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At least 1,063 records · Page 59Linked to original sources
PubMed2006

Anopheles gambiae genome reannotation through synthesis of ab initio and comparative gene prediction algorithms.

BACKGROUND: Complete genome annotation is a necessary tool as Anopheles gambiae researchers probe the biology of this potent malaria vector. RESULTS: We reannotate the A. gambiae genome by synthesizing comparative and ab initio sets of predicted coding sequences (CDSs) into a single set using an exon-gene-union algorithm followed by an open-reading-frame-selection algorithm. The reannotation predicts 20,970 CDSs supported by at least two lines of evidence, and it lowers the proportion of CDSs lacking start and/or stop codons to only approximately 4%. The reannotated CDS set includes a set of 4,681 novel CDSs not represented in the Ensembl annotation but with EST support, and another set of 4,031 Ensembl-supported genes that undergo major structural and, therefore, probably functional changes in the reannotated set. The quality and accuracy of the reannotation was assessed by comparison with end sequences from 20,249 full-length cDNA clones, and evaluation of mass spectrometry peptide hit rates from an A. gambiae shotgun proteomic dataset confirms that the reannotated CDSs offer a high quality protein database for proteomics. We provide a functional proteomics annotation, ReAnoXcel, obtained by analysis of the new CDSs through the AnoXcel pipeline, which allows functional comparisons of the CDS sets within the same bioinformatic platform. CDS data are available for download. CONCLUSION: Comprehensive A. gambiae genome reannotation is achieved through a combination of comparative and ab initio gene prediction algorithms.

Algorithms↗
PubMed2003

Severe acute respiratory syndrome-associated coronavirus genotype and its characterization.

OBJECTIVE: To study the severe acute respiratory syndrome (SARS)-associated coronavirus genotype and its characteristics. METHODS: A SARS-associated coronavirus isolate named ZJ01 was obtained from throat swab samples taken from a patient in Hangzhou, Zhejing province. The complete genome sequence of ZJ01 consisted of 29,715 bp (GenBank accession: AY297028, version: gi: 30910859). Seventeen SARS-associated coronavirus genome sequences in GenBank were compared to analyze the common sequence variations and the probability of co-occurrence of multiple polymorphisms or mutations. Phylogenetic analysis of those sequences was done. RESULTS: By bioinformatics processing and analysis, the 5 loci nucleotides at ZJ01 genome were found being T, T, G, T and T, respectively. Compared with other SARS-associated coronavirus genomes in the GenBank database, an A/G mutation was detected besides the other 4 mutation loci (C:G:C:C/T:T:T:T) involved in this genetic signature. Therefore a new definition was put forward according to the 5 mutation loci. SARS-associated coronavirus strains would be grouped into two genotypes (C:G:A:C:C/T:T:G:T:T), and abbreviated as SARS coronavirus C genotype and T genotype. On the basis of this new definition, the ZJ01 isolate belongs to SARS-associated coronavirus T genotype, first discovered and reported in mainland China. Phylogenetic analysis of the spike protein gene fragments of these SARS-associated coronavirus strains showed that the GZ01 isolate was phylogenetically distinct from other isolates, and compared with groups F1 and F2 of the T genotype, the isolates of BJ01 and CUHK-W1 were more closely related to the GZ01 isolate. It was interesting to find that two (A/G and C/T) of the five mutation loci occurred in the spike protein gene, which caused changes of Asp to Gly and Thr to Ile in the protein, respectively. CONCLUSION: Attention should be paid to whether these genotype and mutation patterns are related to the virus's biological activities,epidemic characteristics and host clinical symptoms.

Genotype↗
PubMed2005

[Phylogenetic analysis for H3A1 strain of all human influenza A virus].

OBJECTIVE: Influenza A virus remains an important pathogen which threatens humans. With the help of latest developed bioinformatics tools, all available human Influenza A virus H3A1 strains were explored to deeply understanding its evolution and variation rules. METHODS: All data of H3A1 sequence in NCBI Genbank and Influenza sequence database were downloaded and aligned in ClustalX with two step cluster method used to split the data and Bayesian phylogenetic tree analysis method applied to precisely construct phylogenetic tree for each clusters. RESULTS: Tree topology indicated that H3 strains evolved along a single evolution trunk and tree pattern and model parameter showed obvious variety tendency with time period. However, no geographic distribution features were found for key variation strains and big branch in trees. CONCLUSION: The evolution of human H3 strains were mainly driven by the interaction of human immune barriers and antigenic drift of virus. Since the influenza subtype had already been spread in human population, south China should not be considered as the originated areas of new strains, hence it should be treated as equally as other places in the world.

