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At least 379 records · Page 21Linked to original sources
PubMed2006

A comprehensive comparative analysis of the occurrence of developmental sequences in fungal, plant and animal genomes.

We report a fully comprehensive data-mining exercise, involving an estimated total of 590,000 similarity searches, using agents available on the Internet to search for homologies to polypeptide sequences assigned to the category 'development' in the Gene Ontology Consortium AmiGO database (www.godatabase.org). The results indicate that of 552 such developmental sequences only 78 are shared between all three kingdoms, 72 are shared only between fungi and animals, 58 sequences are shared between plants and fungi, and four sequences were common only to Dictyostelium and fungi. No sequences were strictly fungus specific, but 68 occurred only in plants (Viridiplantae) and 239 occurred only in animals (Metazoa). Although some homology was indicated for a total of 219 fungal sequences, 143 (65%) of the matches returned were assigned E-values of 0.05 and must be categorised as weak similarities at best. The majority of the highly similar matches found in this survey proved to be between sequences involved in basic cell metabolism or essential eukaryotic cell processes (enzymes in common metabolic pathways, transcription regulators, binding proteins, receptors and membrane proteins). What is lacking is cross-kingdom similarity in the management processes that regulate multicellular development. The crown group of eukaryotic kingdoms control and regulate their developmental processes in very different ways. Unfortunately, we know nothing about molecular control of multicellular fungal developmental biology.

Amino Acid Sequence↗
PubMed1998

The Merck Gene Index browser: an extensible data integration system for gene finding, gene characterization and EST data mining.

MOTIVATION: To make effective use of the vast amounts of expressed sequence tag (EST) sequence data generated by the Merck-sponsored EST project and other similar efforts, sequences must be organized into gene classes, and scientists must be able to 'mine' the gene class data in the context of related genomic data. RESULTS: This paper presents the Merck Gene Index browser, an easily extensible, World Wide Web-based system for mining the Merck Gene Index (MGI) and related genomic data. The MGI is a non-redundant set of clones and sequences, each representing a distinct gene, constructed from all high-quality 3' EST sequences generated by the Merck-sponsored EST project. The MGI browser integrates data from a variety of sources and storage formats, both local and remote, using an eclectic integration strategy, including a federation of relational databases, a local data warehouse and simple hypertext links. Data currently integrated include: LENS cDNA clone and EST data, dbEST protein and non-EST nucleic acid similarity data, WashU sequence chromatograms. Entrez sequence and Medline entries, and UniGene gene clusters. Flatfile sequence data are accessed using the Bioapps server, an internally developed client-server system that supports generic sequence analysis applications. Browser data are retrieved and formatted by means of the Bioinformatics Data Integration Toolkit (B-DIT), a new suite of Perl routines.

Abstracting and Indexing↗
PubMed2005

The bioinformatics resource for oral pathogens.

Complete genomic sequences of several oral pathogens have been deciphered and multiple sources of independently annotated data are available for the same genomes. Different gene identification schemes and functional annotation methods used in these databases present a challenge for cross-referencing and the efficient use of the data. The Bioinformatics Resource for Oral Pathogens (BROP) aims to integrate bioinformatics data from multiple sources for easy comparison, analysis and data-mining through specially designed software interfaces. Currently, databases and tools provided by BROP include: (i) a graphical genome viewer (Genome Viewer) that allows side-by-side visual comparison of independently annotated datasets for the same genome; (ii) a pipeline of automatic data-mining algorithms to keep the genome annotation always up-to-date; (iii) comparative genomic tools such as Genome-wide ORF Alignment (GOAL); and (iv) the Oral Pathogen Microarray Database. BROP can also handle unfinished genomic sequences and provides secure yet flexible control over data access. The concept of providing an integrated source of genomic data, as well as the data-mining model used in BROP can be applied to other organisms. BROP can be publicly accessed at http://www.brop.org.

Bacteria↗
PubMed2006

A Fourier transformation based method to mine peptide space for antimicrobial activity.

