Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “bioinformatic database”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,513 records · Page 84Linked to original sources
PubMed2005

The value of short amino acid sequence matches for prediction of protein allergenicity.

Typically, genetically engineered crops contain traits encoded by one or a few newly expressed proteins. The allergenicity assessment of newly expressed proteins is an important component in the safety evaluation of genetically engineered plants. One aspect of this assessment involves sequence searches that compare the amino acid sequence of the protein to all known allergens. Analyses are performed to determine the potential for immunologically based cross-reactivity where IgE directed against a known allergen could bind to the protein and elicit a clinical reaction in sensitized individuals. Bioinformatic searches are designed to detect global sequence similarity and short contiguous amino acid sequence identity. It has been suggested that potential allergen cross-reactivity may be predicted by identifying matches as short as six to eight contiguous amino acids between the protein of interest and a known allergen. A series of analyses were performed, and match probabilities were calculated for different size peptides to determine if there was a scientifically justified search window size that identified allergen sequence characteristics. Four probability modeling methods were tested: (1) a mock protein and a mock allergen database, (2) a mock protein and genuine allergen database, (3) a genuine allergen and genuine protein database, and (4) a genuine allergen and genuine protein database combined with a correction for repeating peptides. These analyses indicated that searches for short amino acid sequence matches of eight amino acids or fewer to identify proteins as potential cross-reactive allergens is a product of chance and adds little value to allergy assessments for newly expressed proteins.

Allergens↗
PubMed2003

Phylogenomic identification of five new human homologs of the DNA repair enzyme AlkB.

BACKGROUND: Combination of biochemical and bioinformatic analyses led to the discovery of oxidative demethylation - a novel DNA repair mechanism catalyzed by the Escherichia coli AlkB protein and its two human homologs, hABH2 and hABH3. This discovery was based on the prediction made by Aravind and Koonin that AlkB is a member of the 2OG-Fe2+ oxygenase superfamily. RESULTS: In this article, we report identification and sequence analysis of five human members of the (2OG-Fe2+) oxygenase superfamily designated here as hABH4 through hABH8. These experimentally uncharacterized and poorly annotated genes were not associated with the AlkB family in any database, but are predicted here to be phylogenetically and functionally related to the AlkB family (and specifically to the lineage that groups together hABH2 and hABH3) rather than to any other oxygenase family. Our analysis reveals the history of ABH gene duplications in the evolution of vertebrate genomes. CONCLUSIONS: We hypothesize that hABH 4-8 could either be back-up enzymes for hABH1-3 or may code for novel DNA or RNA repair activities. For example, enzymes that can dealkylate N3-methylpurines or N7-methylpurines in DNA have not been described. Our analysis will guide experimental confirmation of these novel human putative DNA repair enzymes.

Amino Acid Sequence↗
PubMed2003

The application of computational methods to explore the diversity and structure of bacterial fatty acid synthase.

Acyl carrier protein (ACP) is a central element in the bacterial, type II dissociated fatty acid synthase (FAS II) system. ACP delivers the fatty acyl intermediates to a variety of enzymes with different biochemical functions and 3-dimensional (3-D) structures. Computational techniques have proved invaluable in guiding the experimental designs that have uncovered the recognition helix on ACP and the common features on its target enzymes responsible for specific protein*protein interactions. Escherichia coli has been the model organism for the study of FAS II, but the availability of complete genomic sequences of a growing number of bacteria coupled with computational bioinformatics has led to new discoveries on the mechanisms that regulate E. coli FAS II and allowed the differences between the E. coli paradigm and major groups of pathogens to be identified and experimentally addressed. Computational methods facilitated the discovery of the E. coli fatty acid synthesis transcriptional regulator, FabR, and led to the identification of novel bacterial FAS II proteins in Gram-positive pathogens, including enoyl-ACP reductases (FabK and FabL) and trans-2-cis-3-decenoyl-ACP isomerase FabM. As more genomic sequences and 3-D coordinates are added to the databases, the power and resolution of the computational approaches will increase to offer deeper insight into the structure, diversity and function of lipid metabolic pathways.

Amino Acid Sequence↗
PubMed2000

Mining genomes and mapping proteomes: identification and characterization of protein subunit vaccines.