Antigens↗
PubMed2004

Science review: searching for gene candidates in acute lung injury.

Acute lung injury (ALI) is a complex and devastating illness, often occurring within the setting of sepsis, and carries an annual mortality rate of 30-50%. Although the genetic basis of ALI has not been fully established, an increasing body of evidence suggests that genetic predisposition contributes to disease susceptibility and severity. Significant difficulty exists, however, in defining the exact nature of these genetic factors, including large phenotypic variance, incomplete penetrance, complex gene-environment interactions, and strong potential for locus heterogeneity. We utilized the candidate gene approach and an ortholog gene database to provide relevant gene ontologies and insights into the genetic basis of ALI. We employed a Medline search of selected basic and clinical studies in the English literature and studies sponsored by the HopGene National Institutes of Health sponsored Program in Genomic Applications. Extensive gene expression profiling studies in animal models of ALI (rat, murine, canine), as well as in humans, were performed to identify potential candidate genes http://www.hopkins-genomics.org/. We identified a number of candidate genes for ALI, with blood coagulation and inflammation gene ontologies being the most highly represented. The candidate gene approach coupled with extensive gene profiling and novel bioinformatics approaches is a valuable way to identify genes that are involved in ALI.

Animals↗
PubMed2000

PIR: a new resource for bioinformatics.

UNLABELLED: The Protein Information Resource (PIR) has greatly expanded its Web site and developed a set of interactive search and analysis tools to facilitate the analysis, annotation, and functional identification of proteins. New search engines have been implemented to combine sequence similarity search results with database annotation information. The new PIR search systems have proved very useful in providing enriched functional annotation of protein sequences, determining protein superfamily-domain relationships, and detecting annotation errors in genomic database archives. AVAILABILITY: http://pir.georgetown.edu/. CONTACT: mcgarvey@nbrf.georgetown.edu

Animals↗
PubMed2025

FOSB is a key factor in the genetic link between inflammatory bowel disease and acute myocardial infarction: multiple bioinformatics analyses and validation.

BACKGROUND: Inflammatory Bowel Disease (IBD), which includes Crohn's disease and ulcerative colitis, is associated with an increased risk of Acute Myocardial Infarction (AMI). The genetic mechanisms underlying this link are not well understood. METHODS: We downloaded IBD and AMI-related microarray datasets from the NCBI Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified and analyzed using enrichment analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Machine learning techniques, including LASSO, random forest, and Boruta, were employed to screen for hub genes. These genes were validated through qRT-PCR and Western blotting. Single-cell sequencing was used to confirm findings. Additionally, potential therapeutic targets were identified using the Connectivity Map (CMap) database. RESULTS: Five key hub genes-THBD, FOSB, ADGPR3, IL1R2, and PLAUR-were identified as significantly involved in both IBD and AMI pathogenesis. A diagnostic model for AMI constructed using these hub genes demonstrated high predictive accuracy. Single-cell sequencing analysis and several potential drugs targeting these hub genes were identified, offering new therapeutic avenues. CONCLUSION: This study highlights the crucial role of FOSB and other hub genes in the comorbidity of IBD and AMI. The findings provide novel insights for early diagnosis and potential therapeutic strategies, emphasizing the importance of further investigation into these genetic links.

Humans↗
PubMed1997

The chemokine information source: identification and characterization of novel chemokines using the WorldWideWeb and expressed sequence tag databases.

