[Gene chip technique and associated bioinformatics].
Explore the source record for details and available documents.
Computational Biology↗
SEARCH · PubMed Health
Results for “Bioinformatics analysis”
Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Profiler: an open web platform for multi-omics analysis.
MOTIVATION: High-throughput multi-omics technologies produce increasingly large and heterogeneous datasets that are difficult to analyze without advanced computational expertise. Existing bioinformatics tools are often fragmented or limited to specific omics types, hindering reproducibility and accessibility. There is a critical need for an integrated, user-friendly, and scalable platform capable of supporting multi-omics analyses across different data modalities. RESULTS: We present Profiler, an open-source, modular platform that unifies data import, quality control, preprocessing, statistical testing, machine and deep learning, biomarker discovery, pathway and drug-target enrichment, and survival modeling within a single reproducible environment. Built in Python with Streamlit, Profiler is available as both a web-based platform deployed on high-performance computing and a desktop version for local execution, enabling flexible usage across computational infrastructures. Profiler supports diverse omics modalities, including proteomics, transcriptomics, lipidomics, and electroencephalogram data. Through applications to glioblastoma proteomic, pancancer, and multi-omics datasets, Profiler reproduced known molecular subtypes, revealed potential therapeutic targets, and generated fully traceable analysis reports within minutes. By integrating advanced analytics behind an intuitive interface, Profiler democratizes multi-omics analysis and provides a robust, scalable foundation for systems biology and precision medicine research. AVAILABILITY AND IMPLEMENTATION: Profiler is open-source and freely available via its web platform (https://prism-profiler.univ-lille.fr) and GitHub (web version: https://github.com/yanisZirem/Profiler_v1_requests_datatests, desktop version: https://github.com/yanisZirem/prism-profiler), and archived on Zenodo (DOI: https://doi.org/10.5281/zenodo.17478158).
Software↗
Profiling and comprehensive expression analysis of ABC transporter solute-binding proteins of Bacillus subtilis membrane based on a proteomic approach.
We analyzed ABC transporter solute-binding proteins (SBPs) of the Bacillus subtilis membrane using a proteomic approach. We prepared a washed cell membrane fraction that was insoluble in 134 mM nondetergent sulfobetaine and then extracted proteins using mixtures of detergents in a stepwise manner. The membrane proteins were resolved by three two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) or two one-dimensional (1-D) PAGE procedures, electroblotted, and digested in the presence of 5% or 80% acetonitrile. Thereafter, matrix-assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF MS) identified 637 proteins corresponding to 15.9% of the total cellular proteins. We predicted that among these, 256 were membrane proteins, 101 were lipoproteins or secretory proteins and 280 were soluble proteins containing peripheral proteins that function in both the cytoplasm and the cell membrane such as SecA and FtsY. Among the 637 proteins, we identified 30 SBPs among 38 importers predicted by a bioinformatic search of the genome. We confirmed expression of the genes for the 30 SBPs using DNA microarray analysis. We compared the 2-D gel separation profiles of submembrane fractions solubilized by 1% n-dodecyl-beta-D-maltoside from cells cultured on Luria Bertani (LB), S7, and S7 medium without glutamate as well as DNA microarray data on LB and S7. The results suggested that YcdH, YtmK and YurO are binding proteins for Mn(++), glutamate and glucose, respectively, and that YqiX and YxeM are binding proteins for amino acids (tryptophan in S7 medium).
ATP-Binding Cassette Transporters↗
openSputnik--a database to ESTablish comparative plant genomics using unsaturated sequence collections.
The public expressed sequence tag collections are continually being enriched with high-quality sequences that represent an ever-expanding range of taxonomically diverse plant species. While these sequence collections provide biased insight into the populations of expressed genes available within individual species and their associated tissues, the information is conceivably of wider relevance in a comparative context. When we consider the available expressed sequence tag (EST) collections of summer 2004, most of the major plant taxonomic clades are at least superficially represented. Investigation of the five million available plant ESTs provides a wealth of information that has applications in modelling the routes of plant genome evolution and the identification of lineage-specific genes and gene families. Over four million ESTs from over 50 distinct plant species have been collated within an EST analysis pipeline called openSputnik. The ESTs were resolved down into approximately one million unigene sequences. These have been annotated using orthology-based annotation transfer from reference plant genomes and using a variety of contemporary bioinformatics methods to assign peptide, structural and functional attributes. The openSputnik database is available at http://sputnik.btk.fi.
