SEARCH · Search PubMed
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.
BIBI was designed to automate DNA sequence analysis for bacterial identification in the clinical field. BIBI relies on the use of BLAST and CLUSTAL W programs applied to different subsets of sequences extracted from GenBank. These sequences are filtered and stored in a new database, which is adapted to bacterial identification.
INTRODUCTION: Distant metastasis accounts for the majority of Breast Cancer (BC)-related mortality. The brain is one of the most common regions of metastasis. However, the underlying molecular mechanisms remain uncertain. METHODS: In this study, gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. Datasets GSE100534 and GSE52604, containing 16 primary brain tumor samples and 38 breast cancer brain metastasis samples, were used to identify the Differentially Expressed Genes (DEGs). The Metascape database was used to analyze enriched Gene Ontology (GO) entries and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway entries in DEGs. The STRING database was then used to construct a Protein-Protein Interaction (PPI) network, and the Cytoscape platform was employed to visualize the network. Furthermore, the Kaplan-Meier curve was used to analyze the Relapse-Free Survival (RFS) among the hub genes. Finally, the iRegulon plugin was used to construct a regulatory network to find the transcription factors (TFs) that regulate the expression of the hub genes. RESULTS: A total of 344 DEGs, including 182 up-regulated and 162 down-regulated genes, were identified by using the limma package in R. A module with 18 nodes and 9 hub genes was selected from the PPI network by using the plugins MCODE and Cyto- Hubba, respectively. KEGG pathway analysis demonstrated that brain metastasis in BC was closely related to the oocyte cell cycle. The Kaplan-Meier curve showed that high expression of these 9 hub genes was associated with poor RFS in BC patients. TFs' analysis showed that E2F4, SIN3A, FOXM1, and TFDP1 interacted with these hub genes. DISCUSSION: This study revealed that Breast Cancer Brain Metastasis (BCBM) may have a promoting effect on the cell cycle of oocytes and affect the maturation and division of oocytes through the KEGG and GO analyses of 344 DEGs. The selected 9 hub genes (ASPM, BUB1, BUB1B, CCNA2, CCNB1, CDK1, NDC80, NCAPG, and TOP2A) and 4 transcription factors (E2F4, SIN3A, FOXM1, TFDP1) may play a critical role in brain metastasis of BC. CONCLUSION: The results of this study may aid in the early diagnosis and suggest potential targets for the treatment of BCBM.
BACKGROUND: Many agricultural species and their pathogens have sequenced genomes and more are in progress. Agricultural species provide food, fiber, xenotransplant tissues, biopharmaceuticals and biomedical models. Moreover, many agricultural microorganisms are human zoonoses. However, systems biology from functional genomics data is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation and agricultural research communities are smaller with limited funding compared to many model organism communities. DESCRIPTION: To facilitate systems biology in these traditionally agricultural species we have established "AgBase", a curated, web-accessible, public resource http://www.agbase.msstate.edu for structural and functional annotation of agricultural genomes. The AgBase database includes a suite of computational tools to use GO annotations. We use standardized nomenclature following the Human Genome Organization Gene Nomenclature guidelines and are currently functionally annotating chicken, cow and sheep gene products using the Gene Ontology (GO). The computational tools we have developed accept and batch process data derived from different public databases (with different accession codes), return all existing GO annotations, provide a list of products without GO annotation, identify potential orthologs, model functional genomics data using GO and assist proteomics analysis of ESTs and EST assemblies. Our journal database helps prevent redundant manual GO curation. We encourage and publicly acknowledge GO annotations from researchers and provide a service for researchers interested in GO and analysis of functional genomics data. CONCLUSION: The AgBase database is the first database dedicated to functional genomics and systems biology analysis for agriculturally important species and their pathogens. We use experimental data to improve structural annotation of genomes and to functionally characterize gene products. AgBase is also directly relevant for researchers in fields as diverse as agricultural production, cancer biology, biopharmaceuticals, human health and evolutionary biology. Moreover, the experimental methods and bioinformatics tools we provide are widely applicable to many other species including model organisms.