BACKGROUND: Naturally occurring antimicrobial peptides are currently being explored as potential candidate peptide drugs. Since antimicrobial peptides are part of the innate immune system of every living organism, it is possible to discover new candidate peptides using the available genomic and proteomic data. High throughput computational techniques could also be used to virtually scan the entire peptide space for discovering out new candidate antimicrobial peptides. RESULT: We have identified a unique indexing method based on biologically distinct characteristic features of known antimicrobial peptides. Analysis of the entries in the antimicrobial peptide databases, based on our indexing method, using Fourier transformation technique revealed a distinct peak in their power spectrum. We have developed a method to mine the genomic and proteomic data, for the presence of peptides with potential antimicrobial activity, by looking for this distinct peak. We also used the Euclidean metric to rank the potential antimicrobial peptides activity. We have parallelized our method so that virtually any given protein space could be data mined, in search of antimicrobial peptides. CONCLUSION: The results show that the Fourier transform based method with the property based coding strategy could be used to scan the peptide space for discovering new potential antimicrobial peptides.

Amino Acid Sequence↗
PubMed2004

Data mining of gene expression changes in Alzheimer brain.

Genome-wide transcription profiling is a powerful technique for studying the enormous complexity of cellular states. Moreover, when applied to disease tissue it may reveal quantitative and qualitative alterations in gene expression that give information on the context or underlying basis for the disease and may provide a new diagnostic approach. However, the data obtained from high-density microarrays is highly complex and poses considerable challenges in data mining. The data requires care in both pre-processing and the application of data mining techniques. This paper addresses the problem of dealing with microarray data that come from two known classes (Alzheimer and normal). We have applied three separate techniques to discover genes associated with Alzheimer disease (AD). The 67 genes identified in this study included a total of 17 genes that are already known to be associated with Alzheimer's or other neurological diseases. This is higher than any of the previously published Alzheimer's studies. Twenty known genes, not previously associated with the disease, have been identified as well as 30 uncharacterized expressed sequence tags (ESTs). Given the success in identifying genes already associated with AD, we can have some confidence in the involvement of the latter genes and ESTs. From these studies we can attempt to define therapeutic strategies that would prevent the loss of specific components of neuronal function in susceptible patients or be in a position to stimulate the replacement of lost cellular function in damaged neurons. Although our study is based on a relatively small number of patients (four AD and five normal), we think our approach sets the stage for a major step in using gene expression data for disease modeling (i.e. classification and diagnosis). It can also contribute to the future of gene function identification, pathology, toxicogenomics, and pharmacogenomics.

Alzheimer Disease↗
PubMed2005

An in silico mining for simple sequence repeats from expressed sequence tags of zebrafish, medaka, Fundulus, and Xiphophorus.

Teleost fish genome projects involving model species are resulting in a rapid accumulation of genomic and expressed DNA sequences in public databases. The expressed sequence tags (ESTs) collected in the databases can be mined for the analysis of both structural and functional genomics. In this study, we in silico analyzed 49,430 unigenes representing a total of 692,654 ESTs from four model fish for their potential use in developing simple sequence repeats (SSRs), or microsatellites. After bioinformatical mining, a total of 3,018 EST derived SSRs (EST-SSRs) were identified for 2,335 SSR containing ESTs (SSR-ESTs). The frequency of identified SSR-ESTs ranged from 1.5% for Xiphophorus to 7.3% for zebrafish. The dinucleotide repeat motif is the most abundant SSR, accounting for 47%, 52%, 64%, and 78% for medaka, Fundulus, zebrafish, and Xiphophorus, respectively. Simulation analysis suggests that a majority of these EST-SSRs have sufficient flanking sequences for polymerase chain reaction (PCR) primer design. Comparative DNA sequence analyses of SSR-ESTs identified several cross-species SSRs and sequences that may be used as cross-reference genes in comparative studies. For example, the flanking sequences of one SSR (CTG)n within the pituitary tumor-transforming gene (PTTG) 1 interacting protein (PTTGIP), showed conservation spanning the medaka, Fundulus, human, and mouse genomes. This study provides a large body of information on EST-SSRs that can be useful for the development of polymorphic markers, gene mapping, and comparative genome analysis. Functional analysis of these SSR-ESTs may reveal their role in metabolism and gene evolution of these model species.

Amino Acid Sequence↗
PubMed2005

Integration of text- and data-mining using ontologies successfully selects disease gene candidates.

