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At least 1,297 records · Page 72Linked to original sources
PubMed2005

MEPD: a resource for medaka gene expression patterns.

The Medaka Expression Pattern Database (MEPD) is a database for gene expression patterns determined by in situ hybridization in the small freshwater fish medaka (Oryzias latipes). Data have been collected from various research groups and MEPD is developing into a central expression pattern depository within the medaka community. Gene expression patterns are described by images and terms of a detailed medaka anatomy ontology of over 4000 terms, which we have developed for this purpose and submitted to Open Biological Ontologies. Sequences have been annotated via BLAST match results and using Gene Ontology terms. These new features will facilitate data analyses using bioinformatics approaches and allow cross-species comparisons of gene expression patterns. Presently, MEPD has 19,757 entries, for 1024 of them the expression pattern has been determined.

Animals↗
PubMed2006

PEDANT genome database: 10 years online.

The PEDANT genome database provides exhaustive annotation of 468 genomes by a broad set of bioinformatics algorithms. We describe recent developments of the PEDANT Web server. The all-new Graphical User Interface (GUI) implemented in Javatrade mark allows for more efficient navigation of the genome data, extended search capabilities, user customization and export facilities. The DNA and Protein viewers have been made highly dynamic and customizable. We also provide Web Services to access the entire body of PEDANT data programmatically. Finally, we report on the application of association rule mining for automatic detection of potential annotation errors. PEDANT is freely accessible to academic users at http://pedant.gsf.de.

Computer Graphics↗
PubMed2005

A sentence sliding window approach to extract protein annotations from biomedical articles.

BACKGROUND: Within the emerging field of text mining and statistical natural language processing (NLP) applied to biomedical articles, a broad variety of techniques have been developed during the past years. Nevertheless, there is still a great ned of comparative assessment of the performance of the proposed methods and the development of common evaluation criteria. This issue was addressed by the Critical Assessment of Text Mining Methods in Molecular Biology (BioCreative) contest. The aim of this contest was to assess the performance of text mining systems applied to biomedical texts including tools which recognize named entities such as genes and proteins, and tools which automatically extract protein annotations. RESULTS: The "sentence sliding window" approach proposed here was found to efficiently extract text fragments from full text articles containing annotations on proteins, providing the highest number of correctly predicted annotations. Moreover, the number of correct extractions of individual entities (i.e. proteins and GO terms) involved in the relationships used for the annotations was significantly higher than the correct extractions of the complete annotations (protein-function relations). CONCLUSION: We explored the use of averaging sentence sliding windows for information extraction, especially in a context where conventional training data is unavailable. The combination of our approach with more refined statistical estimators and machine learning techniques might be a way to improve annotation extraction for future biomedical text mining applications.

Biomedical Research↗
PubMed2006

Electrostatic interactions of peptides flanking the tyrosine kinase domain in the epidermal growth factor receptor provides a model for intracellular dimerization and autophosphorylation.

The mechanism by which ligand-activated EGFR induces autophosphorylation via dimerization is not fully understood. Structural studies have revealed an extracellular loop mediated receptor dimerization. We have previously presented experimental data showing the involvement of a positive 13 amino acid peptide (R645-R657; P13+) from the intracellular juxtamembrane domain (JM) of EGFR important for intracellular dimerization and autophosphorylation. A model was presented that suggest that P13+ interacts with a negative peptide (D979-E991; P13-) positioned distal to the tyrosine kinase domain in the opposite EGFR monomer. The present work shows additional data strengthening this model. In fact, by analyzing protein sequences of 21 annotated ErbB proteins from 9 vertebrate genomes, we reveal the high conservation of peptides P13+ and P13- with regard to their sequence as well as their position relative to the tyrosine kinase (TK) domain. Moreover in silico structure modeling of these ErbB intracellular domains supports a general electrostatic P13+/P13- interaction, implying that the C-terminal of one receptor monomer is facing the TK domain of the other monomer in the receptor dimer and vice versa. This model provides new insights into the molecular mechanism of ErbB receptor activation and suggests a new strategy to pharmacologically interfering with ErbB receptor activity.

