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Results for “Bioinformatics analysis”

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At least 1,135 records · Page 63Linked to original sources

PubMed2004

[Genomic sequence of hepatitis A virus L-A-1 vaccine strain].

OBJECTIVE: To study the genome sequence of hepatitis A virus L-A-1 strain which has been applied for live attenuated vaccine production in China, to compare with other HAV strains, to understand some characteristics of L-A-1 strain, and to find the mechanism of attenuation and cell adaptation. METHODS: Genome fragments were prepared by antigen-capture PCR from infected cell (2BS), PCR products were cloned into T vector, sequenced and analyzed by using bioinformatics program. RESULTS: Analysis of the genomic sequences(nt 25-7,418) showed that the open reading frame contains 6,675 nucleotides in length encoding 2,225 amino acids. Sequence homology comparison showed 98.00% and 94.00% homology at nucleotide level, and 98.51% and 98.65% homology at amino acid level with international strains MBB and HM 175, respectively. Through comparison with other attenuated, cell adapted and cytopathic effect (CPE) strains, L-A-1 strain had mutation at nt 152, 591, 646, 687 and insertion at nt 180-181 in 5?NTR and had mutation at nt 3,889 (aa 1 052-Val) in 2B region, these mutations and insertion are molecular basis for cell adaptation; mutation at nt 4,185 (aa 1 152-Lys) in 2C region should be attenuated marker; deletion in 3A region (nt 5,020-5,025) that caused two amino acids deletion is virus fast growth basis. CONCLUSION: Through analyzing L-A-1 strain genomic sequence, certain sites related to cell adaptation and attenuation were found.

Adaptation, Biological↗

PubMed1999

Applied proteomics--analyzing protein structure and function for drug discovery. 27-28 January 1999, London, UK.

This two-day meeting, attended by approximately 60 delegates, was aimed at researchers in the proteomics field. The proteome is defined as the entire protein content of the cell. Proteomics is the analysis of the end-product of gene expression and all regulations governing gene expression are taken into account, ie, transcriptional and translational. The three stages involved in proteomic analysis are: a separation phase, ie, two dimensional (2D) gel electrophoresis; a characterization phase, ie, mass spectrometry; and, a data analysis phase, ie, bioinformatics.

Journal Article↗

PubMed1997

Detailed analysis of a 17q21 microdissection library by sequence bioinformatics and isolation of region-specific clones.

A region-specific microdissection library originating from human chromosome 17q21, was constructed using the MboI linker-adaptor microcloning technique. DNA sequencing of 241 microclones resulted in the identification of 74 novel coding sequences, paralogs of known genes, and known, but previously unmapped, genes or expressed sequence tags that were "virtually" mapped to chromosome 17q21. By pooling the microclones as multiplexed hybridization probes, and by virtue of their origin on 17q21, we were able to identify approximately 150 P1 clones from the human Reference Library Data Base P1 Library that potentially map to chromosome 17q21. Verification of the 17q21 location of 16 P1 clones was accomplished by PCR analysis with STS primer pairs to known 17q21 genes or by FISH. Our results demonstrate the substantial advantage of combining the sequence analysis of microclones with multiplex hybridization strategies for gene discovery and mapping specific gene rich regions of the genome.

Base Sequence↗

PubMed2004

Bioinformatic mining of type I microsatellites from expressed sequence tags of channel catfish (Ictalurus punctatus).

Gene-derived markers are pivotal to the analysis of genome structure, organization, and evolution and necessary for comparative genomics. However, gene-derived markers are relatively difficult to develop. This project utilized the genomic resources of channel catfish expressed sequence tags (ESTs) to identify simple sequence repeats (SSRs), or microsatellites. It took the advantage of ESTs for the establishment of gene identities, and of microsatellites for the acquisition of high polymorphism. When microsatellites are tagged to genes, the microsatellites can then be used as gene markers. A bioinformatic analysis of 43,033 ESTs identified 4855 ESTs containing microsatellites. Cluster analysis indicated that 1312 of these ESTs fell into 569 contigs, and the remaining 3534 ESTs were singletons. A total of 4103 unique microsatellite-containing genes were identified. The dinucleotide CA/TG and GA/TC pairs were the most abundant microsatellites. AT-rich microsatellite types were predominant among trinucleotide and tetranucleotide microsatellites, consistent with our earlier estimation that the catfish genome is highly AT-rich. Our preliminary results indicated that the majority of the identified microsatellites were polymorphic and, therefore, useful for genetic linkage mapping of catfish. Mapping of these gene-derived markers is under way, which will set the foundation for comparative genome analysis in catfish.

