Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Genome mining”

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 559 records · Page 31Linked to original sources
PubMed2001

MRP8, a new member of ABC transporter superfamily, identified by EST database mining and gene prediction program, is highly expressed in breast cancer.

BACKGROUND: With the completion of the human draft genome sequence, efforts are now devoted to identifying new genes. We have developed a computer-based strategy that utilizes the EST database to identify new genes that could be targets for the immunotherapy of cancer or could be involved in the multistep process of cancer. MATERIALS AND METHODS: Utilizing our computer-based screening strategy, we identified a cluster of expressed sequence tags (ESTs) that are highly expressed in breast cancer. Northern blot and reverse transcriptase polymerase chain reaction (RT-PCR) analyses demonstrated the tissue specificity of the computer-generated cluster and comparison with the human genome sequence assisted in isolating a full-length cDNA clone. RESULTS: We identified a new gene that is highly expressed in breast cancer. This gene is expressed at moderate levels in normal breast and testis and at very low levels in liver, brain, and placenta. The gene has two major transcripts of 4.5 kb and 4.1 kb. The 4.5-kb transcript is very abundant in breast cancer, and has an open reading frame of 1382 amino acids. The predicted protein sequence of the 4.5-kb transcript reveals that it has high homology with MRP5, a member of multidrug resistant-associated protein family (MRP). There are seven reported members in the MRP family; we designate this gene as MRP8 (ABCC11). The 4.5-kb MRP8 transcript consists of 31 exons and is located in a genomic region of over 80.4 kb on chromosome 16q12.1. The smaller 4.1-kb transcript of MRP8 is found in testis and may initiate within intron 6 of the gene. CONCLUSION: The selective expression of MRP8 (ABCC11), a new member of ATP-binding cassette transporter superfamily could be a molecular target for the treatment of breast cancer.

ATP-Binding Cassette Transporters↗
PubMed2004

Microarray data mining using gene ontology.

DNA microarray technology allows scientists to study the expression of thousands of genes--potentially entire genomes--simultaneously. However the large number of genes, variety of statistical methods employed and the complexity of biologic systems complicate analysis of microarray results. We have developed a web based environment that simplifies the presentation of microarray results by combining microarray results processed for statistical significance with probe set annotation by Genbank, NCBI RefSeqs, GeneCards and the Gene Ontology. This allows rapid examination and classification of microarray experiments--annotated by NCIBI tools --by Statistical Significance and Gene Oncology Classes. By providing a simple, easily understood interface to large microarray data sets, this tool has been particularly useful for small research groups focused on a small number of related genes and for researchers who want to ask simple questions without the overhead of complex data management and analysis.

Computational Biology↗
PubMed2004

Risk assessment prediction from genome sequences: promises and dreams.

The application of bacterial genomics opens new avenues of research on foodborne pathogens. Foodborne pathogens must be able to colonize their hosts and survive transmission from host to host. Different groups of genes are involved in the processes of survival, colonization, and virulence, and such genes are potential targets for risk assessment and intervention strategies. Filtering from genome sequences the genes relevant to these processes is a major challenge, and although many tools are already available for analyses, this type of data mining is just beginning. For the simplest application, gene comparison, it is important to know how gene function, for instance in virulence, is being defined and tested. In other genomic applications, reserachers look for specific properties or characteristics of (virulence) genes to identify novel gene candidates. Each approach has pitfalls, and gene candidates must be tested in the lab to confirm their function. Models for colonization and virulence are available for most although not all pathogens. Models for survival and stress responses are needed to increase the utilization of genomic approaches to risk assessment. Here, I discuss how genome sequences are likely to help in microbial risk assessment of foodborne pathogens and how dreams may become promises.

Animals↗
PubMed2005

In silico whole-genome scanning of cancer-associated nonsynonymous SNPs and molecular characterization of a dynein light chain tumour variant.

