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PubMed2003

Informatics and quantitative analysis in biological imaging.

Biological imaging is now a quantitative technique for probing cellular structure and dynamics and is increasingly used for cell-based screens. However, the bioinformatics tools required for hypothesis-driven analysis of digital images are still immature. We are developing the Open Microscopy Environment (OME) as an informatics solution for the storage and analysis of optical microscope image data. OME aims to automate image analysis, modeling, and mining of large sets of images and specifies a flexible data model, a relational database, and an XML-encoded file standard that is usable by potentially any software tool. With this design, OME provides a first step toward biological image informatics.

Algorithms↗

PubMed2026

Molecular profiling of coronary stent testenosis: A systematic review and functional analysis of implicated genes.

BACKGROUND: Coronary stent restenosis occurs in approximately 5% of patients treated with drug-eluting stents (DES) and is associated with adverse clinical outcomes. Elucidating the genetic mechanisms underlying restenosis may support precision medicine approaches to improve patient management.This systematic review aimed to synthesize evidence on genes and biological pathways associated with DES-related restenosis and to perform functional analysis of the implicated genes using bioinformatics tools. METHODS: The review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines. A systematic search of PubMed, Scopus, and Web of Science was performed for human studies investigating genetic or genomic factors in coronary restenosis, with the last search conducted in March 2024. Eligibility criteria included original studies reporting genetic associations with DES restenosis. Screening and data extraction were performed by a single reviewer. Identified genes underwent gene set enrichment analysis using Enrichr (Ma'ayan Laboratory, Computational Systems Biology) and ClueGo extension on Cytoscape (National Resource for Network Biology). RESULTS: Seventeen studies met the inclusion criteria. The studies highlighted multiple genes involved in extracellular matrix remodeling, inflammatory signaling, and the renin-angiotensin system. Gene enrichment analysis confirmed the overrepresentation of these biological pathways in DES-associated restenosis. CONCLUSIONS: This systematic review synthesizes the genetic and molecular contributors to DES-associated restenosis and identifies potential targets for future research and personalized therapies. No external funding was received, and the protocol was not registered.

Humans↗

PubMed2005

Osteo-Promoter Database (OPD) -- promoter analysis in skeletal cells.

BACKGROUND: Increasing our knowledge about the complex expression of genes in skeletal tissue will provide a better understanding of the physiology of skeletal cells. The study summarizes transcriptional regulation factors interacting and cooperating at promoter regions that regulate gene expression. Specifically, we analyzed A/T rich elements along the promoter sequences. DESCRIPTION: The Osteo-Promoter Database (OPD) is a collection of genes and promoters expressed in skeletal cells. We have compiled a new viewer, OPD, as unique database developed and created as an accessible tool for skeletal promoter sequences. OPD can navigate to identify genes specific to skeletal cDNA databases and promoter analysis sites. OPD offers exclusive access to facilitate a dynamic extraction of promoters' gene-specific analyses in skeletal tissue. The data on promoters included in OPD contains cloned promoters or predicted promoters that were analyzed by bioinformatics tools. OPD offers MAR-analysis, which allocates A/T rich elements along these promoter sequences. CONCLUSION: The analysis leads to a better insight of proteins that bind to DNA, regulate DNA, and function in chromatin remodeling. The OPD is a distinctive tool for understanding the complex function of chromatin remodeling and transcriptional regulation of specific gene expression in skeletal tissue.

Bone and Bones↗

PubMed2006

Bioinformatics and cancer: an essential alliance.

Modern research in cancer has been revolutionized by the introduction of new high-throughput methodologies such as DNA microarrays. Keeping the pace with these technologies, the bioinformatics offer new solutions for data analysis and, what is more important, it permits to formulate a new class of hypothesis inspired in systems biology, more oriented to blocks of functionally-related genes. Although software implementations for this new methodologies is new there are some options already available. Bioinformatic solutions for other high-throughput techniques such as array-CGH of large-scale genotyping is also revised.

Chromosome Aberrations↗

PubMed2005

The study of G-protein coupled receptor oligomerization with computational modeling and bioinformatics.

