Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Cell annotation”

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 775 records · Page 43Linked to original sources
PubMed2004

PINdb: a database of nuclear protein complexes from human and yeast.

SUMMARY: Proteins Interacting in the Nucleus database (PINdb) is a database of protein complexes purified from the nucleus of human and yeast cells. It is compiled from the published literature and existing databases. Currently, PINdb contains mostly protein complexes that may be involved in gene transcription. To facilitate comparative analyses and identification of protein complexes, the compositional information is integrated with standardized gene nomenclature, annotation and protein sequences from public databases. The PINdb web interface provides a number of tools for (1) comparison of protein complexes, (2) search for a protein complex by its published name or by a partial list of its components and (3) browsing specific subsets or a functional classification of the complexes. Availablity: http://pin.mskcc.org

Abstracting and Indexing↗
PubMed2004

The CyberCell Database (CCDB): a comprehensive, self-updating, relational database to coordinate and facilitate in silico modeling of Escherichia coli.

The CyberCell Database (CCDB: http://redpoll. pharmacy.ualberta.ca/CCDB) is a comprehensive, web-accessible database designed to support and coordinate international efforts in modeling an Escherichia coli cell on a computer. The CCDB brings together both observed and derived quantitative data from numerous independent sources covering many aspects of the genomic, proteomic and metabolomic character of E.coli (strain K12). The database is self-updating but also supports 'community' annotation, and provides an extensive array of viewing, querying and search options including a powerful, easy-to-use relational data extraction system.

Computational Biology↗
PubMed2000

Expression-based genetic/physical maps of single-nucleotide polymorphisms identified by the cancer genome anatomy project.

SNPs (Single-Nucleotide Polymorphisms), the most common DNA variant in humans, represent a valuable resource for the genetic analysis of cancer and other illnesses. These markers may be used in a variety of ways to investigate the genetic underpinnings of disease. In gene-based studies, the correlations between allelic variants of genes of interest and particular disease states are assessed. An extensive collection of SNP markers may enable entire molecular pathways regulating cell metabolism, growth, or differentiation to be analyzed by this approach. In addition, high-resolution genetic maps based on SNPs will greatly facilitate linkage analysis and positional cloning. The National Cancer Institute's CGAP-GAI (Cancer Genome Anatomy Project Genetic Annotation Initiative) group has identified 10,243 SNPs by examining publicly available EST (Expressed Sequence Tag) chromatograms. More than 6800 of these polymorphisms have been placed on expression-based integrated genetic/physical maps. In addition to a set of comprehensive SNP maps, we have produced maps containing single nucleotide polymorphisms in genes expressed in breast, colon, kidney, liver, lung, or prostate tissue. The integrated maps, a SNP search engine, and a Java-based tool for viewing candidate SNPs in the context of EST assemblies can be accessed via the CGAP-GAI web site (http://cgap.nci.nih.gov/GAI/). Our SNP detection tools are available to the public for noncommercial use.

Chromosome Mapping↗
PubMed2004

Microarray analyses identify molecular biomarkers of Atlantic salmon macrophage and hematopoietic kidney response to Piscirickettsia salmonis infection.

Piscirickettsia salmonis is the intracellular bacterium that causes salmonid rickettsial septicemia, an infectious disease that kills millions of farmed fish each year. The mechanisms used by P. salmonis to survive and replicate within host cells are not known. Piscirickettsiosis causes severe necrosis of hematopoietic kidney. Microarray-based experiments with QPCR validation were used to identify Atlantic salmon macrophage and hematopoietic kidney genes differentially transcribed in response to P. salmonis infection. Infections were confirmed by microscopy and RT-PCR with pathogen-specific primers. In infected salmon macrophages, 71 different transcripts were upregulated and 31 different transcripts were downregulated. In infected hematopoietic kidney, 30 different transcripts were upregulated and 39 different transcripts were downregulated. Ten antioxidant genes, including glutathione S-transferase, glutathione reductase, glutathione peroxidase, and cytochrome b558 alpha- and beta-subunits, were upregulated in infected macrophages but not in infected hematopoietic kidney. Changes in redox status of infected macrophages may allow these cells to tolerate P. salmonis infection, raising the possibility that treatment with antioxidants may reduce hematopoietic tissue damage caused by this rickettsial infection. The downregulation of transcripts involved in adaptive immune responses (e.g., T cell receptor alpha-chain and C-C chemokine receptor 7) in infected hematopoietic kidney but not in infected macrophages may contribute to infection-induced kidney tissue damage. Molecular biomarkers of P. salmonis infection, characterized by immune-relevant functional annotations and high fold differences in expression between infected and noninfected samples, may aid in the development of anti-piscirickettsial vaccines and therapeutics.