Last decade has led to the accumulation of large amounts of data on cancer genetics, opening an unprecedented access to the mapping of cancer genes in the human genome. Single-nucleotide polymorphisms (SNPs), the most common form of DNA variation in humans, emerge as an invaluable tool for cancer association studies. These genotypic markers can be used to assay how alleles of candidate genes correlate with the malignant phenotype, and may provide new clues into the genetic modifications that characterize cancer onset. In this cancer-oriented study, we detail an SNP mining strategy based on the analysis of expressed sequence tags among publicly available databases. Our whole-genome approach provides a comprehensive and unbiased description of nonsynonymous SNPs (nsSNPs) in tumoral versus normal tissues. To gain further insights into the possible relationships between genetic variation and altered phenotype, locations of a subset of nsSNPs were mapped onto protein domains known to be critical for protein function. Computational methods were also used to predict the potential impact of these cancer-associated nsSNPs on protein structure and function. We illustrate our approach through the detailed biochemical and structural characterization of a previously unknown cancer-associated mutation (G79C) affecting the 8 kDa dynein light chain (DNCL1).

Computational Biology↗
PubMed2005

Exploiting naturally occurring DNA variation and molecular profiling data to dissect disease and drug response traits.

Identifying the key drivers of common human diseases and associated signaling pathways remains one of the primary objectives in the biomedical and life sciences. In this respect, common inbred strains of mice have played a crucial role, and recent advances in the development of genomics and bioinformatics tools have significantly enhanced their utility for this purpose. These advances have enabled a more holistic, network-oriented view of biological systems that facilitates elucidation of the underlying causes of disease and the best ways to target them. Success in reconstructing gene networks underlying disease traits (or other complex traits like drug response) and identifying the key drivers of these traits now largely rests on integrative approaches that combine data from multiple different sources. Such integrative genomics approaches that take into account genotypic, molecular profiling and clinical data in segregating mouse populations have recently been developed. Key to this integration has been the development and application of sophisticated algorithms to mine the diversity of data.

Algorithms↗
PubMed2000

An ordered comparative map of the cattle and human genomes.

A cattle-human whole-genome comparative map was constructed using parallel radiation hybrid (RH) mapping in conjunction with EST sequencing, database mining for unmapped cattle genes, and a predictive bioinformatics approach (COMPASS) for targeting specific homologous regions. A total of 768 genes were placed on the RH map in addition to 319 microsatellites used as anchor markers. Of these, 638 had human orthologs with mapping data, thus permitting construction of an ordered comparative map. The large number of ordered loci revealed > or =105 conserved segments between the two genomes. The comparative map suggests that 41 translocation events, a minimum of 54 internal rearrangements, and repositioning of all but one centromere can account for the observed organizations of the cattle and human genomes. In addition, the COMPASS in silico mapping tool was shown to be 95% accurate in its ability to predict cattle chromosome location from random sequence data, demonstrating this tool to be valuable for efficient targeting of specific regions for detailed mapping. The comparative map generated will be a cornerstone for elucidating mammalian chromosome phylogeny and the identification of genes of agricultural importance."Ought we, for instance, to begin by discussing each separate species-in virtue of some common element of their nature, and proceed from this as a basis for the consideration of them separately?" from Aristotle, On the Parts of Animals, 350 B.C.E.

Animals↗
PubMed2005

PROPHECY--a database for high-resolution phenomics.

The rapid recent evolution of the field phenomics--the genome-wide study of gene dispensability by quantitative analysis of phenotypes--has resulted in an increasing demand for new data analysis and visualization tools. Following the introduction of a novel approach for precise, genome-wide quantification of gene dispensability in Saccharomyces cerevisiae we here announce a public resource for mining, filtering and visualizing phenotypic data--the PROPHECY database. PROPHECY is designed to allow easy and flexible access to physiologically relevant quantitative data for the growth behaviour of mutant strains in the yeast deletion collection during conditions of environmental challenges. PROPHECY is publicly accessible at http://prophecy.lundberg.gu.se.

Computer Graphics↗
PubMed2005

Genomics, metagenomics and proteomics in biomining microorganisms.

The use of acidophilic, chemolithotrophic microorganisms capable of oxidizing iron and sulfur in industrial processes to recover metals from minerals containing copper, gold and uranium is a well established biotechnology with distinctive advantages over traditional mining. A consortium of different microorganisms participates in the oxidative reactions resulting in the extraction of dissolved metal values from ores. Considerable effort has been spent in the last years to understand the biochemistry of iron and sulfur compounds oxidation, bacteria-mineral interactions (chemotaxis, quorum sensing, adhesion, biofilm formation) and several adaptive responses allowing the microorganisms to survive in a bioleaching environment. All of these are considered key phenomena for understanding the process of biomining. The use of genomics, metagenomics and high throughput proteomics to study the global regulatory responses that the biomining community uses to adapt to their changing environment is just beginning to emerge in the last years. These powerful approaches are reviewed here since they offer the possibility of exciting new findings that will allow analyzing the community as a microbial system, determining the extent to which each of the individual participants contributes to the process, how they evolve in time to keep the conglomerate healthy and therefore efficient during the entire process of bioleaching.