Currently, there is an extensive and unprecedented effort to obtain the complete nucleotide sequence of the complex genomes of many micro-organisms. In this post-genomic era, based on the availability of the entire genome sequence of an organism, three new disciplines of molecular biology have emerged: genomics, transcriptional profiling and proteomics. All these technologies have the potential to accelerate the process of identifying protective protein antigens as subunit vaccine targets as well as validating and extending the range of available candidate antigens. The progress of these technologies has led to the origination of the science of bioinformatics for management and critical evaluation of the large amount of information generated. Although genomics, transcriptional profiling and proteomics are each based on different principles, there is considerable synergy between them. Appropriate application of any one, or a combination of two or more of these approaches, coupled with bioinformatics, would allow identification of a short-list of vaccine candidates from the entire list of several hundreds to thousands of proteins encoded by the genome. These candidates would then require usual channelling through the subsequent process involving recombinant expression, purification and testing for immunogenicity and protective efficacy.

Animals↗
PubMed2005

Using ontologies in PROTEUS for modeling proteomics data mining applications.

Bioinformatics applications are often characterized by a combination of (pre) processing of raw data representing biological elements, (e.g. sequence alignment, structure prediction), and an high level data mining analysis. Developing such applications needs knowledge of both data mining and bioinformatics domains, that can be effectively achieved by combining ontology about the application domain and ontology about the approaches and processes to solve the given problem. In this paper we talk about using ontologies to model proteomics in silico experiments. In particular data mining of mass spectrometry proteomics data is considered.

Computational Biology↗
PubMed2003

Evolutionarily conserved ELOVL4 gene expression in the vertebrate retina.

PURPOSE: The gene elongation of very long chain fatty acids-4 (ELOVL4) has been shown to underlie phenotypically heterogeneous forms of autosomal dominant macular degeneration. In this study, the extent of evolutionary conservation and the existence and localization of retinal expression of this gene was investigated across a wide variety of species. METHODS: Southern blot analysis of genomic DNA and bioinformatic analysis using the human ELOVL4 cDNA and protein sequences, respectively, were performed to identify species in which ELOVL4 orthologues and/or homologues are present. Retinal RNA and protein extracts derived from different species were assessed by Northern hybridization and immunoblot techniques to assess evolutionary conservation of gene expression. Immunohistochemical analysis of tissue sections prepared from various mammalian retinas was performed to determine the distribution of ELOVL4 and homologous proteins within specific retinal cell layers. RESULTS: The existence of ELOVL4 sequence orthologues and homologues was confirmed by both Southern blot analysis and in silico searches of protein sequence databases. Phylogenetic analysis places ELOVL4 among a large family of known and putative fatty acid elongase proteins. Northern blot analysis revealed the presence of multiple transcripts corresponding to ELOVL4 homologues expressed in the retina of several different mammalian species. Conserved proteins were also detected among retinal extracts of different mammals and were found to localize predominantly to the photoreceptor cell layer within retinal tissue preparations. CONCLUSIONS: The ELOVL4 gene is highly conserved throughout evolution and is expressed in the photoreceptor cells of the retina in a variety of different species, which suggests that it plays a critical role in retinal cell biology.

Amino Acid Sequence↗
PubMed2005

Practical Approaches to the Development of Biomedical Informatics: the INFOBIOMED Network of Excellence.

Biomedical Informatics (BMI) is the emerging discipline that aims to facilitate integration of Bioinformatics and Medical Informatics for the purpose of accelerating discovery and the generation of novel diagnostic and therapeutic modalities. Building on the success of the European Commission-funded BIOINFOMED Study, an INFOBIOMED Network of Excellence has been constituted with the main objective of setting a structure for a collaborative approach at a European level. Initially formed by fifteen European organizations, the main objective of the INFOBIOMED network is therefore to enable the reinforcement of European BMI at the forefront of these emergent interdisciplinary fields. The paper describes the structure of the network, the integration approaches regarding databases and four pilot applications.

Biomedical Research↗
PubMed2001

Open Source Software meets gene expression.

Use of the Open Source Software (OSS) development model has been crucial in a number of recent technological areas, including operating systems, applications and bioinformatics. The rationale for why OSS is often a better development model than proprietary development and some of the results of this model in the field of Gene Expression are reviewed. The paper concludes with a discussion of why funding agencies should endorse OSS and require funded software projects to be released Open Source.

Access to Information↗
PubMedDate not supplied

Biocatalysis, biodegradation and bioinformatics.

Biocatalysis, biodegradation and bioinformatics are prominent scientific fields in industrial microbiology and biotechnology. This paper describes developments in these fields with a focus on the role of David T Gibson as a researcher and mentor. He has pioneered studies on the mechanisms by which aerobic microorganisms transform aromatic hydrocarbons. In addition, his research has served as a model for further investigations into bacterial atrazine and dichloromethane catabolism described here. Microbial catabolism research requires information on organic chemistry, microorganisms, metabolic pathways, catabolic genes, and enzymes. These information needs are now being met more comprehensively by development of the University of Minnesota Biocatalysis/Biodegradation Database.