Animals↗

PubMed2002

Protein sequence analysis in silico: application of structure-based bioinformatics to genomic initiatives.

The current pace of high-throughput genome sequencing programs coupled with high-throughput functional genomic screens has provided researchers with a bewildering array of sequence and biological data to contend with. Identification of proteins of interest from a particular biological study requires the application of bioinformatic tools to process and prioritise the data. From a protein function standpoint, transfer of annotation from known proteins to a novel target is currently the only practical way to convert vast quantities of raw sequence data into meaningful information. New bioinformatics tools now provide more sophisticated methods to transfer functional annotation, integrating sequence, family profile and structural search methodology. The importance of these approaches to medical research is increasing as we move to annotate the proteome through functional and structural genomic efforts.

Animals↗

PubMed2026

CD44 gene rs9666607 polymorphism is associated with papillary thyroid carcinoma and interacts with CREB3L1.

BACKGROUND: The incidence of papillary thyroid carcinoma (PTC) has been rising. CD44 is involved in cell adhesion and migration, but the role of its genetic variation in PTC remains unclear. METHODS: This study aimed to investigate the association of CD44 gene polymorphisms with PTC and to examine the interaction between CD44 and CREB3L1. This study enrolled 354 patients with PTC, and the genotype distribution of the CD44 polymorphism (rs9666607) was analyzed. Key PTC genes were screened using the Gene Expression Omnibus (GEO) database (GSE33630). Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed on these key genes. CD44 expression was validated using TCGA database, ELISA, qRTPCR, Western blot, and IHC in patient tissues, PTC mouse model, and human cell lines. The direct interactive molecules were screened through a bioinformatics method. RESULTS: The GSE33630 dataset identified a total of 124 upregulated and 85 downregulated differentially expressed genes. Enrichment analysis revealed 12 key PTC genes, including CD44. TCGA database validation revealed that CD44 was significantly overexpressed in PTC patients. The rs9666607‑A allele was associated with an increased risk of PTC and lymph node metastasis under a dominant model. CD44 mRNA and protein levels were significantly higher in PTC tissues versus adjacent tissue and further elevated in metastatic cases. Bioinformatic analysis predicted CD44 interaction with the transcription factor CREB3L1, and this was confirmed by molecular docking. CREB3L1 expression was synchronously upregulated with CD44 in PTC. CONCLUSION: CD44 polymorphisms, particularly the rs9666607-A allele, are significantly associated with PTC risk and metastasis in the studied population. CD44 is overexpressed in PTC, and its interaction with CREB3L1 suggests a potential novel interaction in PTC pathogenesis.

Hyaluronan Receptors↗

PubMed2000

Comprehensive gene expression profile of the adult human renal cortex: analysis by cDNA array hybridization.

BACKGROUND: Profiling of gene expression in healthy and diseased renal tissue is important for elucidating the pathogenesis of renal diseases. Comprehensive information about the genes expressed in renal tissue is unavailable. The recently developed cDNA array hybridization methodology allows simultaneous monitoring of thousands of genes expressed renal tissue. METHODS: Complex [alpha-33P]-labeled cDNA probes were prepared from histopathologically uninvolved remnants of nine renal tissues obtained by nephrectomy. Each probe was hybridized to a high-density array of 18,326 paired target genes. The radioactive hybridization signals by phosphorimager screens were quantitated by special software. Bioinformatics from public genomic databases were used to assign a chromosomal location of each expressed transcript and gene function. Cluster analysis was used to arrange genes according to the similarity in pattern of gene expression. RESULTS: A total of 7563 different gene transcripts was detected in the nine tissue samples. Approximately 870 of these genes were full-length mRNA human transcripts (HT), and the remaining 6693 were expressed sequence tags (ESTs). The full-length transcripts were classified by function of the gene product and were listed with information of their chromosomal positions. To allow a comparison between gene expression in clinical and experimental studies, the mouse genes with known similar function to the human counterpart were included in the bioinformatics analysis. Cluster analysis of 502 full-length genes that are expressed in four or more renal tissues revealed more than 110 genes that are highly expressed in all the renal specimens. CONCLUSIONS: The presented data constitute a comprehensive preliminary transcriptional map of the adult human renal cortex. The information may serve as a resource for speeding up the discovery of genes underlying human renal disease. The integrated listing of the full-length expressed human and mouse genes is available through e-mail (Abdalla_Rifai@Brown.edu).

