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At least 1,117 records · Page 62Linked to original sources
PubMed2000

[Molecular cloning of a novel gene located on chromosome 3p25.3 and an analysis of its expression in nasopharyngeal carcinoma].

OBJECTIVE: To obtain the novel genes associated with human nasopharyngeal carcinoma(NPC) on chromosome 3p24-26. METHODS: Twenty epithelial-derived expressed sequence tags(EST) were selected from chromosome 3p24-26 where loss of heterozygosity(LOH) frequently occurs in NPC tissues. Primers were designed based on the sequences of these ESTs. RT-PCR was used to amply their corresponding cDNA fragments from NPC cell line HNE1 and primary cultures of normal nasopharyngeal epithelial cells. The differential expression of two ESTs, T93093 and R41598, was confirmed by Northern blot. Then, expression of EST T93093 was further detected in 7 normal nasopharyngeal and 19 NPC biopsies. cDNA library screening was used to get its full cDNA sequence and the sequence of this novel gene was analyzed by bioinformatics. RESULTS: Thirteen ESTs(T62511, N39155, N68660, R61275, T95314, R06143, H52697, H66521, AA128685, AA284537, N52379, AA054180, and H98090) showed the similar expression level and 5 ESTs(R00732, R07573, R98052, H91759, H17566) showed no expression in both types of cells. EST T93093 was down-expressed, whereas EST R41598 up-expressed in NPC HNE1 cells. The EST T93093 was also found to be down-expressed in 26.3%(5/19) of NPC biopsies. The full length cDNA of this gene was obtained and named NAG-7, which is located at chromosome 3p25.3. Its 1677 bp full length cDNA has a potential open reading frame(ORF) predicting a 94 amino acid protein with a molecular weight of 11023.87 Dalton. Bioinformatics analysis of the NAG-7 gene shows that it is a transmembrane protein containing a protein kinase C(PKC) phosphorylation site and a myristyl site. It has no significant homology to any reported genes in database of GenBank(AF086709). CONCLUSION: NAG-7 is a novel gene down-expressed in NPC, which may be involved in the development of NPC.

Chromosome Mapping↗
PubMed2006

Gene Class expression: analysis tool of Gene Ontology terms with gene expression data.

Serial analysis of gene expression (SAGE) technology produces large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in these gene sets. We present an interactive web-based tool, called Gene Class, which allows functional annotation of SAGE data using the Gene Ontology (GO) database. This tool performs searches in the GO database for each SAGE tag, making associations in the selected GO category for a level selected in the hierarchy. This system provides user-friendly data navigation and visualization for mapping SAGE data onto the gene ontology structure. This tool also provides graphical visualization of the percentage of SAGE tags in each GO category, along with confidence intervals and hypothesis testing.

Animals↗
PubMed2005

AutoFACT: an automatic functional annotation and classification tool.

BACKGROUND: Assignment of function to new molecular sequence data is an essential step in genomics projects. The usual process involves similarity searches of a given sequence against one or more databases, an arduous process for large datasets. RESULTS: We present AutoFACT, a fully automated and customizable annotation tool that assigns biologically informative functions to a sequence. Key features of this tool are that it (1) analyzes nucleotide and protein sequence data; (2) determines the most informative functional description by combining multiple BLAST reports from several user-selected databases; (3) assigns putative metabolic pathways, functional classes, enzyme classes, GeneOntology terms and locus names; and (4) generates output in HTML, text and GFF formats for the user's convenience. We have compared AutoFACT to four well-established annotation pipelines. The error rate of functional annotation is estimated to be only between 1-2%. Comparison of AutoFACT to the traditional top-BLAST-hit annotation method shows that our procedure increases the number of functionally informative annotations by approximately 50%. CONCLUSION: AutoFACT will serve as a useful annotation tool for smaller sequencing groups lacking dedicated bioinformatics staff. It is implemented in PERL and runs on LINUX/UNIX platforms. AutoFACT is available at http://megasun.bch.umontreal.ca/Software/AutoFACT.htm.

Acanthamoeba castellanii↗
PubMed2002

CHOMPER: a bioinformatic tool for rapid validation of tandem mass spectrometry search results associated with high-throughput proteomic strategies.