To achieve a structural context for the analysis of G-protein coupled receptor (GPCR) oligomers, molecular modeling must be used to predict the corresponding interaction interfaces. The task is complicated by the paucity of detailed structural data at atomic resolution, and the large number of possible modes in which the bundles of seven transmembrane (TM) segments of the interacting GPCR monomers can be packed together into dimers and/or higher-order oligomers. Approaches and tools offered by bioinformatics can be used to reduce the complexity of this task and, combined with computational modeling, can serve to yield testable predictions for the structural properties of oligomers. Most of the bioinformatics methods take advantage of the evolutionary relation that exists among GPCRs, as expressed in their sequences and measurable in the common elements of their structural and functional features. These common elements are responsible for the presence of detectable patterns of motifs and correlated mutations evident from the alignment of the sequences of these complex biological systems. The decoding of these patterns in terms of structural and functional determinants can provide indications about the most likely interfaces of dimerization/oligomerization of GPCRs. We review here the main approaches from bioinformatics, enhanced by computational molecular modeling, that have been used to predict likely interfaces of dimerization/oligomerization of GPCRs, and compare results from their application to rhodopsin-like GPCRs. A compilation of the most frequently predicted GPCR oligomerization interfaces points to specific regions of TMs 4-6.

Computational Biology↗

PubMed2006

Gene expression profile exploration of a large dataset on chronic fatigue syndrome.

OBJECTIVE: To gain understanding of the molecular basis of chronic fatigue syndrome (CFS) through gene expression analysis using a large microarray data set in conjunction with clinically administrated questionnaires. METHOD: Data from the Wichita (KS, USA) CFS Surveillance Study was used, comprising 167 participants with two self-report questionnaires (multidimensional fatigue inventory [MFI] and Zung depression scale [Zung]), microarray data, empiric classification, and others. Microarray data was analyzed using bioinformatics tools from ArrayTrack. RESULTS: Correspondence analysis was applied to the MFI questionnaire to select the 23 samples having either the most or the least fatigue, and to the Zung questionnaire to select the 26 samples having either the most or least depression; ten samples were common, resulting in a total of 39 samples. The MFI and Zung-based CFS/non-CFS (NF) classifications on the 39 samples were consistent with the empiric classification. Two differentially-expressed gene lists were determined, 188 fatigue-related genes and 164 depression-related genes, which shared 24 common genes and involved 11 common pathways. Principal component analysis based on 24 genes clearly separates 39 samples with respect to their likelihood to be CFS. Most of the 24 genes are not previously reported for CFS, yet their functions are consistent with the prevailing model of CFS, such as immune response, apoptosis, ion channel activity, signal transduction, cell-cell signaling, regulation of cell growth and neuronal activity. Hierarchical cluster analysis was performed based on 24 genes to classify 128 (=167-39) unassigned samples. Several of the 11 identified common pathways are supported by earlier findings for CFS, such as cytokine-cytokine receptor interaction and neuroactive ligand-receptor interaction. Importantly, most of the 11 common pathways are interrelated, suggesting complex biological mechanisms associated with CFS. CONCLUSION: Bioinformatics is critical in this study to select definitive sample groups, analyze gene expression data and gain insight into biological mechanisms. The 24 identified common genes and 11 common pathways could be important in future studies of CFS at the molecular level.

Adult↗

PubMed2005

Bioinformatics toolbox for narrowing rodent quantitative trait loci.

Quantitative trait locus (QTL) analysis is a powerful method for localizing disease genes, but identifying the causal gene remains difficult. Rodent models of disease facilitate QTL gene identification, and causal genes underlying rodent QTL are often associated with the corresponding human diseases. Recently developed bioinformatics methods, including comparative genomics, combined cross analysis, interval-specific and genome-wide haplotype analysis, followed by sequence and expression analysis, each facilitated by public databases, provide new tools for narrowing rodent QTLs. Here we discuss each tool, illustrate its application and generate a bioinformatics strategy for narrowing QTLs. Combining these bioinformatics tools with classical experimental methods should accelerate QTL gene identification.

Animals↗

PubMed2005

Bioinformatics challenges in proteomics.