Bacteria↗
PubMed2006

Intron length and accelerated 3' gene evolution.

Genetic evolution depends in part upon a balance between negative selection and environmentally driven mutation. To explore whether this balance is affected by gene structure, we have used phylogenetic data mining to compare gene compositions across a range of species. Here we show that genomes of higher species exhibit a greater frequency of 5' CpG islands and of CpG-->TpG/CpA transitions. This latter mutational pattern exhibits a 5'-to-3' trend in higher species, consistent with a length-dependent effect on methylation-dependent CpG suppression. Associated strand asymmetry (TpG>CpA) declines with gene length, implying attenuation of transcription-coupled repair 3' to introns. A sharp 3' rise in coding region single-nucleotide polymorphism frequency further supports a mechanistic role for intron length in promoting genetic variation by reducing repair and/or weakening negative selection. Consistent with this, the Ka/Ks ratio of 3' exons exceeds that of centrally located exons in intron-containing, but not in intronless, genes (p<0.0003). We conclude that the efficiency of transcription-coupled repair decreases with gene length, suggesting in turn that 3' gene evolution is accelerated both by introns and by gene methylation.

3' Untranslated Regions↗
PubMedDate not supplied

Identification and expression analysis of hepcidin-like antimicrobial peptides in bony fish.

Antimicrobial peptides play a crucial role as the first line of defense against invading pathogens. Several types of antimicrobial peptides have been isolated from fish, mostly of the cationic alpha-helical variety. Here, we present the cDNA sequences of five highly disulphide-bonded hepcidin-like peptides from winter flounder, Pseudopleuronectes americanus (Walbaum) and two from Atlantic salmon, Salmo salar (L.). These hepcidin-like molecules consist of a 24 amino acid signal peptide and an acidic propiece of 38-40 amino acids in addition to the mature processed peptide of 19-27 amino acids. Exhaustive data mining of GenBank with these sequences revealed that similar peptides are encoded in the genomes of Japanese flounder, rainbow trout, hybrid striped bass and medaka, indicating that they are widespread among fish. Southern hybridization analysis suggests that closely related hepcidin-like genes are present in other flatfish species, and that they exist as a multigene family clustered on the winter flounder genome. Hepcidin variants are differentially expressed during bacterial challenge, during larval development of P. americanus and in different tissues of adult fish.

Amino Acid Sequence↗
PubMedDate not supplied

The dragon on the gold: myths and realities for data mining in biomedicine and biotechnology using digital and molecular libraries.

To develop bioscience and personalized medicine in the post-genomic era, the biggest problem may be how to extract knowledge from the rich libraries of biomedical data. A particular dragon protects the gold therein: the dragon is the "curse of dimensionality" and its formidable fire weapon, which is burning researchers, is the "combinatorial explosion". This arises because many genomic, proteomic, clinical, and lifestyle factors may interact that cannot necessarily be considered on a simple pairwise or additive basis. A suggested theoretical solution--or at least "road map" that ameliorates management of these problems--borrows from several disciplines. It is undertaken also in the hope might also lead to research with broader impact on several unresolved issues in biotechnology: conversely, mathematical understanding of processes involving molecular libraries, such as cDNA libraries and DNA in the living cell itself, may open the opportunities to use biotechnology to construct nanotechnological storage and query systems.

Biomedical Research↗
PubMed2003

A systematic approach for yielding a potential pool of enzymes: practical case for chiral resolution of (R,S)-ketoprofen ethyl ester.