Current efforts aimed at developing high-throughput proteomics focus on increasing the speed of protein identification. Although improvements in sample separation, enrichment, automated handling, mass spectrometric analysis, as well as data reduction and database interrogation strategies have done much to increase the quality, quantity and efficiency of data collection, significant bottlenecks still exist. Various separation techniques have been coupled with tandem mass spectrometric (MS/MS) approaches to allow a quicker analysis of complex mixtures of proteins, especially where a high number of unambiguous protein identifications are the exception, rather than the rule. MS/MS is required to provide structural / amino acid sequence information on a peptide and thus allow protein identity to be inferred from individual peptides. Currently these spectra need to be manually validated because: (a) the potential of false positive matches i.e., protein not in database, and (b) observed fragmentation trends may not be incorporated into current MS/MS search algorithms. This validation represents a significant bottleneck associated with high-throughput proteomic strategies. We have developed CHOMPER, a software program which reduces the time required to both visualize and confirm MS/MS search results and generate post-analysis reports and protein summary tables. CHOMPER extracts the identification information from SEQUEST MS/MS search result files, reproduces both the peptide and protein identification summaries, provides a more interactive visualization of the MS/MS spectra and facilitates the direct submission of manually validated identifications to a database.

Algorithms↗
PubMed2005

PSST-2.0: Protein Data Bank Sequence Search Tool.

UNLABELLED: PSST-2.0 (Protein Data Bank [PDB] Sequence Search Tool) is an updated version of the earlier PSST (Protein Sequence Search Tool), and the philosophy behind the search engine has remained unchanged. PSST-2.0 is a Web-based, interactive search engine developed to retrieve required protein or nucleic acid sequence information and some of its related details, primarily from sequences derived from the structures deposited in the PDB (the database of 3-dimensional [3-D] protein and nucleic acid structures). Additionally, the search engine works for a selected subset of 25% or 90% non-homologous protein chains. For some of the selected options, the search engine produces a detailed output for the user-uploaded, 3-D atomic coordinates of the protein structure (PDB file format) from the client machine through the Web browser. The search engine works on a locally maintained PDB, which is updated every week from the parent server at the Research Collaboratory for Structural Bioinformatics, and hence the search results are up to date at any given time. AVAILABILITY: PSST-2.0 is freely accessible via http://pranag.physics.iisc.ernet.in/psst/ or http://144.16.71.10/psst/.

Algorithms↗
PubMed2000

The role of the pathologist as tissue refiner and data miner: the impact of functional genomics on the modern pathology laboratory and the critical roles of pathology informatics and bioinformatics.

This article provides an overview of how functional genomics is likely to impact on the pathology laboratory and highlights how informatics and tissue banking will greatly facilitate the molecular age of medicine. Important aspects of functional genomics in the post-genome era, including the roles of laser capture microdissection, DNA- and complementary DNA-based microarrays, proteomic methods, collaborative human tissue banking, tissue microarrays, and pathobioinformatics in the modern pathology laboratory are discussed. The role of mass spectroscopy in the analysis of RNA, DNA, and protein and its impact on the clinical laboratory, particularly in cost-effectiveness and time savings, are evaluated. This article explores how laboratory information systems (LISs) and the devices that feed them information may need to be modified to adapt to greater volumes of data for the new testing modalities that require understanding sophisticated fluorescence detection methods and image processing. Emerging genomic testing methods and their impact on pathology laboratory testing, especially in the area of molecular classification of neoplasms, are examined. The role of the tissue bank in the modern pathology laboratory as an archive of control normal tissues, as well as subsamples of the spectrum of progressive neoplastic states, is discussed in light of its critical importance to the molecular classification of cancer. Establishing a database that combines structured reports in pathology LISs and construction of tissue banking information systems will provide a rich resource for pathology departments. The article discusses a hypothetical resource, such as the Shared Tumor Expression Profiler, that would provide access to well-characterized tissue-based research resources for clinicians and researchers. Last, the article emphasizes how LISs can prepare for these changes, and how training pathologists in pathology informatics and bioinformatics (pathobioinformatics) is critical to ensure pathology's overall leadership role in the post-genome era.