Cluster Analysis↗
Informatics for mutagenesis: the design of mutabase--a distributed data recording system for animal husbandry, mutagenesis, and phenotypic analysis.
The increasing use of high-throughput methods for the production of biologically important information and the increasing diversity of that information pose considerable bioinformatics challenges. These challenges will be met by implementing electronic data management systems not only to capture the data, but increasingly to provide a platform for data integration and mining as we enter the post-genomic era. We discuss the design and implementation of such a data capture system, 'Mutabase', as a model of how such electronic systems might be designed and implemented. Mutabase was created in support of a large-scale, phenotype-driven mouse mutagenesis program at MRC Mammalian Genetics Unit, Harwell, in collaboration with SmithKline Beecham Pharmaceuticals, Queen Mary and Westfield College, London, and Imperial College of Science, Technology and Medicine, London. The aim of this mutagenesis project is to make a significant contribution to the existing mouse mutant resource, closing the phenotype gap and providing many more models for fundamental research and disease modeling. Mutabase records experimental details at the 'point of generation' and provides a number of dissemination and analysis tools for the experimental data, as well as providing a means of assessing various aspects of progress of the program. Mutabase uses a hypertext-based interface to provide interaction between a number of intranet-based client workstations and a central industrial strength database. Mutabase utilizes a variety of techniques in order to implement the user interface system including Perl/CGI, Java Servlets, and an experimental CORBA server. We discuss the relative merits of these methods in the context of the need to provide sound informatics approaches for the support of systematic mutagenesis programs.
Animal Husbandry↗
Biomic study of human myeloid leukemia cells differentiation to macrophages using DNA array, proteomic, and bioinformatic analytical methods.
A biomic approach by integrating three independent methods, DNA microarray, proteomics and bioinformatics, is used to study the differentiation of human myeloid leukemia cell line HL-60 into macrophages when induced by 12-O-tetradecanoyl-phorbol-13-acetate (TPA). Analysis of gene expression changes at the RNA level using cDNA against an array of 6033 human genes showed that 5950 (98.6%) of the genes were expressed in the HL-60 cells. A total of 624 genes (10.5%) were found to be regulated during HL-60 cell differentiation. Most of these genes have not been previously associated with HL-60 cells and include genes encoded for secreted proteins as well as genes involved in cell adhesion, signaling transduction, and metabolism. Protein analysis using two-dimensional gel electrophoresis showed a total of 682 distinct protein spots; 136 spots (19.9%) exhibited quantitative changes between HL-60 control and macrophages. These differentially expressed proteins were identified by mass spectrometry. We developed a bioinformatics program, the Bulk Gene Search System (BGSS, http://www.sinica.edu.tw:8900/perl/genequery.pl) to search for the functions of genes and proteins identified by cDNA microarrays and proteomics. The identified regulated proteins and genes were classified into seven groups according to subcellular locations and functions. This powerful holistic biomic approach using cDNA microarray, proteomics coupled to bioinformatics can provide in-depth information on the impact and importance of the regulated genes and proteins for HL-60 differentiation.
Cell Differentiation↗
A novel bioinformatic strategy for unveiling hidden genome signatures of eukaryotes: self-organizing map of oligonucleotide frequency.
With the increasing amount of available genome sequences, novel tools are needed for comprehensive analysis of species-specific sequence characteristics for a wide variety of genomes. We used an unsupervised neural network algorithm, Kohonen's self-organizing map (SOM), to analyze di- and trinucleotide frequencies in 9 eukaryotic genomes of known sequences (a total of 1.2 Gb); S. cerevisiae, S. pombe, C. elegans, A. thaliana, D. melanogaster, Fugu, and rice, as well as P. falciparum chromosomes 2 and 3, and human chromosomes 14, 20, 21, and 22, that have been almost completely sequenced. Each genomic sequence with different window sizes was encoded as a 16- and 64-dimensional vector giving relative frequencies of di- and trinucleotides, respectively. From analysis of a total of 120,000 nonoverlapping 10-kb sequences and overlapping 100-kb sequences with a moving step size of 10 kb, derived from a total of the 1.2 Gb genomic sequences, clear species-specific separations of most sequences were obtained with the SOMs. The unsupervised algorithm could recognize, in most of the 120,000 10-kb sequences, the species-specific characteristics (key combinations of oligonucleotide frequencies) that are signature representations of each genome. Because the classification power is very high, the SOMs can provide fundamental bioinformatic strategies for extracting a wide range of genomic information that could not otherwise be obtained.