A little after the genomic revolution had been celebrated, it seemed as if a competition began to found new -omics disciplines that ultimately all have the same goal, the understanding of biological function. There are many similar definitions for proteomics that can be summarized as follows: proteomics is a large-scale study of structure and function of proteins in an organism or cell. Importantly, the proteome is much more variable than the genome through its interactions with the genome and secondary modifications. It differs depending on the tissue and stage in life-cycle. Hence, proteomics is a very diverse discipline that uses a variety of experimental set-ups and targets in order to elucidate function. Its dissociation from other disciplines can only remain artificial. The bioinformatics applied to proteomics are equally varied. In this review we will focus mainly on a few areas of bioinformatics that seem to us as particularly noteworthy or characteristic for proteomics research, for example in 2DE analysis or mass spectrometry. Another important task of bioinformatics is the prediction of functional properties. We will summarize the approaches taken in order to predict protein networks, which are based on the extensive integration of several kinds of -omics data. We will give a short overview of a demanding field in computational biology, the analysis and prediction of protein 3D structures. In order to provide a broader perspective we will close this review with a generalized description of activities and databases in the realm of proteomics.

Animals↗

PubMed2006

Structural analysis of hyperperiodic DNA from Caenorhabditis elegans.

Several bioinformatics studies have identified an unexpected but remarkably prevalent approximately 10 bp periodicity of AA/TT dinucleotides (hyperperiodicity) in certain regions of the Caenorhabditis elegans genome. Although the relevant C.elegans DNA segments share certain sequence characteristics with bent DNAs from other sources (e.g. trypanosome mitochondria), the nematode sequences exhibit a much more extensive and defined hyperperiodicity. Given the presence of hyperperiodic structures in a number of critical C.elegans genes, the physical characteristics of hyperperiodic DNA are of considerable interest. In this work, we demonstrate that several hyperperiodic DNA segments from C.elegans exhibit structural anomalies using high-resolution atomic force microscopy (AFM) and gel electrophoresis. Our quantitative analysis of AFM images reveals that hyperperiodic DNA adopts a significantly smaller mean square end-to-end distance, hence a more compact coil structure, compared with non-periodic DNA of similar length. While molecules remain capable of adopting both bent and straight (rod-like) configurations, indicating that their flexibility is still retained, examination of the local curvatures along the DNA contour length reveals that the decreased mean square end-to-end distance can be attributed to the presence of long-scale intrinsic bending in hyperperiodic DNA. Such bending is not detected in non-periodic DNA. Similar studies of shorter, nucleosome-length DNAs that survived micrococcal nuclease digestion show that sequence hyperperiodicity in short segments can likewise induce strong intrinsic bending. It appears, therefore, that regions of the C.elegans genome display a significant correlation between DNA sequence and unusual mechanical properties.

AT Rich Sequence↗

PubMed2003

cDNA2Genome: a tool for mapping and annotating cDNAs.

BACKGROUND: In the last years several high-throughput cDNA sequencing projects have been funded worldwide with the aim of identifying and characterizing the structure of complete novel human transcripts. However some of these cDNAs are error prone due to frameshifts and stop codon errors caused by low sequence quality, or to cloning of truncated inserts, among other reasons. Therefore, accurate CDS prediction from these sequences first require the identification of potentially problematic cDNAs in order to speed up the posterior annotation process. RESULTS: cDNA2Genome is an application for the automatic high-throughput mapping and characterization of cDNAs. It utilizes current annotation data and the most up to date databases, especially in the case of ESTs and mRNAs in conjunction with a vast number of approaches to gene prediction in order to perform a comprehensive assessment of the cDNA exon-intron structure. The final result of cDNA2Genome is an XML file containing all relevant information obtained in the process. This XML output can easily be used for further analysis such us program pipelines, or the integration of results into databases. The web interface to cDNA2Genome also presents this data in HTML, where the annotation is additionally shown in a graphical form. cDNA2Genome has been implemented under the W3H task framework which allows the combination of bioinformatics tools in tailor-made analysis task flows as well as the sequential or parallel computation of many sequences for large-scale analysis. CONCLUSIONS: cDNA2Genome represents a new versatile and easily extensible approach to the automated mapping and annotation of human cDNAs. The underlying approach allows sequential or parallel computation of sequences for high-throughput analysis of cDNAs.