Clinical Laboratory Techniques↗
PubMed2005

Pattern profiling and mapping of the fat body transcriptome in Drosophila melanogaster.

In Drosophila, the fat body is a collective name for the masses and sheets of adipose tissue that are distributed throughout the fly body. Thus far, >386,000 Drosophila expressed sequence tags (ESTs) have been deposited to the GenBank database, including 10,443 derived from fat body in flies (data accessed on October 7, 2004). The objective of this study was to map the transcriptome of the fat body in flies and thus provide genomics and bioinformatics tools for developing a Drosophila model for addressing the genetic complexity of obesity in humans. The gene-EST Basic Local Alignment Search Tool (BLAST) matches revealed that these ESTs could represent 12,188 coding genes in the Drosophila genome. Among them, at least 2,261 are expressed in the fat body, including 41 identified as preferentially expressed genes with logarithm of odds >3.0. Self-organizing map analysis revealed a cluster of 290 genes favorably expressed in the fat body compared with genes expressed in five other tissues. Mapping of the fat body transcriptome identified a 1.7-Mb domain on 3L containing 35 genes that were expressed at a much higher level than in other tissues (transcript density factor = 1.0 approximately 2.3).

Animals↗
PubMed2005

PAT: a protein analysis toolkit for integrated biocomputing on the web.

PAT, for Protein Analysis Toolkit, is an integrated biocomputing server. The main goal of its design was to facilitate the combination of different processing tools for complex protein analyses and to simplify the automation of repetitive tasks. The PAT server provides a standardized web interface to a wide range of protein analysis tools. It is designed as a streamlined analysis environment that implements many features which strongly simplify studies dealing with protein sequences and structures and improve productivity. PAT is able to read and write data in many bioinformatics formats and to create any desired pipeline by seamlessly sending the output of a tool to the input of another tool. PAT can retrieve protein entries from identifier-based queries by using pre-computed database indexes. Users can easily formulate complex queries combining different analysis tools with few mouse clicks, or via a dedicated macro language, and a web session manager provides direct access to any temporary file generated during the user session. PAT is freely accessible on the Internet at http://pat.cbs.cnrs.fr.

Computational Biology↗
PubMed2006

EVEREST: a collection of evolutionary conserved protein domains.

Protein domains are subunits of proteins that recur throughout the protein world. There are many definitions attempting to capture the essence of a protein domain, and several systems that identify protein domains and classify them into families. EVEREST, recently described in Portugaly et al. (2006) BMC Bioinformatics, 7, 277, is one such system that performs the task automatically, using protein sequence alone. Herein we describe EVEREST release 2.0, consisting of 20,029 families, each defined by one or more HMMs. The current EVEREST database was constructed by scanning UniProt 8.1 and all PDB sequences (total over 3,000,000 sequences) with each of the EVEREST families. EVEREST annotates 64% of all sequences, and covers 59% of all residues. EVEREST is available at http://www.everest.cs.huji.ac.il/. The website provides annotations given by SCOP, CATH, Pfam A and EVEREST. It allows for browsing through the families of each of those sources, graphically visualizing the domain organization of the proteins in the family. The website also provides access to analyzes of relationships between domain families, within and across domain definition systems. Users can upload sequences for analysis by the set of EVEREST families. Finally an advanced search form allows querying for families matching criteria regarding novelty, phylogenetic composition and more.

Amino Acid Sequence↗
PubMed2004

Transferable antibiotic resistance elements in Haemophilus influenzae share a common evolutionary origin with a diverse family of syntenic genomic islands.