Genome-wide techniques such as microarray analysis, Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS), linkage analysis and association studies are used extensively in the search for genes that cause diseases, and often identify many hundreds of candidate disease genes. Selection of the most probable of these candidate disease genes for further empirical analysis is a significant challenge. Additionally, identifying the genes that cause complex diseases is problematic due to low penetrance of multiple contributing genes. Here, we describe a novel bioinformatic approach that selects candidate disease genes according to their expression profiles. We use the eVOC anatomical ontology to integrate text-mining of biomedical literature and data-mining of available human gene expression data. To demonstrate that our method is successful and widely applicable, we apply it to a database of 417 candidate genes containing 17 known disease genes. We successfully select the known disease gene for 15 out of 17 diseases and reduce the candidate gene set to 63.3% (+/-18.8%) of its original size. This approach facilitates direct association between genomic data describing gene expression and information from biomedical texts describing disease phenotype, and successfully prioritizes candidate genes according to their expression in disease-affected tissues.

Anatomy↗
PubMed2003

Molecular analysis of cancer using DNA and protein microarrays.

In conclusion, array-based technologies have emerged that contribute to profiling tissues at the genomic, transcriptomic and proteomic levels. Analytical tools are needed to mine the vast amount of data generated. Ultimately the molecular analysis of cancer at a genome and proteome scale will allow better classification of disease and tailored individualized therapy for individual patients.

Biotechnology↗
PubMed2005

Is insulin signaling molecules misguided in diabetes for ubiquitin-proteasome mediated degradation?

Recent mining of the human and mouse genomes, use of yeast genetics, and detailed analyses of several biochemical pathways, have resulted in the identification of many new roles for ubiquitin-proteasome mediated degradation of proteins. In the context of last year's award of Noble Prize (Chemistry) work, the ubiquitin and ubiquitin-like modifications are increasingly recognized as key regulatory events in health and disease. Although the ATP-dependent ubiquitin-proteasome system has evolved as premier cellular proteolytic machinery, dysregulation of this system by several different mechanisms leads to inappropriate degradation of specific proteins and pathological consequences. While aberrations in the ubiquitin-proteasome pathway have been implicated in certain malignancies and neurodegenerative disorders, recent studies indicate a role for this system in the pathogenesis of diabetes and its complications. Inappropriate degradation of insulin signaling molecules such as insulin receptor substrates (IRS-1 and IRS-2) has been demonstrated in experimental diabetes, mediated in part through the up-regulation of suppressors of cytokine signaling (SOCS). It appears that altered ubiquitin-proteasome system might be one of the molecular mechanisms of insulin resistance in many pathological situations. Drugs that modulate the SOCS action and/or proteasomal degradation of proteins could become novel agents for the treatment of insulin resistance and Type 2 diabetes.

Adenosine Triphosphate↗
PubMed2004

Mining single nucleotide polymorphisms from EST data of silkworm, Bombyx mori, inbred strain Dazao.

We made use of 81,635 expressed sequence tags (ESTs) derived from 12 different cDNA libraries of the silkworm, Bombyx mori, inbred strain Dazao (P50), to identify high-quality candidate single nucleotide polymorphisms (SNPs). By PHRAP assembling, 12,980 contigs containing 11,537 contigs assembled by more than one read were obtained, and 101 candidate SNPs and 27 single base insertions/deletions were identified from 117 contigs assembled from 1576 high-quality reads base-called with PHRED and screened on the basis of the neighborhood quality standard (NQS). Simultaneously, we also predicted 40 SNPs in coding regions (cSNPs), of which 26 were predicted to lead to amino acid non-synonymous variations and 14 synonymous substitutions. Also, the 1.66:1 ratio of transition/transversion is different from that of other insects. As the first SNP analysis of a Lepidoptera, B. mori, the single nucleotide polymorphic density is estimated to be 1.3 x 10(-3) by sequence diversity. This analysis shows that expressed sequences from multiple libraries may provide an abundant source of comparative reads to mine for cSNPs from the silkworm genome.

Amino Acid Substitution↗
PubMed2002

A molecular profile of a hematopoietic stem cell niche.