Animals↗
Cytomics, the human cytome project and systems biology: top-down resolution of the molecular biocomplexity of organisms by single cell analysis.
A large amount of structural and functional information is obtained by molecular cell phenotype analysis of tissues, organs and organisms at the single cell level by image or flow cytometry in combination with bioinformatic knowledge extraction (cytomics) concerning nuclei acids, proteins and metabolites (cellular genomics, proteomics and metabolomics) as well as cell function parameters like intracellular pH, transmembrane potentials or ion gradients. In addition, differential molecular cell phenotypes between diseased and healthy cells provide molecular data patterns for (i) predictive medicine by cytomics or for (ii) drug discovery purposes using reverse engineering of the data patterns by biomedical cell systems biology. Molecular pathways can be explored in this way including the detection of suitable target molecules, without detailed a priori knowledge of specific disease mechanisms. This is useful during the analysis of complex diseases such as infections, allergies, rheumatoid diseases, diabetes or malignancies. The top-down approach reaching from single cell heterogeneity in cell systems and tissues down to the molecular level seems suitable for a human cytome project to systematically explore the molecular biocomplexity of human organisms. The analysis of already existing data from scientific studies or routine diagnostic procedures will be of immediate value in clinical medicine, for example as personalized therapy by cytomics.
Cell Biology↗
Bioinformatics and multiepitope DNA immunization to design rational snake antivenom.
BACKGROUND: Snake venom is a potentially lethal and complex mixture of hundreds of functionally diverse proteins that are difficult to purify and hence difficult to characterize. These difficulties have inhibited the development of toxin-targeted therapy, and conventional antivenom is still generated from the sera of horses or sheep immunized with whole venom. Although life-saving, antivenoms contain an immunoglobulin pool of unknown antigen specificity and known redundancy, which necessitates the delivery of large volumes of heterologous immunoglobulin to the envenomed victim, thus increasing the risk of anaphylactoid and serum sickness adverse effects. Here we exploit recent molecular sequence analysis and DNA immunization tools to design more rational toxin-targeted antivenom. METHODS AND FINDINGS: We developed a novel bioinformatic strategy that identified sequences encoding immunogenic and structurally significant epitopes from an expressed sequence tag database of a venom gland cDNA library of Echis ocellatus, the most medically important viper in Africa. Focusing upon snake venom metalloproteinases (SVMPs) that are responsible for the severe and frequently lethal hemorrhage in envenomed victims, we identified seven epitopes that we predicted would be represented in all isomers of this multimeric toxin and that we engineered into a single synthetic multiepitope DNA immunogen (epitope string). We compared the specificity and toxin-neutralizing efficacy of antiserum raised against the string to antisera raised against a single SVMP toxin (or domains) or antiserum raised by conventional (whole venom) immunization protocols. The SVMP string antiserum, as predicted in silico, contained antibody specificities to numerous SVMPs in E. ocellatus venom and venoms of several other African vipers. More significantly, the antiserum cross-specifically neutralized hemorrhage induced by E. ocellatus and Cerastes cerastes cerastes venoms. CONCLUSIONS: These data provide valuable sequence and structure/function information of viper venom hemorrhagins but, more importantly, a new opportunity to design toxin-specific antivenoms-the first major conceptual change in antivenom design after more than a century of production. Furthermore, this approach may be adapted to immunotherapy design in other cases where targets are numerous, diverse, and poorly characterized such as those generated by hypermutation or antigenic variation.
Amino Acid Sequence↗
Plant phosphoproteomics: a long road ahead.
Phosphoproteomics can be defined as the comprehensive study of protein phosphorylation by identification of the phosphoproteins, exact mapping of the phosphorylation sites, quantification of phosphorylation, and eventually, revealing their biological function. Its place in today's research is vitally important to address the most fundamental question - how the phosphorylation events control most, if not all, of the cellular processes in a given organism? Despite the immense importance of phosphorylation, the analysis of phosphoproteins on a proteome-wide scale remains a formidable challenge. Nevertheless, several technologies have been developed, mostly in yeast and mammals, to conduct a large-scale phosphoproteomic study. Some of these technologies have been successfully applied to plants with a few modifications, resulting in documentation of phosphoproteins, phosphorylation site mapping, identification of protein kinase substrates, etc. at the global level. In this review, we summarize in vitro and in vivo approaches for detection and analysis of phosphoproteins including protein kinases and we discuss the importance of phosphoproteomics in understanding plant biology. These approaches along with bioinformatics will help plant researchers to design and apply suitable phosphoproteomic strategies in helping to find answers to their biological questions.