Bacteria↗
PubMed2004

Base-By-Base: single nucleotide-level analysis of whole viral genome alignments.

BACKGROUND: With ever increasing numbers of closely related virus genomes being sequenced, it has become desirable to be able to compare two genomes at a level more detailed than gene content because two strains of an organism may share the same set of predicted genes but still differ in their pathogenicity profiles. For example, detailed comparison of multiple isolates of the smallpox virus genome (each approximately 200 kb, with 200 genes) is not feasible without new bioinformatics tools. RESULTS: A software package, Base-By-Base, has been developed that provides visualization tools to enable researchers to 1) rapidly identify and correct alignment errors in large, multiple genome alignments; and 2) generate tabular and graphical output of differences between the genomes at the nucleotide level. Base-By-Base uses detailed annotation information about the aligned genomes and can list each predicted gene with nucleotide differences, display whether variations occur within promoter regions or coding regions and whether these changes result in amino acid substitutions. Base-By-Base can connect to our mySQL database (Virus Orthologous Clusters; VOCs) to retrieve detailed annotation information about the aligned genomes or use information from text files. CONCLUSION: Base-By-Base enables users to quickly and easily compare large viral genomes; it highlights small differences that may be responsible for important phenotypic differences such as virulence. It is available via the Internet using Java Web Start and runs on Macintosh, PC and Linux operating systems with the Java 1.4 virtual machine.

Base Composition↗
PubMed2026

Decoding protein signatures and protein interactions in oral potentially malignant disorders: a systematic review and network analysis.

BACKGROUND: Proteomic profiling offers thorough insights into protein structure and function, as well as it acts as an essential approach for analyzing molecular changes at the tissue level. However, because of the proteome's diversity and dynamic nature, biomarker discovery remains challenging. By combining proteomics with bioinformatics, the level of understanding in relation to molecular interactions and disease processes can be improved. Through an integrative approach, few limitations can be addressed, thereby promoting proteomic profiling for the discovery of new therapeutic targets and novel biomarkers for a variety of disorders. AIM: To identify differentially expressed protein markers and their key molecular pathways associated with Oral Potentially Malignant Disorders. METHODS: Systematic Review was conducted following the PRISMA guidelines and the protocol registered in the International Prospective Register of Systematic Reviews (PROSPERO) with the registration ID number CRD42024557545. A comprehensive literature review was performed using electronic databases, yielding 12,797, studies from which 15 eligible articles were selected. The Newcastle-Ottawa Scale was used to assess the risk of bias. Vote counting was performed to identify proteins reported in more than one study. A bipartite network was constructed using Cytoscape to identify shared and disease-specific protein markers. Lesion-wise protein-protein interaction networks were generated using STRING and analysed in Cytoscape to identify highly interconnected hub proteins, and pathway enrichment analysis for these hubs was performed using Reactome. RESULTS: A total of fifteen studies (Leukoplakia (LK) - n = 1, Proliferative Verrucous Leukoplakia (PVL) - n = 2, Oral Submucous Fibrosis (OSMF) - n = 7, and Oral Lichen Planus (OLP) - n = 5) were included. The Newcastle-Ottawa Scale was used to evaluate methodological quality and the quality of studies included in this systematic review was high for 4 articles and moderate in the remaining 11. The most commonly employed technique was mass spectrometry. A total of 318 candidate proteins (LK - 14, PVL - 82, OSMF - 172, and OLP - 50) were identified across the oral potentially malignant disorders. Key markers identified through vote counting included ERO1A, NUCB1, RHOA, and IL36A for PVL; LUM, KRT1, KRT9, ALB, and VIM for OSMF; and ALB, LYZ, HP, HBB, and AMY1A for OLP. The bipartite network showed that OSMF and OLP shared the highest number of proteins, indicating the strongest overlap among lesions. Network analysis further highlighted distinct hub proteins for each lesion: for LK- AMY1A, AMY1B and APOA1; for PVL- CFL1, RHOA and CDC42; for OSMF- HSP90AA1, ENO1 and SERPINA1; and for OLP- HP, B2M, and ORM1. Lesion-specific pathway enrichment revealed that LK was associated with epithelial differentiation, PVL with oncogenic signaling, OSMF with stress-driven fibrosis, and OLP with immune-mediated inflammation. CONCLUSIONS: Proteomic expression offers insights into disease pathogenesis by identifying important molecular changes across OPMDs. However, the majority of biomarkers are still in the exploratory stage due to the considerable variation in lesion types, sample sources, proteomic techniques, and reporting systems. In order to create reliable and clinically applicable biomarkers, future studies should concentrate on combining multi-omics techniques with large-scale, standardized cohorts.

