV) infection and in ongoing decision-making based on the patient's virological response to therapy. Virological tools used to assess viral kinetics and viral genomics can also be applied to clinical and translational research, especially in studies aimed at understanding the mechanisms underlying HCV treatment failure. Viral kinetics studies are based on quantification of HCV RNA at prescribed intervals during treatment and mathematical modeling of HCV RNA dynamics. These studies require sensitive and specific HCV RNA assays with an extended dynamic range of quantification. Viral genomics methods are useful to correlate viral kinetics with the intrinsic genomic characteristics of the HCV infecting strain. The interpretation of results utilizing various viral genomics tools is difficult, however, and must include predictive structural and functional genomic analyses. These approaches will be particularly useful in studying the mechanisms of HCV treatment failure with new HCV inhibitors currently under development.

Algorithms↗
PubMed2000

Screening poly(dA/dT)- cDNAs for gene identification.

Many genes expressed in the human genome have not been identified despite intensive efforts. We observed that the presence of long poly(dA/dT) sequences in the 3' end of cDNA templates contributes significantly to this problem, because the hybrids formed randomly between poly(dA) and poly(dT) sequences of unrelated cDNA templates lead to loss of many templates in the normalization/subtraction reactions. The low abundant copies, which account for the majority of the expressed genes, are affected in particular by this phenomenon. We have developed a strategy called screening poly(dA/dT)(-) cDNAs for gene identification to overcome this obstacle. Applying this strategy can significantly enhance the efficiency of genome-wide gene identification and should have an impact on many functional genomic studies in the postgenome era.

Base Sequence↗