Adult↗

PubMed2006

Agents in bioinformatics, computational and systems biology.

The adoption of agent technologies and multi-agent systems constitutes an emerging area in bioinformatics. In this article, we report on the activity of the Working Group on Agents in Bioinformatics (BIOAGENTS) founded during the first AgentLink III Technical Forum meeting on the 2nd of July, 2004, in Rome. The meeting provided an opportunity for seeding collaborations between the agent and bioinformatics communities to develop a different (agent-based) approach of computational frameworks both for data analysis and management in bioinformatics and for systems modelling and simulation in computational and systems biology. The collaborations gave rise to applications and integrated tools that we summarize and discuss in context of the state of the art in this area. We investigate on future challenges and argue that the field should still be explored from many perspectives ranging from bio-conceptual languages for agent-based simulation, to the definition of bio-ontology-based declarative languages to be used by information agents, and to the adoption of agents for computational grids.

Artificial Intelligence↗

PubMed2005

From cyclohydrolase to oxidoreductase: discovery of nitrile reductase activity in a common fold.

The enzyme YkvM from Bacillus subtilis was identified previously along with three other enzymes (YkvJKL) in a bioinformatics search for enzymes involved in the biosynthesis of queuosine, a 7-deazaguanine modified nucleoside found in tRNA(GUN) of Bacteria and Eukarya. Genetic analysis of ykvJKLM mutants in Acinetobacter confirmed that each was essential for queuosine biosynthesis, and the genes were renamed queCDEF. QueF exhibits significant homology to the type I GTP cyclohydrolases characterized by FolE. Given that GTP is the precursor to queuosine and that a cyclohydrolase-like reaction was postulated as the initial step in queuosine biosynthesis, QueF was proposed to be the putative cyclohydrolase-like enzyme responsible for this reaction. We have cloned the queF genes from B. subtilis and Escherichia coli and characterized the recombinant enzymes. Contrary to the predictions based on sequence analysis, we discovered that the enzymes, in fact, catalyze a mechanistically unrelated reaction, the NADPH-dependent reduction of 7-cyano-7-deazaguanineto7-aminomethyl-7-deazaguanine, a late step in the biosynthesis of queuosine. We report here in vitro and in vivo studies that demonstrate this catalytic activity, as well as preliminary biochemical and bioinformatics analysis that provide insight into the structure of this family of enzymes.

Acinetobacter↗

PubMed2025

VirDetector: a bioinformatic pipeline for virus surveillance using nanopore sequencing.

SUMMARY: Virus surveillance programmes are designed to counter the growing threat of viral outbreaks to human health. Nanopore sequencing, in particular, has proven to be suitable for this purpose, as it is readily available and provides rapid results. However, as special bioinformatic programs are required to extract the relevant information from the sequencing data, applications are needed that allow users without extensive bioinformatics knowledge to carry out the relevant analysis steps. We present VirDetector, a bioinformatic pipeline for virus surveillance using nanopore sequencing. The pipeline automatically installs all required programs and databases and allows all its steps to be executed with a single console command. After preprocessing the samples, including the possibility for basecalling, the pipeline classifies each sample taxonomically and reconstructs the viral consensus genomes, which are then used in phylogenetic analyses. This streamlined workflow provides a user-friendly and efficient solution for monitoring viral pathogens. AVAILABILITY AND IMPLEMENTATION: VirDetector is freely available at https://github.com/NLKaiser/VirDetector and https://zenodo.org/records/14637302 (10.5281/zenodo.14637302).

Nanopore Sequencing↗

PubMed2003

Identification of conserved regulatory elements by comparative genome analysis.