Transferable antibiotic resistance in Haemophilus influenzae was first detected in the early 1970s. After this, resistance spread rapidly worldwide and was shown to be transferred by a large 40- to 60-kb conjugative element. Bioinformatics analysis of the complete sequence of a typical H. influenzae conjugative resistance element, ICEHin1056, revealed the shared evolutionary origin of this element. ICEHin1056 has homology to 20 contiguous sequences in the National Center for Biotechnology Information database. Systematic comparison of these homologous sequences resulted in identification of a conserved syntenic genomic island consisting of up to 33 core genes in 16 beta- and gamma-Proteobacteria. These diverse genomic islands shared a common evolutionary origin, insert into tRNA genes, and have diverged widely, with G+C contents ranging from 40 to 70% and amino acid homologies as low as 20 to 25% for shared core genes. These core genes are likely to account for the conjugative transfer of the genomic islands and may even encode autonomous replication. Accessory gene clusters were nestled among the core genes and encode the following diverse major attributes: antibiotic, metal, and antiseptic resistance; degradation of chemicals; type IV secretion systems; two-component signaling systems; Vi antigen capsule synthesis; toxin production; and a wide range of metabolic functions. These related genomic islands include the following well-characterized structures: SPI-7, found in Salmonella enterica serovar Typhi; PAP1 or pKLC102, found in Pseudomonas aeruginosa; and the clc element, found in Pseudomonas sp. strain B13. This is the first report of a diverse family of related syntenic genomic islands with a deep evolutionary origin, and our findings challenge the view that genomic islands consist only of independently evolving modules.

Base Sequence↗
PubMed2026

Exploring shared biomarkers and their mechanisms in thyroid cancer and systemic lupus erythematosus via bioinformatics analysis.

BACKGROUND: Systemic lupus erythematosus (SLE), an autoimmune disorder, is linked to a heightened risk of multiple malignancies, including thyroid cancer. Thyroid cancer is the most prevalent malignancy of the endocrine system, and its autoimmune-related pathological features render it an optimal subject for investigating the mechanisms of their comorbidity. The molecular mechanisms underlying this comorbidity are still ambiguous. The accurate diagnosis and treatment of thyroid cancer urgently necessitate innovative molecular targets that extend beyond conventional pathological characteristics. This study seeks to employ integrated bioinformatics approaches to elucidate potential shared molecular mechanisms and immunological features between thyroid cancer and systemic lupus erythematosus (SLE), aiming to enhance understanding of their comorbidity and identify novel intervention targets. METHODS: This study initially acquired gene expression data for TC and SLE from the GEO database and subsequently screened and identified differentially expressed genes (DEGs) shared by both diseases. Subsequently, we conducted Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome functional enrichment analyses on these 46 shared differentially expressed genes (DEGs) and further assessed the activation status of pertinent pathways using Gene Set Enrichment Analysis (GSEA). Subsequently, we employed CIBERSORTx to examine immune infiltration patterns and developed protein-protein interaction networks utilising the STRING database. We identified hub genes utilising the MCODE and cytoHubba plugins and visualised the findings with Cytoscape software. We additionally assessed the diagnostic efficacy of these core hub genes in an independent dataset utilising ROC curves and investigated their prognostic relevance in thyroid cancer through Kaplan-Meier survival analysis and multivariate Cox proportional hazards regression. Ultimately, we employed the Network Analyst platform to forecast transcription factor-gene and miRNA-gene regulatory networks and identified potential targeted therapeutic compounds utilising the DSigDB database. RESULTS: This study identified 46 differentially expressed genes (DEGs) commonly linked to thyroid cancer and systemic lupus erythematosus (SLE), which were significantly enriched in signalling pathways associated with immune-inflammatory activation, type I interferon responses, and complement pathway activation. Moreover, GSEA findings validated that immune-inflammatory and autoimmune-related pathways are markedly activated in both conditions. Twelve hub genes were discerned through protein-protein interaction networks. Analysis of immune infiltration indicated that thyroid cancer and systemic lupus erythematosus exhibit a shared characteristic of innate immune dysregulation, marked by the infiltration of myeloid cells (neutrophils, M0/M2 macrophages). Receiver operating characteristic (ROC) curve analysis identified six significant core hub genes with substantial diagnostic value: C1QB, LCN2, C1QC, LTF, VSIG4, and C3AR1. Univariate survival analysis indicated that elevated expression of C1QC and C3AR1 significantly enhances overall survival in thyroid cancer patients; however, multivariate COX regression analysis revealed that their independent prognostic significance necessitates further validation. This study predicted the interaction networks of transcription factors and miRNAs regulating key genes, with LCN2 demonstrating the highest connectivity to miRNAs, and identified candidate therapeutic compounds linked to it. CONCLUSION: This study employed bioinformatics analysis to identify critical shared hub genes and molecular pathways connecting thyroid cancer and systemic lupus erythematosus, offering novel insights into their shared pathogenesis and the advancement of targeted biomarkers and therapeutic strategies.