The hematopoietic microenvironment provides a complex molecular milieu that regulates the self-renewal and differentiation activities of stem cells. We have characterized a stem cell supportive stromal cell line, AFT024, that was derived from murine fetal liver. Highly purified in vivo transplantable mouse stem cells are maintained in AFT024 cultures at input levels, whereas other primitive progenitors are expanded. In addition, human stem cells are very effectively supported by AFT024. We suggest that the AFT024 cell line represents a component of an in vivo stem cell niche. To determine the molecular signals elaborated in this niche, we undertook a functional genomics approach that combines extensive sequence mining of a subtracted cDNA library, high-density array hybridization and in-depth bioinformatic analyses. The data have been assembled into a biological process oriented database, and represent a molecular profile of a candidate stem cell niche.

Amino Acid Sequence↗
PubMed2003

Transcriptome analysis of Sinorhizobium meliloti during symbiosis.

BACKGROUND: Rhizobia induce the formation on specific legumes of new organs, the root nodules, as a result of an elaborated developmental program involving the two partners. In order to contribute to a more global view of the genetics underlying this plant-microbe symbiosis, we have mined the recently determined Sinorhizobium meliloti genome sequence for genes potentially relevant to symbiosis. We describe here the construction and use of dedicated nylon macroarrays to study simultaneously the expression of 200 of these genes in a variety of environmental conditions, pertinent to symbiosis. RESULTS: The expression of 214 S. meliloti genes was monitored under ten environmental conditions, including free-living aerobic and microaerobic conditions, addition of the plant symbiotic elicitor luteolin, and a variety of symbiotic conditions. Five new genes induced by luteolin have been identified as well as nine new genes induced in mature nitrogen-fixing bacteroids. A bacterial and a plant symbiotic mutant affected in nodule development have been found of particular interest to decipher gene expression at the intermediate stage of the symbiotic interaction. S. meliloti gene expression in the cultivated legume Medicago sativa (alfalfa) and the model plant M. truncatula were compared and a small number of differences was found. CONCLUSIONS: In addition to exploring conditions for a genome-wide transcriptome analysis of the model rhizobium S. meliloti, the present work has highlighted the differential expression of several classes of genes during symbiosis. These genes are related to invasion, oxidative stress protection, iron mobilization, and signaling, thus emphasizing possible common mechanisms between symbiosis and pathogenesis.

Cluster Analysis↗
PubMed2006

Machine learning in bioinformatics.

This article reviews machine learning methods for bioinformatics. It presents modelling methods, such as supervised classification, clustering and probabilistic graphical models for knowledge discovery, as well as deterministic and stochastic heuristics for optimization. Applications in genomics, proteomics, systems biology, evolution and text mining are also shown.

Artificial Intelligence↗
PubMed2006

OrthologID: automation of genome-scale ortholog identification within a parsimony framework.

MOTIVATION: The determination of gene orthology is a prerequisite for mining and utilizing the rapidly increasing amount of sequence data for genome-scale phylogenetics and comparative genomic studies. Until now, most researchers use pairwise distance comparisons algorithms, such as BLAST, COG, RBH, RSD and INPARANOID, to determine gene orthology. In contrast, orthology determination within a character-based phylogenetic framework has not been utilized on a genomic scale owing to the lack of efficiency and automation. RESULTS: We have developed OrthologID, a Web application that automates the labor-intensive procedures of gene orthology determination within a character-based phylogenetic framework, thus making character-based orthology determination on a genomic scale possible. In addition to generating gene family trees and determining orthologous gene sets for complete genomes, OrthologID can also identify diagnostic characters that define each orthologous gene set, as well as diagnostic characters that are responsible for classifying query sequences from other genomes into specific orthology groups. The OrthologID database currently includes several complete plant genomes, including Arabidopsis thaliana, Oryza sativa, Populus trichocarpa, as well as a unicellular outgroup, Chlamydomonas reinhardtii. To improve the general utility of OrthologID beyond plant species, we plan to expand our sequence database to include the fully sequenced genomes of prokaryotes and other non-plant eukaryotes. AVAILABILITY: http://nypg.bio.nyu.edu/orthologid/

Algorithms↗
PubMed2002

Herpesvirus genetics has come of age.