A systematic approach for the selection of potential biocatalysts from a natural source was developed and then a practical application was addressed. The approach that involves systematically combined conventional screening methods and current tools comprises the following consecutive steps: strain enrichment for activity screening, identification of positive strains, choosing whole genome-sequenced strains as candidates, gathering information about responsible enzymes, bioinformatic analyses and gene mining, probing genetic molecules and then functional expression. The target compound (R,S)-ketoprofen ethyl ester was to be resolved into an enantiomer, and a potential esterase from Pseudomonas fluorescens KCTC 1767 was prepared by the proposed procedure. The enzyme had a high activity and also strict selectivity for the enantiomer (S)-ketoprofen and was suitable therefore as a biocatalyst for practical use. The result achieved by the combined approach could not easily be obtained using other approaches with typical procedures. Hence the approach proposed here should be of considerable use for the screening of potential enzymes, particularly for enzymes with desired activity to unnatural substrates, from conditionally expressed and/or repressed proteins that are distributed widely in natural pools under normal conditions.

Amino Acid Sequence↗
PubMed2006

Robust sequence selection method used to develop the FluChip diagnostic microarray for influenza virus.

DNA microarrays have proven to be powerful tools for gene expression analyses and are becoming increasingly attractive for diagnostic applications, e.g., for virus identification and subtyping. The selection of appropriate sequences for use on a microarray poses a challenge, particularly for highly mutable organisms such as influenza viruses, human immunodeficiency viruses, and hepatitis C viruses. The goal of this work was to develop an efficient method for mining large databases in order to identify regions of conservation in the influenza virus genome. From these regions of conservation, capture and label sequences capable of discriminating between different viral types and subtypes were selected. The salient features of the method were the use of phylogenetic trees for data reduction and the selection of a relatively small number of capture and label sequences capable of identifying a broad spectrum of influenza viruses. A detailed experimental evaluation of the selected sequences is described in a companion paper. The software is freely available under the General Public License at http://www.colorado.edu/chemistry/RGHP/software/.

Computational Biology↗
PubMed2006

A transcriptome anatomy of human colorectal cancers.

BACKGROUND: Accumulating databases in human genome research have enabled integrated genome-wide study on complicated diseases such as cancers. A practical approach is to mine a global transcriptome profile of disease from public database. New concepts of these diseases might emerge by landscaping this profile. METHODS: In this study, we clustered human colorectal normal mucosa (N), inflammatory bowel disease (IBD), adenoma (A) and cancer (T) related expression sequence tags (EST) into UniGenes via an in-house GetUni software package and analyzed the transcriptome overview of these libraries by GOTree Machine (GOTM). Additionally, we downloaded UniGene based cDNA libraries of colon and analyzed them by Xprofiler to cross validate the efficiency of GetUni. Semi-quantitative RT-PCR was used to validate the expression of beta-catenin and. 7 novel genes in colorectal cancers. RESULTS: The efficiency of GetUni was successfully validated by Xprofiler and RT-PCR. Genes in library N, IBD and A were all found in library T. A total of 14,879 genes were identified with 2,355 of them having at least 2 transcripts. Differences in gene enrichment among these libraries were statistically significant in 50 signal transduction pathways and Pfam protein domains by GOTM analysis P < 0.01 Hypergeometric Test). Genes in two metabolic pathways, ribosome and glycolysis, were more enriched in the expression profiles of A and IBD than in N and T. Seven transmembrane receptor superfamily genes were typically abundant in cancers. CONCLUSION: Colorectal cancers are genetically heterogeneous. Transcription variants are common in them. Aberrations of ribosome and glycolysis pathway might be early indicators of precursor lesions in colon cancers. The electronic gene expression profile could be used to highlight the integral molecular events in colorectal cancers.

Cell Line, Tumor↗
PubMed2004

Microarray and comparative genomics-based identification of genes and gene regulatory regions of the mouse immune system.

BACKGROUND: In this study we have built and mined a gene expression database composed of 65 diverse mouse tissues for genes preferentially expressed in immune tissues and cell types. Using expression pattern criteria, we identified 360 genes with preferential expression in thymus, spleen, peripheral blood mononuclear cells, lymph nodes (unstimulated or stimulated), or in vitro activated T-cells. RESULTS: Gene clusters, formed based on similarity of expression-pattern across either all tissues or the immune tissues only, had highly significant associations both with immunological processes such as chemokine-mediated response, antigen processing, receptor-related signal transduction, and transcriptional regulation, and also with more general processes such as replication and cell cycle control. Within-cluster gene correlations implicated known associations of known genes, as well as immune process-related roles for poorly described genes. To characterize regulatory mechanisms and cis-elements of genes with similar patterns of expression, we used a new version of a comparative genomics-based cis-element analysis tool to identify clusters of cis-elements with compositional similarity among multiple genes. Several clusters contained genes that shared 5-6 cis-elements that included ETS and zinc-finger binding sites. cis-Elements AP2 EGRF ETSF MAZF SP1F ZF5F and AREB ETSF MZF1 PAX5 STAT were shared in a thymus-expressed set; AP4R E2FF EBOX ETSF MAZF SP1F ZF5F and CREB E2FF MAZF PCAT SP1F STAT cis-clusters occurred in activated T-cells; CEBP CREB NFKB SORY and GATA NKXH OCT1 RBIT occurred in stimulated lymph nodes. CONCLUSION: This study demonstrates a series of analytic approaches that have allowed the implication of genes and regulatory elements that participate in the differentiation, maintenance, and function of the immune system. Polymorphism or mutation of these could adversely impact immune system functions.