Animals↗
PubMed2005

Mining the probiotic genome: advanced strategies, enhanced benefits, perceived obstacles.

Recent advances in DNA sequencing has made it possible to accurately decipher the entire genetic complement of a probiotic bacterium. Increases in sequencing capabilities have been enhanced through improved computer software that can annotate, or identify, the majority of genes encoded by the sequence. The availability of annotated genome sequence will be important in defining the capabilities of the individual strains of probiotic bacteria. It will also form the platform for microarray and proteomic technologies that allow real-time analysis of RNA and protein expression in the bacterial cell. Investigation of probiotic organisms with these new and potentially powerful tools will facilitate the development of the bacteria as therapeutic agents, and provide the mechanisms to produce advanced probiotic strains. This paper addresses the core technologies in the rapidly growing area of genomics, and their application to the molecular characterisation of probiotic bacteria and host-microbe interactions.

Databases, Genetic↗
PubMed2002

Mice and humans: chromosome engineering and its application to functional genomics.

Functional modeling of human genes and diseases requires suitable mammalian model organisms. For its genetic malleability, the mouse is likely to continue to play a major role in defining basic genetic traits and complex pathological disorders. Recently, gene targeting techniques have been extended towards developing new engineering strategies for generating extensive lesions and rearrangements in mouse chromosomes. While these advances create new opportunities to address similar aberrations observed in human diseases, they also open new ways of scaling-up mutagenesis projects that try to catalogue and annotate cellular functions of mammalian genes.

Animals↗
PubMed2003

Gene expression profile induced by 17 alpha-ethynyl estradiol in the prepubertal female reproductive system of the rat.

The profound effects of 17beta-estradiol on cell growth, differentiation, and general homeostasis of the reproductive and other systems, are mediated mostly by regulation of temporal and cell type-specific expression of different genes. In order to understand better the molecular events associated with the activation of the estrogen receptor (ER), we have used microarray technology to determine the transcriptional program and dose-response characteristics of exposure to a potent synthetic estrogen, 17 alpha-ethynyl estradiol (EE), during prepubertal development. Changes in patterns of gene expression were determined in the immature uterus and ovaries of Sprague-Dawley rats on postnatal day (PND) 24, 24 h after exposure to EE, at 0.001, 0.01, 0.1, 1 and 10 micro g EE/kg/day (sc), for four days (dosing from PND 20 to 23). The transcript profiles were compared between treatment groups and controls using oligonucleotide arrays to determine the expression level of approximately 7000 annotated rat genes and over 1740 expressed sequence tags (ESTs). Quantification of the number of genes whose expression was modified by the treatment, for each of the various doses of EE tested, showed clear evidence of a dose-dependent treatment effect that follows a monotonic response, concordant with the dose-response pattern of uterine wet-weight gain and luminal epithelial cell height. The number of genes whose expression is affected by EE exposure increases according to dose. At the highest dose tested of EE, we determined that the expression level of over 300 genes was modified significantly (p < or = 0.0001). A dose-dependent analysis of the transcript profile revealed a set of 88 genes whose expression is significantly and reproducibly modified (increased or decreased) by EE exposure (p < or = 0.0001). The results of this study demonstrate that, exposure to a potent estrogenic chemical during prepubertal maturation changes the gene expression profile of estrogen-sensitive tissues. Furthermore, the products of the EE-regulated genes identified in these tissues have a physiological role in different intracellular pathways, information that will be valuable to determine the mechanism of action of estrogens. Moreover, those genes could be used as biomarkers to identify chemicals with estrogenic activity.

Animals↗
PubMed2002

Large-scale analysis of the human and mouse transcriptomes.

