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At least 541 records · Page 30Linked to original sources
PubMed2002

Comparative analysis of multiple genome-scale data sets.

The ongoing analyses of published genome-scale data sets is evidence that different approaches are required to completely mine this data. We report the use of novel tools for both visualization and data set comparison to analyze yeast gene-expression (cell cycle and exit from stationary phase/G(0)) and protein-interaction studies. This analysis led to new insights about each data set. For example, G(1)-regulated genes are not co-regulated during exit from stationary phase, indicating that the cells are not synchronized. The tight clustering of other genes during exit from stationary-phase data set further indicates the physiological responses during G(0) exit are separable from cell-cycle events. Comparison of the two data sets showed that ribosomal-protein genes cluster tightly during exit from stationary phase, but are found in three significantly different clusters in the cell-cycle data set. Two protein-interaction data sets were also compared with the gene-expression data. Visual analysis of the complete data sets showed no clear correlation between co-expression of genes and protein interactions, in contrast to published reports examining subsets of the protein-interaction data. Neither two-hybrid study identified a large number of interactions between ribosomal proteins, consistent with recent structural data, indicating that for both data sets, the identification of false-positive interactions may be lower than previously thought.

Cell Cycle↗
PubMed2005

Expressed sequence tags from the laboratory-grown miniature tomato (Lycopersicon esculentum) cultivar Micro-Tom and mining for single nucleotide polymorphisms and insertions/deletions in tomato cultivars.

Laboratory-grown miniature tomato (Lycopersicon esculentum) cultivar Micro-Tom has attracted attention as a host for functional genomics research. In this study, we generated 35,824 expressed sequence tags (ESTs) from leaves and fruits of Micro-Tom. The ESTs comprised 10,287 unigenes (5007 contigs and 5280 singletons), including 1858 novel tomato unigenes. Of the 18 unigenes that shared strong homology with tobacco chloroplast genome sequences, one unigene was likely derived from polyadenylated transcripts of the atpH gene. Interestingly, ESTs for vacuolar invertase, pectate lyase and alcohol acyl transferase were underrepresented in the Micro-Tom data set. From all of the ESTs, we mined 2039 candidate single nucleotide polymorphisms (SNPs) and 121 candidate insertions and deletions (indels) based on homology with four tomato inbred lines, E6203, R11-13, Rio Grande PtoR and R11-12, and a wild relative, L. pennellii TA56, for which sequence data was publicly available with more than 5000 entries. Direct genome sequencing of several SNP or indel sites in Micro-Tom and L. esculentum E6203 suggested that more than 69% of the candidate sites were truly polymorphic, making them useful for the preparation of DNA markers.

DNA, Complementary↗
PubMed2006

Genome-wide differential gene expression in children exposed to air pollution in the Czech Republic.

The Teplice area in the Czech Republic is a mining district where elevated levels of air pollution including airborne carcinogens, have been demonstrated, especially during winter time. This environmental exposure can impact human health; in particular children may be more vulnerable. To study the impact of air pollution in children at the transcriptional level, peripheral blood cells were subjected to whole genome response analysis, in order to identify significantly modulated biological pathways and processes as a result of exposure. Using genome-wide oligonucleotide microarrays, we investigated differential gene expression in children from the Teplice area (n=23) and compared them with children from the rural control area of Prachatice (n=24). In an additional approach, individual gene expressions were correlated with individual peripheral blood lymphocyte micronuclei frequencies, in order to evaluate the linkage of individual gene expressions with an established biomarker of effect that is representative for increased genotoxic risk. Children from the Teplice area showed a significantly higher average micronuclei frequency than Prachatice children (p=0.023). For considerable numbers of genes, the expression differed significantly between the children from the two areas. Amongst these genes, considerable numbers of genes were observed to correlate significantly with the frequencies of micronuclei. The main biological process that appeared significantly affected overall was nucleosome assembly. This suggests an effect of air pollution on the primary structural unit of the condensed DNA. In addition, several other pathways were modulated. Based on the results of this study, we suggest that transcriptomic analysis represents a promising biomarker for environmental carcinogenesis.

Air Pollutants↗
PubMed2003

Accelerating comparative genomics using parallel computing.