Animals↗
PubMed1985

Autoimmune haemolytic anaemia: recent advances in pathogenesis, diagnosis and treatment.

The diagnosis and management of patients with autoimmune haemolytic anaemia demands knowledge of various aspects of both clinical and laboratory medicine. There is an apparent gap of communication between the serologist and the clinical physician due to the high specialization of both. The purpose of this annotation is to close some of these gaps by relating the serological data to the diagnosis, severity of disease, treatment, and prognosis.

Adrenal Cortex Hormones↗
PubMed2006

A genome-wide map of conserved microRNA targets in C. elegans.

BACKGROUND: Metazoan miRNAs regulate protein-coding genes by binding the 3' UTR of cognate mRNAs. Identifying targets for the 115 known C. elegans miRNAs is essential for understanding their function. RESULTS: By using a new version of PicTar and sequence alignments of three nematodes, we predict that miRNAs regulate at least 10% of C. elegans genes through conserved interactions. We have developed a new experimental pipeline to assay 3' UTR-mediated posttranscriptional gene regulation via an endogenous reporter expression system amenable to high-throughput cloning, demonstrating the utility of this system using one of the most intensely studied miRNAs, let-7. Our expression analyses uncover several new potential let-7 targets and suggest a new let-7 activity in head muscle and neurons. To explore genome-wide trends in miRNA function, we analyzed functional categories of predicted target genes, finding that one-third of C. elegans miRNAs target gene sets are enriched for specific functional annotations. We have also integrated miRNA target predictions with other functional genomic data from C. elegans. CONCLUSIONS: At least 10% of C. elegans genes are predicted miRNA targets, and a number of nematode miRNAs seem to regulate biological processes by targeting functionally related genes. We have also developed and successfully utilized an in vivo system for testing miRNA target predictions in likely endogenous expression domains. The thousands of genome-wide miRNA target predictions for nematodes, humans, and flies are available from the PicTar website and are linked to an accessible graphical network-browsing tool allowing exploration of miRNA target predictions in the context of various functional genomic data resources.

Animals↗
PubMed2004

Genome-wide high-throughput screens in functional genomics.

The availability of complete genome sequences from many organisms has yielded the ability to perform high-throughput, genome-wide screens of gene function. Within the past year, rapid advances have been made towards this goal in many major model systems, including yeast, worms, flies, and mammals. Yeast genome-wide screens have taken advantage of libraries of deletion strains, but RNA-interference has been used in other organisms to knockdown gene function. Examples of recent large-scale functional genetic screens include drug-target identification in yeast, regulators of fat accumulation in worms, growth and viability in flies, and proteasome-mediated degradation in mammalian cells. Within the next five years, such screens are likely to lead to annotation of function of most genes across multiple organisms. Integration of such data with other genomic approaches will extend our understanding of cellular networks.

Animals↗
PubMed2005

Assisting medical annotation in Swiss-Prot using statistical classifiers.

Bio-medical knowledge bases are valuable resources for the research community. Original scientific publications are the main source used to annotate them. Medical annotation in Swiss-Prot is specifically targeted at finding and extracting data about human genetic diseases and polymorphisms. Curators have to scan through hundreds of publications to select the relevant ones. This workload can be greatly reduced by using bio-text mining techniques. Using a combination of natural language processing (NLP) techniques and statistical classifiers, we achieve recall points of up to 84% on the potentially interesting documents and a precision of more than 96% in detecting irrelevant documents. Careful analysis of the document pre-processing chain allows us to measure the impact of some steps on the overall result, as well as test different classifier configurations. The best combination was used to create a prototype of a search and classification tool that is currently tested by the database curators.

Databases, Protein↗
PubMed2004

Genome-wide expression profiling of a cardiac pressure overload model identifies major metabolic and signaling pathway responses.