Humans↗
PubMed2026

Whole-genome sequencing and analysis of the endophytic fungus Alternaria alternata Y-2 from Leymus chinensis.

To explore the genetic basis and functional potential of beneficial symbiosis between the endophytic fungus Alternaria alternata Y-2 and its host Leymus chinensis, we performed Illumina-based draft whole-genome sequencing and systematic bioinformatic analysis. Although this assembly does not reach telomere-to-telomere completeness, it provides high-quality gene-level information for gene prediction, functional annotation, carbohydrate-active enzyme (CAZyme) identification, and secondary metabolite biosynthetic gene cluster analysis. The final genome size of A. alternata Y-2 was 34,383,676 bp with a GC content of 51.0%, containing 12,724 predicted protein-coding genes, 90 tRNAs, and 12 rRNAs. BUSCO assessment showed 98.9% completeness, supporting the high quality of this draft genome. A total of 12,627 genes were successfully annotated in the NCBI NR database, and 17,183 genes were functionally categorized using GO terms. In total, 448 CAZyme genes and 21 secondary metabolite biosynthetic gene clusters were identified, which are potentially involved in lignocellulose degradation, cellular redox homeostasis and biosynthesis of bioactive metabolites. Based on ITS sequence alignment, NR annotation, and phylogenetic analysis of single-copy orthologous genes, the strain was confidently identified as A. alternata. This study firstly reports the draft genome of an endophytic A. alternata strain derived from L. chinensis and provides valuable genetic resources for exploring the endophytic lifestyle, stress tolerance, and bioactive metabolite potential of this fungus.

Alternaria↗
PubMed2005

Multiple retropseudogenes from pluripotent cell-specific gene expression indicates a potential signature for novel gene identification.

Oct4, Nanog, and Stella are transcription factors specifically expressed in embryonic stem (ES) cells and germ lineage cells that impart critical functions in the maintenance of pluripotency. Here, we report the excessive frequency and apparent selectivity of retrotransposition of ES cell-specific genes. Six highly homologous pseudogenes for Oct4, 10 for Nanog, and 16 for Stella were identified by nucleotide BLAST (basic local alignment sequence tool) searches against the respective gene mRNA transcripts. Of 15 non-ES cell-specific transcription factor genes, only one had a single pseudogene hit in our screen, emphasizing the apparent selectivity. We present a hypothesis whereby retrotransposition of ES or germ cell-specific genes may reflect an innate predisposition. This is based on the increased probability of germ-line transmission when retrotransposition occurs at a very early stage of development within cells known to contribute to the germ cell lineage. The parental genes for Nanog, Stella, and another embryonic gene, GDF3 are all located on chromosome 12p13 of the human genome, and on chromosome 6 in mouse. Here, we identified an Oct4 pseudogene at the same respective loci in both human and mouse genomes, suggesting functional relevance and indicative of epigenetic regulation. We tested whether the apparent susceptibility for ES cell-specific gene retrotransposition may be extrapolated to a more unified phenomenon, such that a bioinformatic approach may represent a potentially novel strategy for identification of genes with embryonic cell-specific functionality. A preliminary investigation indeed revealed a single gene, previously demonstrated to be responsible for multiple retropseudogenes via germ cell-specific expression in Xenopus.

Chromosomal Proteins, Non-Histone↗
PubMed2005

What makes a gene name? Named entity recognition in the biomedical literature.

The recognition of biomedical concepts in natural text (named entity recognition, NER) is a key technology for automatic or semi-automatic analysis of textual resources. Precise NER tools are a prerequisite for many applications working on text, such as information retrieval, information extraction or document classification. Over the past years, the problem has achieved considerable attention in the bioinformatics community and experience has shown that NER in the life sciences is a rather difficult problem. Several systems and algorithms have been devised and implemented. In this paper, the problems and resources in NER research are described, the principal algorithms underlying most systems sketched, and the current state-of-the-art in the field surveyed.

Algorithms↗
PubMed2005

Detection and characterization of horizontal transfers in prokaryotes using genomic signature.