High-throughput gene expression profiling has become an important tool for investigating transcriptional activity in a variety of biological samples. To date, the vast majority of these experiments have focused on specific biological processes and perturbations. Here, we have generated and analyzed gene expression from a set of samples spanning a broad range of biological conditions. Specifically, we profiled gene expression from 91 human and mouse samples across a diverse array of tissues, organs, and cell lines. Because these samples predominantly come from the normal physiological state in the human and mouse, this dataset represents a preliminary, but substantial, description of the normal mammalian transcriptome. We have used this dataset to illustrate methods of mining these data, and to reveal insights into molecular and physiological gene function, mechanisms of transcriptional regulation, disease etiology, and comparative genomics. Finally, to allow the scientific community to use this resource, we have built a free and publicly accessible website (http://expression.gnf.org) that integrates data visualization and curation of current gene annotations.

Animals↗
PubMed2004

Whole-genome annotation by using evidence integration in functional-linkage networks.

The advent of high-throughput biology has catalyzed a remarkable improvement in our ability to identify new genes. A large fraction of newly discovered genes have an unknown functional role, particularly when they are specific to a particular lineage or organism. These genes, currently labeled "hypothetical," might support important biological cell functions and could potentially serve as targets for medical, diagnostic, or pharmacogenomic studies. An important challenge to the scientific community is to associate these newly predicted genes with a biological function that can be validated by experimental screens. In the absence of sequence or structural homology to known genes, we must rely on advanced biotechnological methods, such as DNA chips and protein-protein interaction screens as well as computational techniques to assign putative functions to these genes. In this article, we propose an effective methodology for combining biological evidence obtained in several high-throughput experimental screens and integrating this evidence in a way that provides consistent functional assignments to hypothetical genes. We use the visualization method of propagation diagrams to illustrate the flow of functional evidence that supports the functional assignments produced by the algorithm. Our results contain a number of predictions and furnish strong evidence that integration of functional information is indeed a promising direction for improving the accuracy and robustness of functional genomics.

Chromosome Mapping↗
PubMed2005

Genomic mapping of RNA polymerase II reveals sites of co-transcriptional regulation in human cells.

BACKGROUND: Transcription by RNA polymerase II is regulated at many steps including initiation, promoter release, elongation and termination. Accumulation of RNA polymerase II at particular locations across genes can be indicative of sites of regulation. RNA polymerase II is thought to accumulate at the promoter and at sites of co-transcriptional alternative splicing where the rate of RNA synthesis slows. RESULTS: To further understand transcriptional regulation at a global level, we determined the distribution of RNA polymerase II within regions of the human genome designated by the ENCODE project. Hypophosphorylated RNA polymerase II localizes almost exclusively to 5' ends of genes. On the other hand, localization of total RNA polymerase II reveals a variety of distinct landscapes across many genes with 74% of the observed enriched locations at exons. RNA polymerase II accumulates at many annotated constitutively spliced exons, but is biased for alternatively spliced exons. Finally, RNA polymerase II is also observed at locations not in gene regions. CONCLUSION: Localizing RNA polymerase II across many millions of base pairs in the human genome identifies novel sites of transcription and provides insights into the regulation of transcription elongation. These data indicate that RNA polymerase II accumulates most often at exons during transcription. Thus, a major factor of transcription elongation control in mammalian cells is the coordination of transcription and pre-mRNA processing to define exons.

Chromatin Immunoprecipitation↗
PubMed2006

Gene targeting of ErbB3 using a Cre-mediated unidirectional DNA inversion strategy.

Recombinase-mediated unidirectional DNA inversion and transcriptional arrest is a promising strategy for high throughput conditional mutagenesis in the mouse. Banks of mouse embryonic stem cells with defined, transcriptionally silent insertions that can be activated by Cre recombinase would take advantage of existing transgenic Cre lines to rapidly produce hundreds of lineage specific and temporally controlled knockout mice for each gene, thereby introducing significant parallelism to functional gene annotation. However, the extent to which this strategy results in effective gene knockout has not been established. To test the feasibility of this strategy we targeted ErbB3, a member of the ErbB family of tyrosine kinase receptors, using this strategy. Insertion of a reversed "flipflox" vector consisting of a gene inactivation cassette (GI) and an internal ribosome entry site (IRES)-GFP reporter into intron 1 of ErbB3 was transcriptionally silent and did not affect ErbB3 expression. Crosses with ubiquitous and lineage specific Cre recombinase expressing lines permanently inverted the inserted GI cassette and blocked ErbB3 expression. Unidirectional DNA inversion by in vivo recombination is an effective strategy for targeted or ubiquitous gene knockout.