The genetic analysis of the large and complex herpesviruses has been a constant challenge to herpesvirologists. Elegant methods have been developed to produce mutants in infected cells that rely on the cellular recombination machinery. Bacterial artificial chromosomes (BACs), single copy F-factor-based plasmid vectors of intermediate insert capacity, have now enabled the cloning of complete herpesvirus genomes. Infectious virus genomes can be shuttled between Escherichia coli and eukaryotic cells. Herpesvirus BAC DNA engineering in E. coli by homologous recombination requires neither restriction sites nor cloning steps and allows the introduction of a wide variety of DNA modifications. Such E. coli-based technology has provided a safe, fast and effective approach to the systematic mining of the information stored in herpesvirus genomes as a result of their intimate co-evolution with their specific hosts for millions of years. Use of this technique could lead to new developments in clinical virology and basic virology research, and increase the usage of viral genomes as investigative tools and vectors.

Animals↗
PubMed2002

Long terminal repeat retrotransposons of Oryza sativa.

BACKGROUND: Long terminal repeat (LTR) retrotransposons constitute a major fraction of the genomes of higher plants. For example, retrotransposons comprise more than 50% of the maize genome and more than 90% of the wheat genome. LTR retrotransposons are believed to have contributed significantly to the evolution of genome structure and function. The genome sequencing of selected experimental and agriculturally important species is providing an unprecedented opportunity to view the patterns of variation existing among the entire complement of retrotransposons in complete genomes. RESULTS: Using a new data-mining program, LTR_STRUC, (LTR retrotransposon structure program), we have mined the GenBank rice (Oryza sativa) database as well as the more extensive (259 Mb) Monsanto rice dataset for LTR retrotransposons. Almost two-thirds (37) of the 59 families identified consist of copia-like elements, but gypsy-like elements outnumber copia-like elements by a ratio of approximately 2:1. At least 17% of the rice genome consists of LTR retrotransposons. In addition to the ubiquitous gypsy- and copia-like classes of LTR retrotransposons, the rice genome contains at least two novel families of unusually small, non-coding (non-autonomous) LTR retrotransposons. CONCLUSIONS: Each of the major clades of rice LTR retrotransposons is more closely related to elements present in other species than to the other clades of rice elements, suggesting that horizontal transfer may have occurred over the evolutionary history of rice LTR retrotransposons. Like LTR retrotransposons in other species with relatively small genomes, many rice LTR retrotransposons are relatively young, indicating a high rate of turnover.

Animals↗
PubMedDate not supplied

Models-of-data and models-of-processes in the post-genomic era.

As we are entering the post-genomic era, models-of-data, such as mining and filtering methods for gene sequences and microarrays and the clustering of co-expressed genes, must be complemented with models-of-processes that explain relationships between genomic information and phenomena at biochemical and physiological levels. Many of these models will have the structure of compartment models, whose conceptualization, identification and analysis will fundamentally benefit from the seminal work of John Jacquez. The article indicates with three vignettes that non-linear compartment models in the formulation of biochemical systems theory are viable candidates for post-genomic models-of-processes.

Animals↗
PubMed1998

Intron based radiation hybrid mapping of 15 complex I genes of the human electron transport chain.

At least 34 complex I subunits of the electron transport chain are encoded by the nuclear genome, but only 14 of these have been mapped in the human. To rapidly map additional subunits, we have performed a combination of database mining and direct "wet" experimentation to identify intron and/or 5' upstream genomic DNA regions for 16 complex I genes. Wet experimentation was applied to 5 genes, and involved direct PCR amplification of introns by inter-exon PCR or splinkerette based PCR walking. Database mining was applied to 11 genes, and entailed the identification of incompletely spliced mRNAs and genomic CpG island clone sequences. This data was in files that carried no documentary description of the non-exon regions. Non-exon sequences were thus derived for 15 complex I genes and used to design functional gene specific PCR assays. Radiation hybrid mapping of these PCRs located 15 complex I genes to chromosomes l, 4, 5 (2 genes), 7 (2 genes), 8, 9 (2 genes), 11, 14, 16 (2 genes), 18, and 19.

Chromosome Mapping↗