In the past decade there has been an increase in the number of completely sequenced genomes due to the race of multibillion-dollar genome-sequencing projects. The enormous biological sequence data thus flooding into the sequence databases necessitates the development of efficient tools for comparative genome sequence analysis. The information deduced by such analysis has various applications viz. structural and functional annotation of novel genes and proteins, finding gene order in the genome, gene fusion studies, constructing metabolic pathways etc. Such study also proves invaluable for pharmaceutical industries, such as in silico drug target identification and new drug discovery. There are various sequence analysis tools available for mining such useful information of which FASTA and Smith-Waterman algorithms are widely used. However, analyzing large datasets of genome sequences using the above codes seems to be impractical on uniprocessor machines. Hence there is a need for improving the performance of the above popular sequence analysis tools on parallel cluster computers. Performance of the Smith-Waterman (SSEARCH) and FASTA programs were studied on PARAM 10000, a parallel cluster of workstations designed and developed in-house. FASTA and SSEARCH programs, which are available from the University of Virginia, were ported on PARAM and were optimized. In this era of high performance computing, where the paradigm is shifting from conventional supercomputers to the cost-effective general-purpose cluster of workstations and PCs, this study finds extreme relevance. Good performance of sequence analysis tools on a cluster of workstations was demonstrated, which is important for accelerating identification of novel genes and drug targets by screening large databases.

Algorithms↗
PubMedDate not supplied

[Construction and characterization of normalized cDNA library of maize inbred Mo17 from multiple tissues and developmental stages].

Comprehensive complementary DNA (cDNA) library is a valuable resource for functional genomics. In this study, we set up a normalized cDNA library of Mo17 (MONL) by saturation hybridization with genomic DNA, which contained expressed genes of eight tissues and organs from inbred Mo17 of maize (Zea mays L.). In this library, the insert sizes range from 0.4 kb to 4 kb and the average size is 1.18 kb. 10.830 clones were spotted on nylon membrane to make a cDNA microarray. Randomly picked 300 clones from the cDNA library were sequenced. The cDNA microarry was hybridized with pooled tissue mRNA probes or housekeeping gene cDNA probes. The results showed the normalized cDNA library comprehensively includes tissue-specific genes in which 71% are unique ESTs (expressed sequence tags) based on the 300 sequences analyzed. Using BLAST program to compare the sequences against online nucleotide databases, 88% sequences were found in ZmDB or NCBI, and 12% sequences were not found in existing nucleotide databases. More than 73% sequences are of unknown function. The library could be extensively used in developing DNA markers, sequencing ESTs, mining new genes, identifying positional cloning and candidate gene, and developing microarrays in maize genomics research.

Base Sequence↗
PubMed1999

THE CAENORHABDITIS ELEGANS GENOME: A Guide in The Post Genomics Age.

The completion of the entire genome sequence of the free-living nematode, Caenorhabditis elegans is a tremendous milestone in modern biology. Not only will scientists be poring over data mined from this resource, but techniques and methodologies developed along the way have changed the way we can approach biological questions. The completion of the C. elegans genomic sequence will be of particular importance to scientists working on parasitic nematodes. In many cases, these nematode species present intractable challenges to those interested in their biology and genetics. The data already compared from parasites to the C. elegans database reveals a wealth of opportunities for parasite biologists. It is likely that many of the same genes will be present in parasites and that these genes will have similar functions. Additional information regarding differences between free-living and parasitic species will provide insight into the evolution and nature of parasitism. Finally, genetic and genomic approaches to the study of parasitic nematodes now have a clearly marked path to follow.

Journal Article↗
PubMed2004

Public sphere and the sustainability of the bioinformatics promise.

The literature about genomics and bioinformatics achievements in high-impact journals such as Nature and Science has raised disproportionate expectations amongst the general public about fast and revolutionary drugs and breakthroughs in biomedicine. However, the yield obtained by database mining activities has been modest, as reported in the February 2001 issues of these journals featuring the completion of human genome draft sequences by the Human Genome Project Consortium and the company Celera. I have compared changes in rethoric employed by molecular biologists in 2001 and in April 2003, when the final sequence was announced. The comparison suggests that researchers are concerned about the sustainability of society's investment in this field, though not explicitly.

Bibliometrics↗
PubMed2002

Gene expression profile of human bone marrow stromal cells: high-throughput expressed sequence tag sequencing analysis.

Human bone marrow stromal cells (HBMSC) are pluripotent cells with the potential to differentiate into osteoblasts, chondrocytes, myelosupportive stroma, and marrow adipocytes. We used high-throughput DNA sequencing analysis to generate 4258 single-pass sequencing reactions (known as expressed sequence tags, or ESTs) obtained from the 5' (97) and 3' (4161) ends of human cDNA clones from a HBMSC cDNA library. Our goal was to obtain tag sequences from the maximum number of possible genes and to deposit them in the publicly accessible database for ESTs (dbEST of the National Center for Biotechnology Information). Comparisons of our EST sequencing data with nonredundant human mRNA and protein databases showed that the ESTs represent 1860 gene clusters. The EST sequencing data analysis showed 60 novel genes found only in this cDNA library after BLAST analysis against 3.0 million ESTs in NCBI's dbEST database. The BLAST search also showed the identified ESTs that have close homology to known genes, which suggests that these may be newly recognized members of known gene families. The gene expression profile of this cell type is revealed by analyzing both the frequency with which a message is encountered and the functional categorization of expressed sequences. Comparing an EST sequence with the human genomic sequence database enables assignment of an EST to a specific chromosomal region (a process called digital gene localization) and often enables immediate partial determination of intron/exon boundaries within the genomic structure. It is expected that high-throughput EST sequencing and data mining analysis will greatly promote our understanding of gene expression in these cells and of growth and development of the skeleton.