The chemokine superfamily is a large group of more than 30 small proteins. Many of these were originally identified because of their role in the selective recruitment and activation of leukocytes during inflammation. More recently, some of the chemokine receptors and ligands have been implicated in the mechanism of viral infection for primate lentiviruses such as HIV-1. From the original identification of interleukin-8 (IL-8; the most studied member of the superfamily), the number of new family members has mushroomed over the last few years. Two events have dramatically altered the speed at which sequence information concerning novel chemokines has become available to the scientific community. First, many groups have been obtaining large amounts of sequence information from cDNA libraries by sequencing the clones at random, generating expressed sequence tags (ESTs). Although these ESTs are relatively short, typically less than 500 bases, this amount of sequence is usually sufficient to obtain the entire open reading frame for chemokines. Second, there has been a rapid growth in the use of the WorldWideWeb by bioinformatics groups. The Web was originally set up by the European Centre for Particle Physics (CERN) in Geneva as a method of transferring data between collaborating groups throughout the world. It has enabled biologists throughout the world to have almost instantaneous access both to the databases containing the EST sequences and to the automated tools that are required for searching such databases. With such methods we have been able to rapidly identify more than 10 new human chemokines from public domain databases. In addition to the known categories of chemokines, which are named C, CC, and CXC based on the spacings of N-terminal cysteine residues, we have been able to identify the first member of a novel chemokine subfamily, with a novel CXXXC cysteine spacing. Furthermore, we can subdivide the CC chemokines into monocyte chemotactic protein and macrophage inflammatory protein families based on their sequence identity levels, but also their clustering on the human genome, as identified on other Web sites. The rapid availability of all this data has reduced the amount of time spent on conventional gene identification, enabling us to move quickly on to trying to understand the biology and physiological relevance of these molecules. The novel chemokine sequences obtained and alignments with existing members of the superfamily are now contained within a Chemokine Information Source on an open access server, allowing further searching of chemokine sequences and increasing the availability of such data to the scientific community.

Amino Acid Sequence↗
PubMed1999

Ontology for immunogenetics: the IMGT-ONTOLOGY.

MOTIVATION: IMGT, the international ImMunoGeneTics database (http:@imgt.cines.fr:8104), created by M.-P. Lefranc, is an integrated database specializing in antigen receptors (immunoglobulins and T-cell receptors) and major histocompatibility complex (MHC) of all vertebrate species. IMGT accurate immunogenetics data are based on the standardization of the biological knowledge provided by the 'ImMunoGeneTics' IMGT-ONTOLOGY. The IMGT-ONTOLOGY describes the classification and specification of terms needed for immunogenetics and bioinformatics. IMGT-ONTOLOGY covers four main concepts: 'IDENTIFICATION', 'DESCRIPTION', 'CLASSIFICATION' and 'OBTENTION'. These concepts allow an extensive and standardized description and characterization of immunoglobulin and T-cell receptor data. The controlled vocabulary and the annotation rules are indispensable to ensure accuracy, consistency and coherence in IMGT. IMGT-ONTOLOGY allows scientists and clinicians to use, for the first time, identical terms with the same meaning in immunogenetics. It provides a semantic repository that will improve interoperability between specialist and generalist databases.

Animals↗
PubMed2001

Bioinformatics for rice resources.

The distinguishing feature of the 'new biology' is that it is information intensive. Not only does it demand access to and assimilation of vast data sets accumulated by engineered laboratory processes, but it also demands a previously unimaginable level of data integration across data types and sources. There are various information resources available for rice. In addition, there are various information resources that are not focused on rice but that contain rice data. The challenge for rice researchers and breeders is to access this wealth of data meaningfully. This challenge will grow significantly as international efforts aimed at sequencing the entire rice genome come into full swing. Only through concerted efforts in bioinformatics will the power of these public data be brought to bear on the needs of rice researchers and breeders worldwide. These efforts will need to focus on two large but distinct areas: (1) development of an effective bioinformatics infrastructure (hardware systems, software systems, and software engineers and support staff) and (2) computational biology research in visualization and analysis of very large, complex data sets, such as those that will be developed using high-throughput expression technologies, large-scale insertional mutagenesis, and biochemical profiling of various types. In the midst of the large flow of high-throughput data that the international rice genome sequencing efforts will produce, it is also imperative that integration of those data with unique germplasm data held in trust by the CGIAR be a part of the informatics infrastructure. This paper will focus on the state of rice information resources, the needs of the rice community, and some proposed bioinformatics activities to support these needs.

Algorithms↗
PubMed1996

Bioinformatics--principles and potential of a new multidisciplinary tool.