Bioinformatics analysis↗
PubMed2004

VirGen: a comprehensive viral genome resource.

VirGen is a comprehensive viral genome resource that organizes the 'sequence space' of viral genomes in a structured fashion. It has been developed with the objective of serving as an annotated and curated database comprising complete genome sequences of viruses, value-added derived data and data mining tools. The current release (v1.1) contains 559 complete genomes in addition to 287 putative genomes of viruses belonging to eight viral families for which the host range includes animals and plants. Viral genomes in VirGen are annotated using sequence-based Bioinformatics approaches. The genomic data is also curated to identify 'alternate names' of viral proteins, where available. VirGen archives the results of comparisons of genomes, proteomes and individual proteins within and between viral species. It is the first resource to provide phylogenetic trees of viral species computed using whole-genome sequence data. The module of predicted B-cell antigenic determinants in VirGen is an attempt to link the genome to its vaccinome. Comparative genome analysis data facilitate the study of genome organization and evolution of viruses, which would have implications in applied research to identify candidates for the design of vaccines and antiviral drugs. VirGen is a relational database and is available at http://bioinfo. ernet.in/virgen/virgen.html.

Antigens, Viral↗
PubMed2005

Atlas - a data warehouse for integrative bioinformatics.

BACKGROUND: We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development. DESCRIPTION: The Atlas system is based on relational data models that we developed for each of the source data types. Data stored within these relational models are managed through Structured Query Language (SQL) calls that are implemented in a set of Application Programming Interfaces (APIs). The APIs include three languages: C++, Java, and Perl. The methods in these API libraries are used to construct a set of loader applications, which parse and load the source datasets into the Atlas database, and a set of toolbox applications which facilitate data retrieval. Atlas stores and integrates local instances of GenBank, RefSeq, UniProt, Human Protein Reference Database (HPRD), Biomolecular Interaction Network Database (BIND), Database of Interacting Proteins (DIP), Molecular Interactions Database (MINT), IntAct, NCBI Taxonomy, Gene Ontology (GO), Online Mendelian Inheritance in Man (OMIM), LocusLink, Entrez Gene and HomoloGene. The retrieval APIs and toolbox applications are critical components that offer end-users flexible, easy, integrated access to this data. We present use cases that use Atlas to integrate these sources for genome annotation, inference of molecular interactions across species, and gene-disease associations. CONCLUSION: The Atlas biological data warehouse serves as data infrastructure for bioinformatics research and development. It forms the backbone of the research activities in our laboratory and facilitates the integration of disparate, heterogeneous biological sources of data enabling new scientific inferences. Atlas achieves integration of diverse data sets at two levels. First, Atlas stores data of similar types using common data models, enforcing the relationships between data types. Second, integration is achieved through a combination of APIs, ontology, and tools. The Atlas software is freely available under the GNU General Public License at: http://bioinformatics.ubc.ca/atlas/

Computational Biology↗
PubMed2003

Hidden Markov models and optimized sequence alignments.

We present a formulation of the Needleman-Wunsch type algorithm for sequence alignment in which the mutation matrix is allowed to vary under the control of a hidden Markov process. The fully trainable model is applied to two problems in bioinformatics: the recognition of related gene/protein names and the alignment and scoring of homologous proteins.

Animals↗
PubMed2006

3dSS: 3D structural superposition.

3dSS is a web-based interactive computing server, primarily designed to aid researchers, to superpose two or several 3D protein structures. In addition, the server can be effectively used to find the invariant and common water molecules present in the superposed homologous protein structures. The molecular visualization tool RASMOL is interfaced with the server to visualize the superposed 3D structures with the water molecules (invariant or common) in the client machine. Furthermore, an option is provided to save the superposed 3D atomic coordinates in the client machine. To perform the above, users need to enter Protein Data Bank (PDB)-id(s) or upload the atomic coordinates in PDB format. This server uses a locally maintained PDB anonymous FTP server that is being updated weekly. This program can be accessed through our Bioinformatics web server at the URL http://cluster.physics.iisc.ernet.in/3dss/ or http://10.188.1.15/3dss/.