Cardiac hypertrophy is a predictor of cardiovascular morbidity and mortality independent of other risk factors. Pressure overload induces the development of left ventricular hypertrophy (LVH) and left atrial enlargement (LAE) in the mammalian heart. To systematically investigate the transcriptional changes, which mediate these processes, we have performed a genome-wide transcriptional profiling of each of the four heart chambers from mice subjected to transverse aortic constriction (TAC). A major new finding of this analysis is that during enlargement the left atrium undergoes radical changes in gene transcription that may play a significant role in pathophysiology. Structural changes in the LA and LV are correlated with significant changes in the transcriptional profile of these chambers, with thousands of differentially expressed known and novel factors. Statistical analysis of the results identified Gene Ontology biological process groups with significant group-wide changes, including angiogenesis, energy pathways, fatty acid oxidation, oxidative phosphorylation, cytoskeletal and matrix reorganization, and G-protein coupled receptor (GPCR) signaling. To facilitate future research, a searchable annotated Internet database has been constructed that allows access to the expression data presented here. Further study of these genes and processes will lead to better understanding of pathways involved in the pathophysiology of the cardiac response to pressure overload.

Animals↗
PubMed2003

Expression profiling of human idiopathic dilated cardiomyopathy.

OBJECTIVE: To investigate the global changes accompanying human dilated cardiomyopathy (DCM) we performed a large-scale expression screen using myocardial biopsies from a group of DCM patients with moderate heart failure. By hierarchical clustering and functional annotation of the deregulated genes we examined extensive changes in the cellular and molecular processes associated to DCM. METHODS: The expression profiles were obtained using a whole genome covering library (UniGene RZPD1) comprising 30336 cDNA clones and amplified RNA from myocardiac biopsies from 10 DCM patients in comparison to tissue samples from four non-failing, healthy donors. RESULTS: By setting stringent selection criteria 364 differentially expressed, sequence-verified non-redundant transcripts were identified with a false discovery rate of <0.001. Numerous genes and ESTs were identified representing previously recognised, as well as novel DCM-associated transcripts. Many of them were found to be upregulated and involved in cardiomyocyte energetics, muscle contraction or signalling. Two hundred and twenty-two deregulated transcripts were functionally annotated and hierarchically clustered providing an insight into the pathophysiology of DCM. Data was validated using the MLP-deficient mouse, in which several differentially expressed transcripts identified in the human DCM biopsies could be confirmed. CONCLUSIONS: We report the first genome-wide expression profile analysis using cardiac biopsies from DCM patients at various stages of the disease. Although there is a diversity of links between the cytoskeleton and the initiation of DCM, we speculate that genes implicated in intracellular signalling and in muscle contraction are associated with early stages of the disease. Altogether this study represents the most comprehensive and inclusive molecular portrait of human cardiomyopathy to date.

Adult↗
PubMedDate not supplied

Phylomat: an automated protein motif analysis tool for phylogenomics.

Recent progress in genomics, proteomics, and bioinformatics enables unprecedented opportunities to examine the evolutionary history of molecular, cellular, and developmental pathways through phylogenomics. Accordingly, we have developed a motif analysis tool for phylogenomics (Phylomat, http://alg.ncsa.uiuc.edu/pmat) that scans predicted proteome sets for proteins containing highly conserved amino acid motifs or domains for in silico analysis of the evolutionary history of these motifs/domains. Phylomat enables the user to download results as full protein or extracted motif/domain sequences from each protein. Tables containing the percent distribution of a motif/domain in organisms normalized to proteome size are displayed. Phylomat can also align the set of full protein or extracted motif/domain sequences and predict a neighbor-joining tree from relative sequence similarity. Together, Phylomat serves as a user-friendly data-mining tool for the phylogenomic analysis of conserved sequence motifs/domains in annotated proteomes from the three domains of life.

Algorithms↗
PubMed2004

The human plasma proteome: a nonredundant list developed by combination of four separate sources.