Chromosome Mapping↗

PubMedDate not supplied

Application of proteomic technologies to cytologic specimens. A review.

With the increasing use of molecular biology techniques in routine pathology practice, it seems reasonable that their application to cytologic specimens will become popular in the near future. Proteomics is a novel area of research that involves the global analysis of tissue proteins using diverse technologies, such as 2-D gel electrophoresis, mass spectrometry and bioinformatics. This review discusses recent applications of proteomic analysis to cytologic specimens as well as its potential in the diagnosis of neoplastic and nonneoplastic disease.

Cytological Techniques↗

PubMed2006

Molecular cloning of a novel cDNA from Mus muscular BALB/c mice encoding glycosyl hydrolase family 1: a homolog of human lactase-phlorizin hydrolase.

OBJECTIVE: To study the mechanism of lactose intolerance (LI) by cloning the mouse lactase cDNA and recombining a vector. METHODS Total murine RNA was isolated from the small intestine of a 4-week-old BALB/c mouse (d). Gene-specific primers were designed and synthesized according to the cDNA sequences of lactase-phlorizin hydrolase (LPH) in human, rat, and rabbit. A coding sequence (CDS) fragment was obtained using RT-PCR, and inserted into a clone vector pNEB-193, then the cDNA was sequenced and analyzed using bioinformatics. RESULTS: The cDNA from the BALB/c mouse with 912 bp encoding 303 amino acid residues. Analysis of the deduced amino acid sequence using bioinformatics revealed that this cDNA shared extensive sequence homology with human LPH containing a conserved glycosyl hydrolase family 1 motif important for regulating lactase intolerance. CONCLUSION: BALB/c mouse LPH cDNA (GenBank accession No: AY751548) provides a necessary foundation for study of the biological function and regulatory mechanism of the lactose intolerance in mice.

Animals↗

PubMedDate not supplied

Phylomat: an automated protein motif analysis tool for phylogenomics.

Recent progress in genomics, proteomics, and bioinformatics enables unprecedented opportunities to examine the evolutionary history of molecular, cellular, and developmental pathways through phylogenomics. Accordingly, we have developed a motif analysis tool for phylogenomics (Phylomat, http://alg.ncsa.uiuc.edu/pmat) that scans predicted proteome sets for proteins containing highly conserved amino acid motifs or domains for in silico analysis of the evolutionary history of these motifs/domains. Phylomat enables the user to download results as full protein or extracted motif/domain sequences from each protein. Tables containing the percent distribution of a motif/domain in organisms normalized to proteome size are displayed. Phylomat can also align the set of full protein or extracted motif/domain sequences and predict a neighbor-joining tree from relative sequence similarity. Together, Phylomat serves as a user-friendly data-mining tool for the phylogenomic analysis of conserved sequence motifs/domains in annotated proteomes from the three domains of life.

Algorithms↗

PubMed2006

Group analysis of regulation of fibroblast genome on low-adhesion nanostructures.

Nanotopographical material modification represents a possible way of producing surfaces that influence cellular adhesion for biomaterials purposes. Here, two low-adhesion surfaces are studied with human genome microarrays (120nm diameter pits produced by electron beam lithography and 11nm high columns produced by colloidal lithography). In order to present the large numbers of results produced in a succinct and easy to understand manner, two types of recent bioinformatics methods were used; iterative group analysis and Ingenuity pathway analysis. These methods allowed the easy comparison of the nanomaterials and showed large-scale changes in areas of extracellular matrix, cell signalling and inflammation. The results demonstrate that whilst modes of cellular response to low-adhesion materials are similar, the more adhesion is reduced, the further 'shut-down' of critical cellular activities is observed. We also feel that the analysis used could be of interest to biomaterials scientists looking for easy ways to display microarray data efficiently.