Horizontal DNA transfer is an important factor of evolution and participates in biological diversity. Unfortunately, the location and length of horizontal transfers (HTs) are known for very few species. The usage of short oligonucleotides in a sequence (the so-called genomic signature) has been shown to be species-specific even in DNA fragments as short as 1 kb. The genomic signature is therefore proposed as a tool to detect HTs. Since DNA transfers originate from species with a signature different from those of the recipient species, the analysis of local variations of signature along recipient genome may allow for detecting exogenous DNA. The strategy consists in (i) scanning the genome with a sliding window, and calculating the corresponding local signature (ii) evaluating its deviation from the signature of the whole genome and (iii) looking for similar signatures in a database of genomic signatures. A total of 22 prokaryote genomes are analyzed in this way. It has been observed that atypical regions make up approximately 6% of each genome on the average. Most of the claimed HTs as well as new ones are detected. The origin of putative DNA transfers is looked for among approximately 12 000 species. Donor species are proposed and sometimes strongly suggested, considering similarity of signatures. Among the species studied, Bacillus subtilis, Haemophilus Influenzae and Escherichia coli are investigated by many authors and give the opportunity to perform a thorough comparison of most of the bioinformatics methods used to detect HTs.

Bacillus subtilis↗
PubMed2006

Djinn Lite: a tool for customised gene transcript modelling, annotation-data enrichment and exploration.

BACKGROUND: There is an ever increasing rate of data made available on genetic variation, transcriptomes and proteomes. Similarly, a growing variety of bioinformatic programs are becoming available from many diverse sources, designed to identify a myriad of sequence patterns considered to have potential biological importance within inter-genic regions, genes, transcripts, and proteins. However, biologists require easy to use, uncomplicated tools to integrate this information, visualise and print gene annotations. Integrating this information usually requires considerable informatics skills, and comprehensive knowledge of the data format to make full use of this information. Tools are needed to explore gene model variants by allowing users the ability to create alternative transcript models using novel combinations of exons not necessarily represented in current database deposits of mRNA/cDNA sequences. RESULTS: Djinn Lite is designed to be an intuitive program for storing and visually exploring of custom annotations relating to a eukaryotic gene sequence and its modelled gene products. In particular, it is helpful in developing hypothesis regarding alternate splicing of transcripts by allowing the construction of model transcripts and inspection of their resulting translations. It facilitates the ability to view a gene and its gene products in one synchronised graphical view, allowing one to drill down into sequence related data. Colour highlighting of selected sequences and added annotations further supports exploration, visualisation of sequence regions and motifs known or predicted to be biologically significant. CONCLUSION: Gene annotating remains an ongoing and challenging task that will continue as gene structures, gene transcription repertoires, disease loci, protein products and their interactions become more precisely defined. Djinn Lite offers an accessible interface to help accumulate, enrich, and individualize sequence annotations relating to a gene, its transcripts and translations. The mechanism of transcript definition and creation, and subsequent navigation and exploration of features, are very intuitive and demand only a short learning curve. Ultimately, Djinn Lite can form the basis for providing valuable clues to plan new experiments, providing storage of sequences and annotations for dedication to customised projects. The application is appropriate for Windows 98-ME-2000-XP-2003 operating systems.

Alternative Splicing↗
PubMed2004

PoPS: a computational tool for modeling and predicting protease specificity.

Proteases play a fundamental role in the control of intra- and extracellular processes by binding and cleaving specific amino acid sequences. Identifying these targets is extremely challenging. Current computational attempts to predict cleavage sites are limited, representing these amino acid sequences as patterns or frequency matrices. Here we present PoPS, a publicly accessible bioinformatics tool (http://pops.csse.monash.edu.au/) which provides a novel method for building computational models of protease specificity that, while still being based on these amino acid sequences, can be built from any experimental data or expert knowledge available to the user. PoPS specificity models can be used to predict and rank likely cleavages within a single substrate, and within entire proteomes. Other factors, such as the secondary or tertiary structure of the substrate, can be used to screen unlikely sites. Furthermore, the tool also provides facilities to infer, compare and test models, and to store them in a publicly accessible database.

Amino Acid Sequence↗
PubMed2005

PoPS: a computational tool for modeling and predicting protease specificity.

Proteases play a fundamental role in the control of intra- and extra-cellular processes by binding and cleaving specific amino acid sequences. Identifying these targets is extremely challenging. Current computational attempts to predict cleavage sites are limited, representing these amino acid sequences as patterns or frequency matrices. Here we present PoPS, a publicly accessible bioinformatics tool (http://pops.csse.monash.edu.au/) that provides a novel method for building computational models of protease specificity, which while still being based on these amino acid sequences, can be built from any experimental data or expert knowledge available to the user. PoPS specificity models can be used to predict and rank likely cleavages within a single substrate, and within entire proteomes. Other factors, such as the secondary or tertiary structure of the substrate, can be used to screen unlikely sites. Furthermore, the tool also provides facilities to infer, compare and test models, and to store them in a publicly accessible database.

Algorithms↗