We have merged four different views of the human plasma proteome, based on different methodologies, into a single nonredundant list of 1175 distinct gene products. The methodologies used were 1) literature search for proteins reported to occur in plasma or serum; 2) multidimensional chromatography of proteins followed by two-dimensional electrophoresis and mass spectroscopy (MS) identification of resolved proteins; 3) tryptic digestion and multidimensional chromatography of peptides followed by MS identification; and 4) tryptic digestion and multidimensional chromatography of peptides from low-molecular-mass plasma components followed by MS identification. Of 1,175 nonredundant gene products, 195 were included in more than one of the four input datasets. Only 46 appeared in all four. Predictions of signal sequence and transmembrane domain occurrence, as well as Genome Ontology annotation assignments, allowed characterization of the nonredundant list and comparison of the data sources. The "nonproteomic" literature (468 input proteins) is strongly biased toward signal sequence-containing extracellular proteins, while the three proteomics methods showed a much higher representation of cellular proteins, including nuclear, cytoplasmic, and kinesin complex proteins. Cytokines and protein hormones were almost completely absent from the proteomics data (presumably due to low abundance), while categories like DNA-binding proteins were almost entirely absent from the literature data (perhaps unexpected and therefore not sought). Most major categories of proteins in the human proteome are represented in plasma, with the distribution at successively deeper layers shifting from mostly extracellular to a distribution more like the whole (primarily cellular) proteome. The resulting nonredundant list confirms the presence of a number of interesting candidate marker proteins in plasma and serum.

Biomarkers, Tumor↗
PubMed2004

TMDET: web server for detecting transmembrane regions of proteins by using their 3D coordinates.

The structure of integral membrane proteins is determined in the absence of the lipid bilayer; consequently the membrane localization of the protein is usually not specified in the corresponding PDB file. Recently, we have developed a new method called TMDET which determines the most possible localization of the membrane relative to the protein structure, and gives the annotation of the membrane embedded parts of the sequence. The entire Protein Data Bank has been scanned by the new TMDET algorithm resulting in the database of structurally determined transmembrane proteins (PDB_TM). Here we present the web interface of the TMDET algorithm to allow scientists to determine the membrane localization of structural data prior to deposition or to analyze model structures.

Algorithms↗
PubMed2004

SpliceMachine: predicting splice sites from high-dimensional local context representations.

MOTIVATION: In this age of complete genome sequencing, finding the location and structure of genes is crucial for further molecular research. The accurate prediction of intron boundaries largely facilitates the correct prediction of gene structure in nuclear genomes. Many tools for localizing these boundaries on DNA sequences have been developed and are available to researchers through the internet. Nevertheless, these tools still make many false positive predictions. RESULTS: This manuscript presents a novel publicly available splice site prediction tool named SpliceMachine that (i) shows state-of-the-art prediction performance on Arabidopsis thaliana and human sequences, (ii) performs a computationally fast annotation and (iii) can be trained by the user on its own data. AVAILABILITY: Results, figures and software are available at http://www.bioinformatics.psb.ugent.be/supplementary_data/ CONTACT: sven.degroeve@psb.ugent.be; yves.vandepeer@psb.ugent.be.

Algorithms↗
PubMed2005

SynBrowse: a synteny browser for comparative sequence analysis.

MOTIVATION: The recent efforts of various sequence projects to sequence deeply into various phylogenies provide great resources for comparative sequence analysis. A generic and portable tool is essential for scientists to visualize and analyze sequence comparisons. RESULTS: We have developed SynBrowse, a synteny browser for visualizing and analyzing genome alignments both within and between species. It is intended to help scientists study macrosynteny, microsynteny and homologous genes between sequences. It can also aid with the identification of uncharacterized genes, putative regulatory elements and novel structural features of a species. SynBrowse is a GBrowse (the Generic Genome Browser) family software tool that runs on top of the open source BioPerl modules. It consists of two components: a web-based front end and a set of relational database back ends. Each database stores pre-computed alignments from a focus sequence to reference sequences in addition to the genome annotations of the focus sequence. The user interface lets end users select a key comparative alignment type and search for syntenic blocks between two sequences and zoom in to view the relationships among the corresponding genome annotations in detail. SynBrowse is portable with simple installation, flexible configuration, convenient data input and easy integration with other components of a model organism system. AVAILABILITY: The software is available at http://www.gmod.org CONTACT: vbrendel@iastate.edu

Algorithms↗
PubMed2006

Functional bioinformatics for Arabidopsis thaliana.