BACKGROUND: For genes that have been successfully delineated within the human genome sequence, most regulatory sequences remain to be elucidated. The annotation and interpretation process requires additional data resources and significant improvements in computational methods for the detection of regulatory regions. One approach of growing popularity is based on the preferential conservation of functional sequences over the course of evolution by selective pressure, termed 'phylogenetic footprinting'. Mutations are more likely to be disruptive if they appear in functional sites, resulting in a measurable difference in evolution rates between functional and non-functional genomic segments. RESULTS: We have devised a flexible suite of methods for the identification and visualization of conserved transcription-factor-binding sites. The system reports those putative transcription-factor-binding sites that are both situated in conserved regions and located as pairs of sites in equivalent positions in alignments between two orthologous sequences. An underlying collection of metazoan transcription-factor-binding profiles was assembled to facilitate the study. This approach results in a significant improvement in the detection of transcription-factor-binding sites because of an increased signal-to-noise ratio, as demonstrated with two sets of promoter sequences. The method is implemented as a graphical web application, ConSite, which is at the disposal of the scientific community at http://www.phylofoot.org/. CONCLUSIONS: Phylogenetic footprinting dramatically improves the predictive selectivity of bioinformatic approaches to the analysis of promoter sequences. ConSite delivers unparalleled performance using a novel database of high-quality binding models for metazoan transcription factors. With a dynamic interface, this bioinformatics tool provides broad access to promoter analysis with phylogenetic footprinting.

Algorithms↗

PubMed2002

Super pairwise alignment (SPA): an efficient approach to global alignment for homologous sequences.

Sequence analysis is the basis of bioinformatics, while sequence alignment is a fundamental task for sequence analysis. The widely used alignment algorithm, Dynamic Programming, though generating optimal alignment, takes too much time due to its high computation complexity O(N(2)). In order to reduce computation complexity without sacrificing too much accuracy, we have developed a new approach to align two homologous sequences. The new approach presented here, adopting our novel algorithm which combines the methods of probabilistic and combinatorial analysis, reduces the computation complexity to as low as O(N). The computation speed by our program is at least 15 times faster than traditional pairwise alignment algorithms without a loss of much accuracy. We hence named the algorithm Super Pairwise Alignment (SPA). The pairwise alignment execution program based on SPA and the detailed results of the aligned sequences discussed in this article are available upon request.

Algorithms↗

PubMed2005

Bioinformatics and functional magnetic resonance imaging in clinical populations: practical aspects of data collection, analysis, interpretation, and management.

In this paper the authors review the issues associated with bioinformatics and functional magnetic resonance (fMR) imaging in the context of neurosurgery. They discuss the practical aspects of data collection, analysis, interpretation, and the management of large data sets, and they consider the challenges involved in the adoption of fMR imaging into clinical neurosurgical practice. Their goal is to provide neurosurgeons and other clinicians with a better understanding of some of the current issues associated with bioinformatics or neuroinformatics and fMR imaging. Thousands to tens of thousands of images are typically acquired during an fMR imaging session. It is essential to follow an activation task paradigm exactly to obtain an accurate representation of cortical activation. These images are then interactively postprocessed offline to produce an activation map, or in some cases a series of maps. The maps may then be viewed and interpreted in consultation with a neurosurgeon and/or other clinicians. After this consultation, long-term archiving of the processed fMR activation maps along with the standard structural MR images is a complex but necessary final step in this process. The fMR modality represents a valuable tool in the neurosurgical planning process that is still in the developmental stages for routine clinical use, but holds exceptional promise for patient care.

Brain Mapping↗

PubMed2002

Biological data becomes computer literate: new advances in bioinformatics.

Bioinformatics is an art and science concerned with the use of computing in biological research areas such as genomics, transcriptomics, proteomics, genetics, and evolution. This review paints a broad picture of bioinformatics, drawing examples from genomic sequencing and microarray analysis. I highlight the role of bioinformatics at multiple points along the path from high-tech data generation to biological discovery.

Computational Biology↗

PubMed2005

Microarray and bioinformatic detection of novel and established genes expressed in experimental anti-Thy1 nephritis.

BACKGROUND: Microarray technology is a powerful tool that can probe the molecular pathogenesis of renal injury. In this present study microarray analysis was used to monitor serial changes in the renal transcriptome of a rat model of mesangial proliferative glomerulonephritis. Administration of anti-Thy1 antibody results in phases of acute mesangial injury (day 2), cell proliferation (day 5), matrix expansion (days 5 and 7), and subsequent healing (day 14). METHODS: Using Affymetrix (RAE230A) microarrays coupled with sequential primary biologic function-focused and secondary "baited" global cluster analysis, a cohort of established and putative novel modulators of mesangial cell turnover was identified. RESULTS: Cluster analysis of proliferative genes identified a number of gene expression profiles. The most striking pattern was increased gene expression at day 5, a cluster that included platelet-derived growth factor (PDGF), cyclins and transforming growth factor-beta (TGF-beta). The gene expression patterns identified by primary focused cluster analysis were used as bioinformatic bait and resulted in the identification of novel families of genes such as the S100 family. The expression of established and novel genes was confirmed using reverse transcription-polymerase chain reaction (RT-PCR). Next, in vivo gene expression was compared to PDGF-stimulated mesangial cells in vitro revealing similar patterns of dysregulation. CONCLUSION: Transcriptomic analysis defined both known and novel molecules involved in mesangial cell proliferation in vitro and in vivo and defined a panel of molecules that are potential contributors to mesangial cell dysfunction in glomerular disease.