Animals↗
PubMed2003

Biological mechanism profiling using an annotated compound library.

We present a method for testing many biological mechanisms in cellular assays using an annotated library of 2036 small organic molecules. This annotated compound library represents a large-scale collection of compounds with diverse, experimentally confirmed biological mechanisms and effects. We found that this chemical library is (1) more structurally diverse than conventional, commercially available libraries, (2) enriched in active compounds in a tumor cell viability assay, and (3) capable of generating hypotheses regarding biological mechanisms underlying cellular processes. We elucidated biological mechanisms relevant to the antiproliferative activity of 85 compounds from this library that were selected using a high-throughput cell viability screen. We developed a novel automated scoring system for identifying statistically enriched mechanisms among such a subset of compounds. This scoring system can identify both previously known and potentially novel antiproliferative mechanisms.

Cell Line, Tumor↗
PubMed2005

List of lists-annotated (LOLA): a database for annotation and comparison of published microarray gene lists.

Microarray profiling of RNA expression is a powerful tool that generates large lists of transcripts that are potentially relevant to a disease or treatment. However, because the lists of changed transcripts are embedded in figures and tables, they are typically inaccessible for search engines. Due to differences in gene nomenclatures, the lists are difficult to compare between studies. LOLA (Lists of Lists Annotated) is an internet-based database for comparing gene lists from microarray studies or other genomic-scale methods. It serves as a common platform to compare and reannotate heterogeneous gene lists from different microarray platforms or different genomic methodologies such as serial analysis of gene expression (SAGE) or proteomics. LOLA () provides researchers with a means to store, annotate, and compare gene lists produced from different studies or different analyses of the same study. It is especially useful in identifying potentially "high interest" genes which are reported as significant across multiple studies and species. Its application to the fields of stem cell, cancer, and aging research is demonstrated by comparing published papers.

Animals↗
PubMed2006

The LIFEdb database in 2006.

LIFEdb (http://www.LIFEdb.de) integrates data from large-scale functional genomics assays and manual cDNA annotation with bioinformatics gene expression and protein analysis. New features of LIFEdb include (i) an updated user interface with enhanced query capabilities, (ii) a configurable output table and the option to download search results in XML, (iii) the integration of data from cell-based screening assays addressing the influence of protein-overexpression on cell proliferation and (iv) the display of the relative expression ('Electronic Northern') of the genes under investigation using curated gene expression ontology information. LIFEdb enables researchers to systematically select and characterize genes and proteins of interest, and presents data and information via its user-friendly web-based interface.

Cell Proliferation↗
PubMed2026

Integrative multi-omics profiling of insomnia-related molecular features reveals microbiome, immune, and therapy-relevant heterogeneity in colorectal cancer.

Emerging evidence implicates insomnia as a potential risk factor in carcinogenesis, potentially involving systemic inflammation, circadian disruption, and microbiome alterations. However, the molecular associations linking insomnia-related features to colorectal cancer (CRC), particularly with respect to tumor biology, immune microenvironmental states, and therapy-relevant phenotypes, remain largely unexplored. Multi-omics integration of genomic, transcriptomic, and microbiome data from 3,026 CRC patients across seven independent cohorts, including a large, well-annotated Clinical Omics study of Colorectal Cancer in China (COCC) cohort, enabled insomnia-based molecular classification through unsupervised non-negative matrix factorization (NMF) clustering. The insomnia subtype (IS) was biologically characterized via pathway enrichment, immune deconvolution, microbial profiling, and single-cell transcriptomics. Furthermore, an insomnia score (ISscore) was developed and validated in multiple cohorts for risk stratification and assessment of treatment-response-related indicators in CRC. Unsupervised clustering revealed two distinct molecular subtypes (IS1/IS2), with IS2 demonstrating significantly poorer survival. IS2 exhibited marked activation of EMT/angiogenesis pathways versus cell cycle activation in IS1. The IS2 microenvironment showed increased immunosuppression-related infiltration and exhausted T cell signatures, together with intratumoral microbiome variation characterized by depletion of Ruminococcaceae UCG-002 and enrichment of Hungatella/Selenomonas. The ISscore system stratified survival risk and was associated with computational indicators of immunotherapy response. Single-cell analysis nominated PPIA-BSG as a potential cell-cell communication signal involving high-ISscore tumor cells, CXCL12+ endothelial cells, and CLEC9A+ dendritic cell subsets. This multi-omics characterization of insomnia-CRC interplay suggests that insomnia-related molecular features are associated with an immunologically distinct and microbiome-altered tumor ecosystem. The ISscore provides a reproducible framework for capturing insomnia-related molecular heterogeneity, supporting risk stratification and future evaluation of therapy-relevant phenotypes.IMPORTANCEChronic insomnia affects millions, but it is not typically considered a cancer risk factor. Our study, analyzing vast biological data from over 3,000 colorectal cancer patients, uncovers a potential link between a person's predisposition to insomnia and their risk of developing this disease. This suggests that the biological pathways related to sleep may play a role in cancer development. Understanding this connection opens up new avenues for identifying individuals at higher risk and developing novel prevention strategies for colorectal cancer.