Chromatography↗
Functional proteomics and correlated signaling pathway of the thermophilic bacterium Bacillus stearothermophilus TLS33 under cold-shock stress.
The thermophilic bacterium Bacillus stearothermophilus TLS33 was examined under cold-shock stress by a proteomic approach to gain a better understanding of the protein synthesis and complex regulatory pathways of bacterial adaptation. After downshift in the temperature from 65 degrees C, the optimal growth temperature for this bacterium, to 37 degrees C and 25 degrees C for 2 h, we used the high-throughput techniques of proteomic analysis combining 2-DE and MS to identify 53 individual proteins including differentially expressed proteins. The bioinformatics database was used to search the biological functions of proteins and correlate these with gene homology and metabolic pathways in cell protection and adaptation. Eight cold-shock-induced proteins were shown to have markedly different protein expression: glucosyltransferase, anti-sigma B (sigma(B)) factor, Mrp protein homolog, dihydroorthase, hypothetical transcriptional regulator in FeuA-SigW intergenic region, RibT protein, phosphoadenosine phosphosulfate reductase and prespore-specific transcriptional activator RsfA. Interestingly, six of these cold-shock-induced proteins are correlated with the signal transduction pathway of bacterial sporulation. This study aims to provide a better understanding of the functional adaptation of this bacterium to environmental cold-shock stress.
Amino Acid Sequence↗
Identification and initial characterization of 5000 expressed sequenced tags (ESTs) each from adult human normal and osteoarthritic cartilage cDNA libraries.
OBJECTIVE: To prepare, sequence and analyse adult human cartilage cDNA libraries to study the gene expression pattern between normal and osteoarthritic cartilage. METHODS: Poly A(+)RNA from adult human normal and osteoarthritic articular cartilage was isolated and used to prepare cDNA libraries. Approximately 5000 ESTs from each library were sequenced and analysed using bioinformatic tools. The expression of select genes was confirmed by Northern blot and in situ hybridization analysis. RESULTS: Multiple gene families including several classical cartilage matrix protein encoding genes were identified. Approximately 28-40% of the genes sequenced from these libraries were novel, while half of the genes encoded known proteins and 4-6% of the genes encoded novel homologs of known proteins. Several known genes, whose expression has not been reported previously in cartilage, were also identified. We have confirmed the cartilage expression of three known (CTGF, CTGF-L and clusterin) and two novel homologs of known genes (PCPE-2 and Gal-Nac transferase) by Northern blot and in situ hybridization analysis. CONCLUSION: This is the first report of the preparation and sequencing of cDNA libraries from adult human normal and osteoarthritic articular cartilage. Further analysis of genes identified from these libraries may provide molecular targets for diagnosis and/or treatment of osteoarthritis (OA).
Adult↗
Using CAVE technology for functional genomics studies.
We have established the first Java 3D-enabled CAVE (CAVE automated virtual environment). The Java application programming interface allows the complete separation of the program development from the program execution, opening new application domains for the CAVE technology. Programs can be developed on any Java-enabled computer platform, including Windows, Macintosh, and Linux workstations, and executed in the CAVE without modification. The introduction of Java, one of the major programming environments for bioinformatics, into the CAVE environment allows the rapid development applications for genome research, especially for the analysis of the spatial and temporal data that are being produced by functional genomics experiments. The CAVE technology will play a major role in the modeling of biological systems that is necessary to understand how these systems are organized and how they function.
Automation↗
Unsupervised multiscale clustering of single-cell transcriptomes to identify hierarchical structures of cell subtypes.