Bone Marrow Cells↗
PubMed2006

Drought tolerance genes in rice.

Quantitative trait loci (QTLs) for drought tolerance (DT) can be readily identified in available databases and in this paper, these QTLs were summarized in the form of a consensus map. An in silico strategy was then deployed to mine for candidate genes associated with DT QTLs using rice dbEST and rice genome databases. DT QTLs on rice chromosomes 1, 2, 4, 8, and 9 were selected to test the method. The result showed candidate genes associated with DT could be readily identified.

Acclimatization↗
PubMed2024

A novel molecular pathway of lipid accumulation in human hepatocytes caused by PFOA and PFOS.

Exposed to ubiquitously perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) has been associated with non-alcoholic fatty liver disease (NAFLD), yet the underlying molecular mechanism remains elusive. The extrapolation of empirical studies correlating per- and polyfluoroalkyl substance (PFAS) exposure with NAFLD occurrence to real-life exposure was hindered by the limited availability of mechanistic data at environmentally relevant concentrations. Herein, a novel pathway mediating hepatocyte lipid accumulation by PFOA and PFOS at human-relevant dose (<10&#xa0;&#x3bc;M) was identified by integrating CRISPR-Cas9 genome screening, concentration-dependent transcriptional assay in HepG2 cell and epidemiological data mining. 1) At genetic level, nudt7 showed the highest enriched potency among 569 NAFLD-related genes, and the transcription of nudt7 was significantly downregulated by PFOA and PFOS exposure (<7 &#x3bc;M). 2) At molecular pathway, upon exposure to&#xa0;&#x2264;10-4&#xa0;&#x3bc;M PFOA and PFOS, the downregulation of nudt7 transcriptional expression triggered the reduction of Ace-CoA hydrolase activity. 3) At cellular level, increased lipids were measured in HepG2 cells with PFOA and PFOS (<2&#xa0;&#x3bc;M). Overall, we identified a novel mechanism mediated by transcriptional downregulation of nudt7 gene in hepatocellular lipid increase treated with PFOA and PFOS, which could potentially explain the NAFLD occurrence associated with exposure to PFASs in humans.

Humans↗
PubMed2006

Extracting gene networks for low-dose radiation using graph theoretical algorithms.

Genes with common functions often exhibit correlated expression levels, which can be used to identify sets of interacting genes from microarray data. Microarrays typically measure expression across genomic space, creating a massive matrix of co-expression that must be mined to extract only the most relevant gene interactions. We describe a graph theoretical approach to extracting co-expressed sets of genes, based on the computation of cliques. Unlike the results of traditional clustering algorithms, cliques are not disjoint and allow genes to be assigned to multiple sets of interacting partners, consistent with biological reality. A graph is created by thresholding the correlation matrix to include only the correlations most likely to signify functional relationships. Cliques computed from the graph correspond to sets of genes for which significant edges are present between all members of the set, representing potential members of common or interacting pathways. Clique membership can be used to infer function about poorly annotated genes, based on the known functions of better-annotated genes with which they share clique membership (i.e., "guilt-by-association"). We illustrate our method by applying it to microarray data collected from the spleens of mice exposed to low-dose ionizing radiation. Differential analysis is used to identify sets of genes whose interactions are impacted by radiation exposure. The correlation graph is also queried independently of clique to extract edges that are impacted by radiation. We present several examples of multiple gene interactions that are altered by radiation exposure and thus represent potential molecular pathways that mediate the radiation response.

Algorithms↗
PubMed2005

Mining colon cancer specific alternative splicing in EST database.

Among 75218 splicing sites, 137 colon cancer specific alternative splicing isoforms were found by mining EST database. Alternative splicing database were first constructed by aligning EST to genomic sequence. Numbers of ESTs from normal or cancer colon tissue supporting splicing isoform at each splicing site were then queried and analyzed with Fisher exact test. There were 53 3' splicing, 42 5' splicing, 40 exon skipping and 2 mutual exclusive cancer specific splicing isoforms.

Alternative Splicing↗
PubMed2001

[Application of DNA chip technology to biomedical research].