colorectal cancer↗
PubMed2006

C. elegans: an invaluable model organism for the proteomics studies of the cholesterol-mediated signaling pathway.

With the availability of its complete genome sequence and unique biological features relevant to human disease, Caenorhabditis elegans has become an invaluable model organism for the studies of proteomics, leading to the elucidation of nematode gene function. A journey from the genome to proteome of C. elegans may begin with preparation of expressed proteins, which enables a large-scale analysis of all possible proteins expressed under specific physiological conditions. Although various techniques have been used for proteomic analysis of C. elegans, systematic high-throughput analysis is still to come in order to accommodate studies of post-translational modification and quantitative analysis. Given that no integrated C. elegans protein expression database is available, it is about time that a global C. elegans proteome project is launched through which datasets of transcriptomes, protein-protein interaction and functional annotation can be integrated. As an initial target of a pilot project of the C. elegans proteome project, the cholesterol-mediated signaling pathway will be an excellent example since, like in other organisms, it is one of the key controlling pathways in cell growth and development in C. elegans. As this field tends to broaden to functional proteomics, there is a high demand to develop the versatile proteome informatics tools that can mange many different data in an integrative manner.

Animals↗
PubMed2005

Transcriptional maps of 10 human chromosomes at 5-nucleotide resolution.

Sites of transcription of polyadenylated and nonpolyadenylated RNAs for 10 human chromosomes were mapped at 5-base pair resolution in eight cell lines. Unannotated, nonpolyadenylated transcripts comprise the major proportion of the transcriptional output of the human genome. Of all transcribed sequences, 19.4, 43.7, and 36.9% were observed to be polyadenylated, nonpolyadenylated, and bimorphic, respectively. Half of all transcribed sequences are found only in the nucleus and for the most part are unannotated. Overall, the transcribed portions of the human genome are predominantly composed of interlaced networks of both poly A+ and poly A- annotated transcripts and unannotated transcripts of unknown function. This organization has important implications for interpreting genotype-phenotype associations, regulation of gene expression, and the definition of a gene.

Cell Line↗
PubMed2003

Identification of cellular changes associated with increased production of human growth hormone in a recombinant Chinese hamster ovary cell line.

A proteomics approach was used to identify the proteins potentially implicated in the cellular response concomitant with elevated production levels of human growth hormone in a recombinant Chinese hamster ovary (CHO) cell line following exposure to 0.5 mM butyrate and 80 microM zinc sulphate in the production media. This involved incorporation of two-dimensional (2-D) gel electrophoresis and protein identification by a combination of N-terminal sequencing, matrix-assisted laser desorption/ionisation-time of flight mass spectrometry, amino acid analysis and cross species database matching. From these identifications a CHO 2-D reference map and annotated database have been established. Metabolic labelling and subsequent autoradiography showed the induction of a number of cellular proteins in response to the media additives butyrate and zinc sulphate. These were identified as GRP75, enolase and thioredoxin. The chaperone proteins GRP78, HSP90, GRP94 and HSP70 were not up-regulated under these conditions.

Amino Acids↗