The spatio-temporal expression pattern of a gene during development is a valuable piece of information. But there is no way to compare precisely the patterns of expression of different genes, or the way the patterns are changed in a mutant. One way to solve this problem is to construct digital reference images of development (a bioinformatics framework), to which expression patterns can be mapped and stored, then compared. Such frameworks are under active development in several model systems. They will form the basis of powerful and integrated gene expression databases, which facilitate comparisons between genes, tissues and species.
MOTIVATION: Comparison of nucleic acid and protein sequences is a fundamental tool of modern bioinformatics. A dominant method of such string matching is the 'seed-and-extend' approach, in which occurrences of short subsequences called 'seeds' are used to search for potentially longer matches in a large database of sequences. Each such potential match is then checked to see if it extends beyond the seed. To be effective, the seed-and-extend approach needs to catalogue seeds from virtually every substring in the database of search strings. Projects such as mammalian genome assemblies and large-scale protein matching, however, have such large sequence databases that the resulting list of seeds cannot be stored in RAM on a single computer. This significantly slows the matching process. RESULTS: We present a simple and elegant method in which only a small fraction of seeds, called 'minimizers', needs to be stored. Using minimizers can speed up string-matching computations by a large factor while missing only a small fraction of the matches found using all seeds.
ArrayExpress is a public microarray repository founded on the Minimum Information About a Microarray Experiment (MIAME) principles that stores MIAME-compliant gene expression data. Plant-based data sets represent approximately one-quarter of the experiments in ArrayExpress. The majority are based on Arabidopsis (Arabidopsis thaliana); however, there are other data sets based on Triticum aestivum, Hordeum vulgare, and Populus subsp. AtMIAMExpress is an open-source Web-based software application for the submission of Arabidopsis-based microarray data to ArrayExpress. AtMIAMExpress exports data in MAGE-ML format for upload to any MAGE-ML-compliant application, such as J-Express and ArrayExpress. It was designed as a tool for users with minimal bioinformatics expertise, has comprehensive help and user support, and represents a simple solution to meeting the MIAME guidelines for the Arabidopsis community. Plant data are queryable both in ArrayExpress and in the Data Warehouse databases, which support queries based on gene-centric and sample-centric annotation. The AtMIAMExpress submission tool is available at http://www.ebi.ac.uk/at-miamexpress/. The software is open source and is available from http://sourceforge.net/projects/miamexpress/. For information, contact miamexpress@ebi.ac.uk.
The stomatogastric nervous system (STNS) is a premiere model for studying modulation of motor pattern generation. Whereas the cellular and network responses to monoamines have been particularly well characterized electrophysiologically, the transduction mechanisms that link the different monoaminergic signals to specific intracellular responses are presently unknown in this system. To begin to elucidate monoaminergic signal transduction in pyloric neurons, we used a bioinformatics approach to predict the existence of 18 monoamine receptors in arthropods, 9 of which have been previously cloned in Drosophila and other insects. We then went on to use the two existing insect databases to clone and characterize the 10th putative arthropod receptor from the spiny lobster, Panulirus interruptus. This receptor is most homologous to the 5-HT2 subtype and shows a dose-dependent response to 5-HT but not to any of the other monoamines present in the STNS. Through a series of pharmacological experiments, we demonstrate that this newly described receptor, 5-HT2betaPan, couples with the traditional G(q) pathway when expressed in HEK293 cells, but not to G(s) or G(i/o). Moreover, it is constitutively active, because the highly conserved DRY motif in transmembrane region 3 has evolved into DRF. Site-directed mutagenesis that reverts the motif back to DRY abolishes this agonist-independent activity. We further demonstrate that this receptor most likely participates in the modulation of stomatogastric motor output, because it is found in neurites in the synaptic neuropil of the stomatogastric ganglion as well as in the axon terminals at identified pyloric neuromuscular junctions.