Computer Graphics↗
PubMed2002

Bioinformatic analysis of the human mu opioid receptor (OPRM1) splice and polymorphic variants.

Mu opioid receptor (OPRM1), a member of the G-protein coupled receptor superfamily, mediates the analgesic and euphoric effects of opioid drugs. The sequences of OPRM1 cDNA and reported splice variants were used to search the public and Celera genomic databases. The matched sequences were analyzed to assemble an OPRM1 genomic contig. Human OPRM1 gene was estimated to span at least 90 kb in the chromosome 6q24-25 region. Four coding exons are separated by 3 introns. While intron 2 has only 773 bp, these databases for the first time provide the precise length of and other information about long introns 1 and 3, containing 50 and 27 kb, respectively. When a consensus exon/intron splice junction at the end of the coding exon 3 was not utilized, it may have resulted in continuous translation of the exon to yield the splice variant OPRM1A. The study did not identify human orthologs of other OPRM1 variants that had been reported for mouse OPRM1, although several proposed exons were found to be included in mouse genomic clones. Single nucleotide polymorphisms in the OPRM1 gene were also analyzed and summarized, which could provide potential polymorphic markers for molecular genetic studies.

Alternative Splicing↗
PubMed2026

Metatranscriptomic analysis of viral sequences associated with Culex nigripalpus at an Alabama aquaculture site.

Mosquitoes associated with aquaculture habitats can harbor diverse viruses, yet the viromes of many locally abundant species remain poorly characterized. At an aquaculture-associated site in Auburn, Alabama, we surveyed mosquito populations and found Culex nigripalpus to be the dominant species collected. To characterize viruses associated with this mosquito, we performed RNA-seq on pooled female Cx. nigripalpus and compared complementary bioinformatic workflows for viral detection and genome recovery. One workflow removed host-associated reads by mapping to the closest available mosquito reference genome prior to assembly, whereas a second workflow used fully de novo assembly and viral database annotation. Additional protein-level filtering, cross-workflow comparison, and comparison of Trinity and rnaSPAdes assemblies were used to prioritize well-supported viral candidates. Across the original analyses, 16 submitted accessions corresponding to 12 collapsed virus/name groups were recovered, including Merida virus, Hubei mosquito virus 5, Zhejiang mosquito virus, Hubei virga-like virus 3, Rinkaby virus, Elemess virus, Qingnian mosquito virus, Serbia narna-like virus 2, XiangYun narna-levi-like virus 8, Ecclesville picorna-like virus, and baculovirus-like fragments. Several candidates were supported across multiple workflows, while others were recovered only under specific analytical conditions, indicating that candidate recovery was influenced by assembly and filtering choices. Selected viral contigs were independently supported by RT-PCR amplification. Overall, these results provide a first characterization of viral sequences associated with Cx. nigripalpus from an Alabama aquaculture-associated site and show that comparison across assembly and filtering strategies helped prioritize the most consistently supported viral candidates.

Animals↗
PubMed2003

Protein family classification and functional annotation.

With the accelerated accumulation of genomic sequence data, there is a pressing need to develop computational methods and advanced bioinformatics infrastructure for reliable and large-scale protein annotation and biological knowledge discovery. The Protein Information Resource (PIR) provides an integrated public resource of protein informatics to support genomic and proteomic research. PIR produces the Protein Sequence Database of functionally annotated protein sequences. The annotation problems are addressed by a classification-driven and rule-based method with evidence attribution, coupled with an integrated knowledge base system being developed. The approach allows sensitive identification, consistent and rich annotation, and systematic detection of annotation errors, as well as distinction of experimentally verified and computationally predicted features. The knowledge base consists of two new databases, sequence analysis tools, and graphical interfaces. PIR-NREF, a non-redundant reference database, provides a timely and comprehensive collection of all protein sequences, totaling more than 1,000,000 entries. iProClass, an integrated database of protein family, function, and structure information, provides extensive value-added features for about 830,000 proteins with rich links to over 50 molecular databases. This paper describes our approach to protein functional annotation with case studies and examines common identification errors. It also illustrates that data integration in PIR supports exploration of protein relationships and may reveal protein functional associations beyond sequence homology.

Amino Acid Motifs↗