Animals↗

PubMed2025

SpectroPipeR-a streamlining post Spectronaut® DIA-MS data analysis R package.

SUMMARY: Proteome studies frequently encounter challenges in down-stream data analysis due to limited bioinformatics resources, rapid data generation, and variations in analytical methods. To address these issues, we developed SpectroPipeR, an R package designed to streamline data analysis tasks and provide a comprehensive, standardized pipeline for Spectronaut® DIA-MS data. This novel package automates various analytical processes, including XIC plots, ID rate summary, normalization, batch and covariate adjustment, relative protein quantification, multivariate analysis, and statistical analysis, while generating interactive HTML reports for e.g. ELN systems. AVAILABILITY AND IMPLEMENTATION: The SpectroPipeR package (manual: https://stemicha.github.io/SpectroPipeR/) was written in R and is freely available on GitHub (https://github.com/stemicha/SpectroPipeR).

Software↗

PubMed2004

Bioinformatics in reproductive biology--functional annotation based on comparative sequence analysis.

Recent studies of the genomes of a variety of model organisms have provided an unprecedented opportunity to identify and characterize all signaling molecules in the human genome. Regardless of the approaches used to decipher gene characteristics and their role in physiology, pairwise sequence comparison represents the fundamental bioinformatic tool for initial functional annotation of newly identified genes. Because genes evolved from duplication and adapted to different evolutionary niches for each organism during speciation, detailed sequence analysis could provide additional information on the biochemical and biological characteristics of novel genes. In addition, the integration of sequence-based gene discovery with phylogeny-based function prediction leads to a more complete understanding of the signaling pathways. For example, detailed pairwise sequence analysis has led to the identification of (1) stresscopin (SCP) and stresscopin-related peptides (SRP) as the CRH-related genes, (2) multiple relaxin-like factor genes, and (3) the novel glycoprotein hormone subunit family genes, alpha2 and beta5. Furthermore, based on the understanding that ligands and receptors coevolved during evolution, we have identified a variety of novel extracellular signaling polypeptides including (1) stresscopin and stresscopin-related peptides as selective ligands for the type 2 CRH receptor, (2) the pregnancy hormone, relaxin, and related peptides that activate two orphan G protein-coupled receptors (GPCRs), LGR7 and LGR8, and (3) alpha2 and beta5 that form a heterodimer capable of activating the TSH receptor. Thus, detailed studies on the characteristics and evolution of gene sequences have provided an inroad to the elucidation of novel signaling polypeptides and the associated signal transduction pathways.

Animals↗

PubMed2003

A bioinformatic approach to the identification of candidate genes for the development of new cancer diagnostics.

A multivariate analysis of the National Cancer Institute gene expression database is reported here. The soft independent modelling of a class analogy approach achieved cell line classification according to histological origin. With the PCA method, based on the expression of 9605 genes and ESTs, classification of colon, leukaemia, renal, melanoma and CNS cells could be performed, but not of lung, breast and ovarian cells. Another multivariate procedure, called partial least squares discriminant analysis (PLS-DA), provides bioinformatic clues for the selection of a limited number of gene transcripts most effective in discriminating different tumoral histotypes. Among them it is possible to identify candidates in the development of new diagnostic tests for cancer detection and unknown genes deserving high priority in further studies. In particular, melan-A, acid phosphatase 5, dopachrome tautomerase, S100-beta and acid ceramidase were found to be among the most important genes for melanoma. The potential of the present bioinformatic approach is exemplified by its ability to identify differentiation and diagnostic markers already in use in clinical settings, such as protein S-100, a prognostic parameter in patients with metastatic melanoma and a screening marker for melanoma metastasis.

Biomarkers, Tumor↗