Recent improvements in DNA microarray technologies and bioinformatics have made it possible to look for common features of ionizing radiation-responsive genes and their regulatory regions. We analyzed the promoters of 217 radiation-responsive human genes, compiled from microarray databases available in the literature. Using the DBTSS database, the transcriptional start sites were determined, and the core promoter elements, such as the TATA-box, initiator (Inr), GC-box and CCAAT-box, were searched for in the -1000 bp/ +200 bp region of each gene by using MATCH. It was found that the frequency of Inr in radiation-responsive genes was higher than that in general genes, and the frequencies of the GC-box and CCAAT-box were significantly lower than those in general genes. Use of the GC-box and the CCAAT-box in radiation-responsive genes was found to be dependent on the TATA-box status; that is, GC-box frequency was low in TATA box-containing genes, and CCAAT-box frequency was also low in TATA-less genes. When correlations between gene functions and frequencies of core promoter elements were examined, no apparent biased use of the core promoter element in association with a specific gene function was observed. It may be speculated that use of Inr in the core promoter correlates with appearance of radiation-responsive enhancer (silencer) elements in the upstream (downstream) regulatory region.
The assessment of residue conservation in a multiple sequence alignment is a central issue in bioinformatics. Conserved residues and regions are used to determine structural and functional motifs or evolutionary relationships between the sequences of a multiple sequence alignment. For this reason, residue conservation is a valuable measure for database and motif search or for estimating the quality of alignments. In this paper, we present statistical methods for identifying conserved residues in multiple sequence alignments. While most earlier studies examine the positional conservation of the alignment, we focus on the detection of individual conserved residues at a position. The major advantages of multiple comparison methods originate from their ability to select conserved residues simultaneously and to consider the variability of the residue estimates. Large-scale simulations were used for the comparative analysis of the methods. Practical performance was studied by comparing the structurally and functionally important residues of Src homology 2 (SH2) domains to the assignments of the conservation indices. The applicability of the indices was also compared in three additional protein families comprising different degrees of entropy and variability in alignment positions. The results indicate that statistical multiple comparison methods are sensitive and reliable in identifying conserved residues.
Bioinformatics can play an important role in developing improved technology for the detection and characterization of food allergens. However, the full realization of this potential will depend on the development of allergen-specific databases as well as improved methods for data mining within these databases. Examples of existing allergen databases and analysis tools are described, as are the most important issues that need to be addressed in the next stage of database development.
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.
In this paper we present the work carried out within INFOBIOMED, the European Network of Excellence (NoE) in Biomedical Informatics, to facilitate training and mobility in the area. An analysis of past experiences in both Medical Informatics and Bioinformatics has led to various actions. In this scenario, we have elaborated three actions: (1) a survey of the training and mobility situation, needs and actions to be taken, (2) a Biomedical Informatics course database (ICD), and (3) a Mobility Brokerage Service (MBS). We describe the use of Web Services to build the MBS, designed to facilitate the exchange of professionals within the consortium, belonging to ten European countries. The goal of INFOBIOMED is to expand these initiatives to other NoEs and institutions within the European Union.
ESTWeb is an internet based software package designed for uniform data processing and storage for large-scale EST sequencing projects. The package provides for: (a) reception of sequencing chromatograms; (b) sequence processing such as base-calling, vector screening, comparison with public databases; (c) storage of data and analysis in a relational database, (d) generation of a graphical report of individual sequence quality; and (e) issuing of reports with statistics of productivity and redundancy. The software facilitates real-time monitoring and evaluation of EST sequence acquisition progress along an EST sequencing project.
To specify the C-terminal peroxisome targeting signal type 1 (PTS1) and the N-terminal PTS2 for higher plants, a maximum number of plant cDNAs and expressed sequence tags that are homologous to PTS1- and PTS2-targeted plant proteins was retrieved from the public databases and the primary structure of their targeting domains was analyzed for conserved properties. According to their high overall frequency in the homologs and their widespread occurence in different orthologous groups, nine major PTS1 tripeptides ([SA][RK][LM]> without AKM> plus SRI> and PRL>) and two major PTS2 nonapeptides (R[LI]x5HL) were defined that are considered good indicators for peroxisomal localization if present in unknown proteins. A lower but significant number of homologs contained 1 of 11 minor PTS1 tripeptides or of 9 minor PTS2 nonapeptides, many of which have not been identified before in plant peroxisomal proteins. The region adjacent to the PTS peptides was characterized by specific conserved properties as well, such as a pronounced incidence of basic and Pro residues and a high positive net charge, which probably play an auxiliary role in peroxisomal targeting. By contrast, several peptides with assumed peroxisomal targeting properties were not found in any of the 550 homologs and hence play--if at all--only a minor role in peroxisomal targeting. Based on the definition of these major and minor PTS and on the recognition of additional conserved properties, the accuracy of predicting peroxisomal proteins can be raised and plant genomes can be screened for novel proteins of peroxisomes more successfully.