The completion of Human Genome Project enabled us to access to the information on nucleotide sequences of whole human genome. One of the most valuable information on human genome would be the list of approximately 35,000 genes. Although 35% of them are still needed to annotate their functions, we can genome-widely approach to various conditions including disease states. To analyze bunch of information at once, we need high-throughput technology containing most of genes. DNA chip successfully provide a stable platform technology for the massive screening of genomes. Microarrays can be used to obtain genome-wide fingerprint on transcriptional changes in various physiological and pathological conditions, leading to the mining novel genes related to those specific states. We can check the multiple molecular markers for diagnosis, prediction or prognosis of specific diseases. Data from microarray will provide huge amounts of experssion profile, which might induce the transformation of biomedical research.

Base Sequence↗
PubMed2005

A probabilistic model for mining implicit 'chemical compound-gene' relations from literature.

MOTIVATION: The importance of chemical compounds has been emphasized more in molecular biology, and 'chemical genomics' has attracted a great deal of attention in recent years. Thus an important issue in current molecular biology is to identify biological-related chemical compounds (more specifically, drugs) and genes. Co-occurrence of biological entities in the literature is a simple, comprehensive and popular technique to find the association of these entities. Our focus is to mine implicit 'chemical compound and gene' relations from the co-occurrence in the literature. RESULTS: We propose a probabilistic model, called the mixture aspect model (MAM), and an algorithm for estimating its parameters to efficiently handle different types of co-occurrence datasets at once. We examined the performance of our approach not only by a cross-validation using the data generated from the MEDLINE records but also by a test using an independent human-curated dataset of the relationships between chemical compounds and genes in the ChEBI database. We performed experimentation on three different types of co-occurrence datasets (i.e. compound-gene, gene-gene and compound-compound co-occurrences) in both cases. Experimental results have shown that MAM trained by all datasets outperformed any simple model trained by other combinations of datasets with the difference being statistically significant in all cases. In particular, we found that incorporating compound-compound co-occurrences is the most effective in improving the predictive performance. We finally computed the likelihoods of all unknown compound-gene (more specifically, drug-gene) pairs using our approach and selected the top 20 pairs according to the likelihoods. We validated them from biological, medical and pharmaceutical viewpoints.

Artificial Intelligence↗
PubMed2006

The ASAP II database: analysis and comparative genomics of alternative splicing in 15 animal species.

We have greatly expanded the Alternative Splicing Annotation Project (ASAP) database: (i) its human alternative splicing data are expanded approximately 3-fold over the previous ASAP database, to nearly 90,000 distinct alternative splicing events; (ii) it now provides genome-wide alternative splicing analyses for 15 vertebrate, insect and other animal species; (iii) it provides comprehensive comparative genomics information for comparing alternative splicing and splice site conservation across 17 aligned genomes, based on UCSC multigenome alignments; (iv) it provides an approximately 2- to 3-fold expansion in detection of tissue-specific alternative splicing events, and of cancer versus normal specific alternative splicing events. We have also constructed a novel database linking orthologous exons and orthologous introns between genomes, based on multigenome alignment of 17 animal species. It can be a valuable resource for studies of gene structure evolution. ASAP II provides a new web interface enabling more detailed exploration of the data, and integrating comparative genomics information with alternative splicing data. We provide a set of tools for advanced data-mining of ASAP II with Pygr (the Python Graph Database Framework for Bioinformatics) including powerful features such as graph query, multigenome alignment query, etc. ASAP II is available at http://www.bioinformatics.ucla.edu/ASAP2.

Alternative Splicing↗
PubMed2000

Human genome. Finally, the book of life and instructions for navigating it.

The race is over. On 26 June, to much fanfare, two rival teams announced that they had each completed a version of the "book of life"--a rough draft of the complete human genetic code. So what, exactly, is in these two different volumes, and how will they fine-tune it so that everyone from workaday biologists to pharmaceutical giants can mine its gold?

Animals↗
PubMed2005

Mining time-dependent gene features.

This paper presents an application of the Independent Component Analysis (ICA) method to genomic data. In particular, experimentally produced perturbation effects over the E.coli bacterium are monitored through the changes of gene expression values observed at regular times, and until steady state has been reached. The aim is to control the response of the SOS system to DNA damage. We might assume that only part of the genetic regulatory network is affected directly by the perturbation conditions, as indirect cascade effects might also be present, and some genes may change just because of randomness. ICA decomposes the gene matrix and identifies groups of genes belonging to a certain estimated component by virtue of co-expression; it is of course of interest to establish co-regulation dynamics, which might underlie the captured correlation. Stronger forms of dependence, like Mutual Information, are thus computed and compared with linear correlation in order to validate the results and establish the role of the identified components in determining the network dynamics.

Algorithms↗