Adhesiveness↗

PubMedDate not supplied

Differential expression of proteins in response to ceramide-mediated stress signal in colon cancer cells by 2-D gel electrophoresis and MALDI-TOF-MS.

Comparative cancer cell proteome analysis is a strategy to study the implication of ceramides in the transmission of stress signals. To better understand the mechanisms by which ceramide regulate some physiological or pathological events and the response to the pharmacological treatment of cancer, we performed a differential analysis of the proteome of HCT-116 (human colon carcinoma) cells in response to these substances. We first established the first 2-dimensional map of the HCT-116 proteome. Then, HCT116 cell proteome treated or not with C6-ceramide have been compared using two-dimensional electrophoresis, matrix-assisted laser desorption/ionization-mass spectrometry and bioinformatic (genomic databases). 2-DE gel analysis revealed more than fourty proteins that were differentially expressed in control cells and cells treated with ceramide. Among them, we confirmed the differential expression of proteins involved in apoptosis and cell adhesion.

Apoptosis↗

PubMed2001

[Measurement of gene activity by DNA microarrays].

BACKGROUND: DNA microarray is a tool that can be used to measure in one single analysis simultaneous changes in the activity of tens of thousands of genes. MATERIAL AND METHODS: The method is based upon advanced robotic techniques; High-density arrays of DNA probes are placed on a solid surface; this is followed by hybridisation with a fluorescence labelled sample and analysis of fluorescence signals. RESULTS: The analysis create huge data sets which have to be transformed into formats that can be interpreted and correlated with existing knowledge. This means that bioinformatics is an integrated part of microarray analysis. INTERPRETATION: DNA microarray may be used to examine complex physiological and pathological conditions and will most likely be very important in functional studies addressing the structural knowledge of genes obtained through the Human Genome Project. Dedicated microchips are already being tested in the diagnosis of malignant and premalignant diseases and being used to characterize HIV viruses with respect to choice of therapy.

Computational Biology↗

PubMed2003

An overview of data models for the analysis of biochemical pathways.

Biochemical pathways such as metabolic, regulatory or signal transduction pathways can be viewed as interconnected processes forming an intricate network of functional and physical interactions between molecular species in the cell. The amount of information available on such pathways for different organisms is increasing very rapidly. This is offering the possibility of performing various analyses on the structure of the full network of pathways for one organism as well as across different organisms, and has therefore generated interest in developing databases for storing and managing this information. Analysing these networks remains far from straightforward owing to the nature of the databases, which are often heterogeneous, incomplete or inconsistent. Pathway analysis is hence a challenging problem in systems biology and in bioinformatics. Various forms of data models have been devised for the analysis of biochemical pathways. This paper presents an overview of the types of models used for this purpose, concentrating on those concerned with the structural aspects of biochemical networks. In particular, the different types of data models found in the literature are classified using a unified framework. In addition, how these models have been used in the analysis of biochemical networks is described. This enables us to underline the strengths and weaknesses of the different approaches, as well as to highlight relevant future research directions.

Cell Physiological Phenomena↗

PubMed2003

A novel CpG-associated brain-expressed candidate gene for chromosome 18q-linked bipolar disorder.

We previously identified 18q21-q22 as a candidate region for bipolar (BP) disorder and constructed a yeast artificial chromosome (YAC) contig map. Here we identified three potential CpG islands using CCG/CGG YAC fragmentation. Analysis of available genomic sequences using bioinformatic tools identified an exon of 3639 bp downstream of a CpG island of 1.2 kb containing a putative transcription initiation site. The exon contained an open reading frame coding for 1212 amino acids with significant homology to the SART-2 protein; weaker homology was found with a series of sulphotransferases. Alignment of cDNA sequences of corresponding ESTs and RT-PCR sequencing predicted a transcript of 9.5 kb which was confirmed by Northern blot analysis. The transcript was expressed in different brain areas as well as in multiple other peripheral tissues. We performed an extensive mutation analysis in 113 BP patients. A total of nine single nucleotide polymorphisms (SNPs) were identified. Five SNPs predicted an amino acid change, of which two were present in BP patients but not in 163 control individuals.

Amino Acid Substitution↗