Animals↗
PubMed2002

Microarray analysis of bacterial pathogenicity.

The DNA microarray, a surface that contains an ordered arrangement of each identified open reading frame of a sequenced genome, is the engine of functional genomics. Its output, the expression profile, provides a genome wide snap-shot of the transcriptome. Refined by array-specific statistical instruments and data-mined by clustering algorithms and metabolic pathway databases, the expression profile discloses, at the transcriptional level, how the microbe adapts to new conditions of growth--the regulatory networks that govern the adaptive response and the metabolic and biosynthetic pathways that effect the new phenotype. Adaptation to host microenvironments underlies the capacity of infectious agents to persist in and damage host tissues. While monitoring the whole genome transcriptional response of bacterial pathogens within infected tissues has not been achieved, it is likely that the complex, tissue-specific response is but the sum of individual responses of the bacteria to specific physicochemical features that characterize the host milieu. These are amenable to experimentation in vitro and whole-genome expression studies of this kind have defined the transcriptional response to iron starvation, low oxygen, acid pH, quorum-sensing pheromones and reactive oxygen intermediates. These have disclosed new information about even well-studied processes and provide a portrait of the adapting bacterium as a 'system', rather than the product of a few genes or even a few regulons. Amongst the regulated genes that compose this adaptive system are transcription factors. Expression profiling experiments of transcription factor mutants delineate the corresponding regulatory cascade. The genetic basis for pathogenicity can also be studied by using microarray-based comparative genomics to characterize and quantify the extent of genetic variability within natural populations at the gene level of resolution. Also identified are differences between pathogen and commensal that point to possible virulence determinants or disclose evolutionary history. The host vigorously engages the pathogen; expression studies using host genome microarrays and bacterially infected cell cultures show that the initial host reaction is dominated by the innate immune response. However, within the complex expression profile of the host cell are components mediated by pathogen-specific determinants. In the future, the combined use of bacterial and host microarrays to study the same infected tissue will reveal the dialogue between pathogen and host in a gene-by-gene and site- and time-specific manner. Translating this conversation will not be easy and will probably require a combination of powerful bioinformatic tools and traditional experimental approaches--and considerable effort and time.

Animals↗
PubMed2004

PPD - Proteome Profile Database.

With the complete sequencing of multiple genomes, there have been extensions in the methods of sequence analysis from single gene/protein-based to analyzing multiple genes and proteins simultaneously. Therefore, there is a demand of user-friendly software tools that will allow mining of these enormous datasets. PPD is a WWW-based database for comparative analysis of protein lengths in completely sequenced prokaryotic and eukaryotic genomes. PPD's core objective is to create protein classification tables based on the lengths of proteins by specifying a set of organisms and parameters. The interface can also generate information on changes in proteins of specific length distributions. This feature is of importance when the user's interest is focused on some evolutionarily related organisms or on organisms with similar or related tissue specificity or life-style. PPD is available at: PPD Home.

Animals↗
PubMed2006

The application of systems biology to drug discovery.

Recent advances in the 'omics' technologies, scientific computing and mathematical modeling of biological processes have started to fundamentally impact the way we approach drug discovery. Recent years have witnessed the development of genome-scale functional screens, large collections of reagents, protein microarrays, databases and algorithms for data and text mining. Taken together, they enable the unprecedented descriptions of complex biological systems, which are testable by mathematical modeling and simulation. While the methods and tools are advancing, it is their iterative and combinatorial application that defines the systems biology approach.

Animals↗