The materials of bioinformatics are biological data, and its methods are derived from a wide variety of computational techniques. Recent years have seen an explosive growth in biological data, and the development of novel computational methods. These methods have become essential to research progress in structural biology, genomics, structure-based drug design and molecular evolution. The development and maintenance of a robust infrastructure of biological data is of equal importance if biotechnology is to take maximum advantage of research advances in a wide variety of fields. While bioinformatics has already made important contributions, it faces significant challenges as it matures.

Animals↗
PubMed2004

The carbohydrate sequence markup language (CabosML): an XML description of carbohydrate structures.

UNLABELLED: Bioinformatics resources for glycomics are very poor as compared with those for genomics and proteomics. The complexity of carbohydrate sequences makes it difficult to define a common language to represent them, and the development of bioinformatics tools for glycomics has not progressed. In this study, we developed a carbohydrate sequence markup language (CabosML), an XML description of carbohydrate structures. AVAILABILITY: The language definition (XML Schema) and an experimental database of carbohydrate structures using an XML database management system are available at http://www.phoenix.hydra.mki.co.jp/CabosDemo.html CONTACT: kikuchi@hydra.mki.co.jp.

Carbohydrate Sequence↗
PubMed2002

The vaccinia virus N1L protein is an intracellular homodimer that promotes virulence.

The vaccinia virus (VV) N1L gene encodes a protein of 14 kDa that was identified previously in the concentrated supernatant of virus-infected cells. Here we show that the protein is present predominantly (>90%) within cells rather than in the culture supernatant and it exists as a non-glycosylated, non-covalent homodimer. The N1L protein present in the culture supernatant was uncleaved at the N terminus and was released from cells more slowly than the VV A41L gene product, a secreted glycoprotein that has a conventional signal peptide. Bioinformatic analyses predict that the N1L protein is largely alpha-helical and show that it is conserved in many VV strains, in other orthopoxviruses and in members of other chordopoxvirus genera. However, database searches found no non-poxvirus proteins with significant amino acid similarity to N1L. A deletion mutant lacking the N1L gene replicated normally in cell culture, but was attenuated in intranasal and intradermal murine models compared to wild-type and revertant controls. The conservation of the N1L protein and the attenuated phenotype of the deletion mutant indicate an important role in the virus life-cycle.

Animals↗
PubMedDate not supplied

An insight-based methodology for evaluating bioinformatics visualizations.

High-throughput experiments, such as gene expression microarrays in the life sciences, result in very large data sets. In response, a wide variety of visualization tools have been created to facilitate data analysis. A primary purpose of these tools is to provide biologically relevant insight into the data. Typically, visualizations are evaluated in controlled studies that measure user performance on predetermined tasks or using heuristics and expert reviews. To evaluate and rank bioinformatics visualizations based on real-world data analysis scenarios, we developed a more relevant evaluation method that focuses on data insight. This paper presents several characteristics of insight that enabled us to recognize and quantify it in open-ended user tests. Using these characteristics, we evaluated five microarray visualization tools on the amount and types of insight they provide and the time it takes to acquire it. The results of the study guide biologists in selecting a visualization tool based on the type of their microarray data, visualization designers on the key role of user interaction techniques, and evaluators on a new approach for evaluating the effectiveness of visualizations for providing insight. Though we used the method to analyze bioinformatics visualizations, it can be applied to other domains.

Algorithms↗
PubMed2004

Identification of novel highly expressed genes in pancreatic ductal adenocarcinomas through a bioinformatics analysis of expressed sequence tags.