BACKGROUND: Cell clustering is an essential step in uncovering cellular architectures in single-cell RNA sequencing (scRNA-seq) data. However, the existing cell clustering approaches are not well designed to dissect complex structures of cellular landscapes at a finer resolution. RESULTS: Here, we develop a multiscale clustering (MSC) approach to construct a sparse cell-cell correlation network for unsupervised identification of de novo cell types and subtypes across multiple resolutions. Based upon simulated silver- and gold-standard data as well as real scRNA-seq data in diseases, MSC demonstrates significantly improved performance compared to established benchmark methods and reveals a biologically meaningful cell hierarchy to facilitate the discovery of novel disease-associated cell subtypes and mechanisms. CONCLUSIONS: We present MSC as a new single-cell multiscale clustering framework as a powerful tool for advancing discoveries in disease-associated cell populations using single-cell sequencing data.
Single-Cell Analysis↗
MAO: a Multiple Alignment Ontology for nucleic acid and protein sequences.
The application of high-throughput techniques such as genomics, proteomics or transcriptomics means that vast amounts of heterogeneous data are now available in the public databases. Bioinformatics is responding to the challenge with new integrated management systems for data collection, validation and analysis. Multiple alignments of genomic and protein sequences provide an ideal environment for the integration of this mass of information. In the context of the sequence family, structural and functional data can be evaluated and propagated from known to unknown sequences. However, effective integration is being hindered by syntactic and semantic differences between the different data resources and the alignment techniques employed. One solution to this problem is the development of an ontology that systematically defines the terms used in a specific domain. Ontologies are used to share data from different resources, to automatically analyse information and to represent domain knowledge for non-experts. Here, we present MAO, a new ontology for multiple alignments of nucleic and protein sequences. MAO is designed to improve interoperation and data sharing between different alignment protocols for the construction of a high quality, reliable multiple alignment in order to facilitate knowledge extraction and the presentation of the most pertinent information to the biologist.
Databases, Genetic↗
Gene Aging Nexus: a web database and data mining platform for microarray data on aging.
The recent development of microarray technology provided unprecedented opportunities to understand the genetic basis of aging. So far, many microarray studies have addressed aging-related expression patterns in multiple organisms and under different conditions. The number of relevant studies continues to increase rapidly. However, efficient exploitation of these vast data is frustrated by the lack of an integrated data mining platform or other unifying bioinformatic resource to enable convenient cross-laboratory searches of array signals. To facilitate the integrative analysis of microarray data on aging, we developed a web database and analysis platform 'Gene Aging Nexus' (GAN) that is freely accessible to the research community to query/analyze/visualize cross-platform and cross-species microarray data on aging. By providing the possibility of integrative microarray analysis, GAN should be useful in building the systems-biology understanding of aging. GAN is accessible at http://gan.usc.edu.
Aging↗
Characterization of a novel porin involved in systemic Yersinia enterocolitica infection.
Yersinia enterocolitica is an enteric pathogen capable of causing systemic disease in a murine model. We have identified a novel protein, systemic factor protein A (SfpA), conserved in other pathogenic bacteria that is involved in systemic disease. Analysis of bacterial colonization revealed that a DeltasfpA strain is defective in mesenteric lymph node colonization. Bioinformatics and functional studies suggest that SfpA is a porin.
Acute Disease↗
SeqVISTA: a graphical tool for sequence feature visualization and comparison.
BACKGROUND: Many readers will sympathize with the following story. You are viewing a gene sequence in Entrez, and you want to find whether it contains a particular sequence motif. You reach for the browser's "find in page" button, but those darn spaces every 10 bp get in the way. And what if the motif is on the opposite strand? Subsequently, your favorite sequence analysis software informs you that there is an interesting feature at position 13982-14013. By painstakingly counting the 10 bp blocks, you are able to examine the sequence at this location. But now you want to see what other features have been annotated close by, and this information is buried several screenfuls higher up the web page. RESULTS: SeqVISTA presents a holistic, graphical view of features annotated on nucleotide or protein sequences. This interactive tool highlights the residues in the sequence that correspond to features chosen by the user, and allows easy searching for sequence motifs or extraction of particular subsequences. SeqVISTA is able to display results from diverse sequence analysis tools in an integrated fashion, and aims to provide much-needed unity to the bioinformatics resources scattered around the Internet. Our viewer may be launched on a GenBank record by a single click of a button installed in the web browser. CONCLUSION: SeqVISTA allows insights to be gained by viewing the totality of sequence annotations and predictions, which may be more revealing than the sum of their parts. SeqVISTA runs on any operating system with a Java 1.4 virtual machine. It is freely available to academic users at http://zlab.bu.edu/SeqVISTA.
Amino Acid Sequence↗