Introduction: Varicocele, characterized by the enlargement of scrotal veins, is a common contributor to male infertility, but its genetic underpinnings remain largely unknown. Aim: The goal of this study is to identify potential biomarkers associated with varicocele in order to better understand its molecular mechanisms. Materials and methods: Using the three primary databases, NCBI, DisGeNET, and OpenTarget, we analyzed gene variants and found 79 pertinent genes associated with varicocele. Protein-protein interaction analysis was performed using STRING and visualized with Cytoscape. Molecular Complex Detection (MCODE) and CytoHubba tools helped identify significant protein clusters. Results: The gene ontology analysis shows that there are 79 proteins involved in the inflammatory process, the regulation of gene expression, and cellular components that play a role in oxidative stress and angiogenesis. Our results revealed three key biomarkers: Interleukin-1 beta (IL1B), B-cell lymphoma 2 (BCL2), and matrix metalloproteinase-9 (MMP-9). These proteins are involved in critical processes, such as inflammation, oxidative stress, angiogenesis, and vascular damage, that are central to the pathophysiology of varicocele. Conclusion: The identification of IL1B, BCL2, and MMP-9 offers new insights into varicocele’s molecular mechanisms and suggests potential targets for diagnostic and therapeutic strategies, advancing personalized treatment approaches for fertility restoration.
The NPHS2 gene is expressed in podocytes and encodes the integral membrane protein called podocin, which is believed to play an important role in the renal function of glomerular filtration. Mutations in this gene can cause serious renal function disorders. In this study, we used data-mining techniques and bioinformatic tools to search for the mouse ortholog of the NPHS2-related gene. It might be valuable for future studies of renal diseases. We employed repeated cycles of searching, comparison, and assembling to extend the assembled EST sequences. The discovered gene sequence mslp2, an ortholog of the human SLP2 gene, was found to have a total length of 1253 bp with the amino acid coding region located in 32-1093 nt. It was further verified using the RT-PCR and RACE techniques to ensure its biological accuracy and then registered with the GenBank. When ClustalW was used for comparing the mslp2 and human SLP2 genes for similarities, the similarities were as high as 88% for nucleotide and 92% for amino acid sequences. In conclusion, we propose a method for rapid identification of the mouse ortholog gene from the human genome.
We present a set of geometric docking algorithms for rigid, flexible, and cyclic symmetry docking. The algorithms are highly efficient and have demonstrated very good performance in CAPRI Rounds 3-5. The flexible docking algorithm, FlexDock, is unique in its ability to handle any number of hinges in the flexible molecule, without degradation in run-time performance, as compared to rigid docking. The algorithm for reconstruction of cyclically symmetric complexes successfully assembles multimolecular complexes satisfying C(n) symmetry for any n in a matter of minutes on a desktop PC. Most of the algorithms presented here are available at the Tel Aviv University Structural Bioinformatics Web server (http://bioinfo3d.cs.tau.ac.il/).
In the postgenomic age of drug discovery, targets can no longer be viewed as singular objects having no relationship to one another. All targets are now visible and the systematic exploration of selected target families appears to be a promising way to speed up and further industrialize target-based drug discovery. Chemogenomics refers to such systematic exploration of target families and aims to identify all possible ligands of all target families. Because biology works by applying prior knowledge to an unknown entity, chemogenomics approaches are expected to be especially effective within the previously well-explored target families, for which, in addition to the protein sequence and structure information, considerable knowledge of pharmacologically active structural classes and structure-activity relationships exists. For the new target families, chemical knowledge will have to be generated and beyond biological target validation, the emphasis is on chemistry to provide the molecules with which their novel biology and pharmacology can be studied. Using examples from the previously most successfully explored target families, the GPCR family in particular, we summarize herein our current chemogenomics knowledge-based strategies for drug discovery, which are founded on the high integration of chem and bioinformatics, thereby providing a molecular informatics frame for the exploration of the new target families.