In most microarray experiments, a significant fraction of the differentially expressed mRNAs identified correspond to expressed sequence tags (ESTs) and are generally discarded from further analyses. We used careful bioinformatics analyses to characterize those ESTs that were found to be highly overexpressed in a series of pancreatic adenocarcinomas. cDNA was prepared from 60 non-neoplastic samples (normal pancreas [n = 20], normal colon [n = 10], or normal duodenal mucosal [n = 30]) and from 64 pancreatic cancers (resected cancers [n = 50] or cancer cell lines [n = 14]) and hybridized to the complete Affymetrix Human Genome U133 GeneChip(R) set (arrays U133A and B) for simultaneous analysis of 45,000 fragments corresponding to 33,000 known genes and 6,000 ESTs. The GeneExpress(R) software system Fold Change Analysis Tool was used and 60 ESTs were identified that were expressed at levels at least 3-fold greater in the pancreatic cancers as compared to normal tissues. Searches against the human genomic sequence and comparative genomic analysis of human and mouse genomes was carried out using basic local alignment search tools (BLAST), BLASTN, and BLASTX, for identifying protein coding genes corresponding to the ESTs. Subsequently, in order to pick the most relevant candidate genes for a more detailed analysis, we looked for domains/motifs in the open reading frames using SMART and Pfam programs. We were able to definitively map 43 of the 60 ESTs to known or novel genes, and 15 of the ESTs could be localized in close proximity to a gene in the human genome although we were unable to establish that the EST was indeed derived from those genes. The differential expression of a subset of genes was confirmed at the protein level by immunohistochemical labeling of tissue microarrays (inhibin beta A [INHBA] and CD29) and/or at the transcript level by RT-PCR (INHBA, AKAP12, ELK3, FOXQ1, EIF5A2, and EFNA5). We conclude that bioinformatics tools can be used to characterize differentially overexpressed ESTs, and that some of these ESTs may represent diagnostically and therapeutically useful targets that might be missed using data solely from currently annotated databases.

Adenocarcinoma↗
PubMed2001

Bioinformatics in medical practice: what is necessary for a hospital?

Building bioinformatic facilities for a university hospital is pretty similar to using standardized building blocks to construct a house. Starting with the intention to built a dwelling house, a factory or just a shelter the architect draws a construction plan and determines the material to be used. In general, the building is then constructed by the workmen following exactly the plan. However, for particular reasons, minor alterations may be needed to improve the construction of the building. Here we use the metaphor of constructing a "bio-informatics building" to describe the steps needed to support the daily tasks of a university hospital medical microbiology department which uses genomic methods quite extensively for pathogen identification. Today the Giessen "bioinformatics building" is not yet complete but we have been able to lay solid foundations and erect the ground floor which is functional already. Using a combination of standard tools, internet accessible genomic databases and some own software tools we can support genome sequencing from the raw sequence to pathogen identification.

Computational Biology↗
PubMed2006

A comparative analysis of highly conserved sex-determining genes between Apis mellifera and Drosophila melanogaster.

A comparison of the most conserved sex-determining genes between the fruit fly, Drosophila melanogaster, and the honey bee, Apis mellifera, was performed with bioinformatics tools developed for computational molecular biology. An initial set of protein sequences already described in the fruit fly as participants of the sex-determining cascade was retrieved from the Gene Ontology database (http://www.geneontology.org/) and aligned against a database of protein sequences predicted from the honey bee genome. The doublesex (dsx) gene is considered one of the most conserved sex-determining genes among metazoans, and a male-specific partial cDNA of putative A. mellifera dsx gene (Amdsx) was identified experimentally. The theoretical predictions were developed in the context of sequence similarity. Experimental evidence indicates that dsx is present in embryos and larvae, and that it encodes a transcription factor widely conserved in metazoans, containing a DM DNA-binding domain implicated in the regulation of the expression of genes involved in sexual phenotype formation.

Animals↗
PubMed2005

GeneFarm, structural and functional annotation of Arabidopsis gene and protein families by a network of experts.

Genomic projects heavily depend on genome annotations and are limited by the current deficiencies in the published predictions of gene structure and function. It follows that, improved annotation will allow better data mining of genomes, and more secure planning and design of experiments. The purpose of the GeneFarm project is to obtain homogeneous, reliable, documented and traceable annotations for Arabidopsis nuclear genes and gene products, and to enter them into an added-value database. This re-annotation project is being performed exhaustively on every member of each gene family. Performing a family-wide annotation makes the task easier and more efficient than a gene-by-gene approach since many features obtained for one gene can be extrapolated to some or all the other genes of a family. A complete annotation procedure based on the most efficient prediction tools available is being used by 16 partner laboratories, each contributing annotated families from its field of expertise. A database, named GeneFarm, and an associated user-friendly interface to query the annotations have been developed. More than 3000 genes distributed over 300 families have been annotated and are available at http://genoplante-info.infobiogen.fr/Genefarm/. Furthermore, collaboration with the Swiss Institute of Bioinformatics is underway to integrate the GeneFarm data into the protein knowledgebase Swiss-Prot.

Arabidopsis↗