MOTIVATION: The genome of Arabidopsis thaliana, which has the best understood plant genome, still has approximately one-third of its genes with no functional annotation at all from either MIPS or TAIR. We have applied our Data Mining Prediction (DMP) method to the problem of predicting the functional classes of these protein sequences. This method is based on using a hybrid machine-learning/data-mining method to identify patterns in the bioinformatic data about sequences that are predictive of function. We use data about sequence, predicted secondary structure, predicted structural domain, InterPro patterns, sequence similarity profile and expressions data. RESULTS: We predicted the functional class of a high percentage of the Arabidopsis genes with currently unknown function. These predictions are interpretable and have good test accuracies. We describe in detail seven of the rules produced.

Algorithms↗
PubMed2006

A whole genome long-range haplotype (WGLRH) test for detecting imprints of positive selection in human populations.

MOTIVATION: The identification of signatures of positive selection can provide important insights into recent evolutionary history in human populations. Current methods mostly rely on allele frequency determination or focus on one or a small number of candidate chromosomal regions per study. With the availability of large-scale genotype data, efficient approaches for an unbiased whole genome scan are becoming necessary. METHODS: We have developed a new method, the whole genome long-range haplotype test (WGLRH), which uses genome-wide distributions to test for recent positive selection. Adapted from the long-range haplotype (LRH) test, the WGLRH test uses patterns of linkage disequilibrium (LD) to identify regions with extremely low historic recombination. Common haplotypes with significantly longer than expected ranges of LD given their frequencies are identified as putative signatures of recent positive selection. In addition, we have also determined the ancestral alleles of SNPs by genotyping chimpanzee and gorilla DNA, and have identified SNPs where the non-ancestral alleles have risen to extremely high frequencies in human populations, termed 'flipped SNPs'. Combining the haplotype test and the flipped SNPs determination, the WGLRH test serves as an unbiased genome-wide screen for regions under putative selection, and is potentially applicable to the study of other human populations. RESULTS: Using WGLRH and high-density oligonucleotide arrays interrogating 116 204 SNPs, we rapidly identified putative regions of positive selection in three populations (Asian, Caucasian, African-American), and extended these observations to a fourth population, Yoruba, with data obtained from the International HapMap consortium. We mapped significant regions to annotated genes. While some regions overlap with genes previously suggested to be under positive selection, many of the genes have not been previously implicated in natural selection and offer intriguing possibilities for further study. AVAILABILITY: the programs for the WGLRH algorithm are freely available and can be downloaded at http://www.affymetrix.com/support/supplement/WGLRH_program.zip.

Algorithms↗
PubMed1993

A quality control algorithm for DNA sequencing projects.

Heterologous DNA sequences from rearrangements with the genomes of host cells, genomic fragments from hybrid cells, or impure tissue sources can threaten the purity of libraries that are derived from RNA or DNA. Hybridization methods can only detect contaminants from known or suspected heterologous sources, and whole library screening is technically very difficult. Detection of contaminating heterologous clones by sequence alignment is only possible when related sequences are present in a known database. We have developed a statistical test to identify heterologous sequences that is based on the differences in hexamer composition of DNA from different organisms. This test does not require that sequences similar to potential heterologous contaminants are present in the database, and can in principle detect contamination by previously unknown organisms. We have applied this test to the major public expressed sequence tag (EST) data sets to evaluate its utility as a quality control measure and a peer evaluation tool. There is detectable heterogeneity in most human and C.elegans EST data sets but it is not apparently associated with cross-species contamination. However, there is direct evidence for both yeast and bacterial sequence contamination in some public database sequences annotated as human. Results obtained with the hexamer test have been confirmed with similarity searches using sequences from the relevant data sets.

Algorithms↗