PubMed Health⌕ Search

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.

At least 937 records · Page 52Linked to original sources
PubMed2005

5th HUPO BPP Bioinformatics Meeting at the European Bioinformatics Institute in Hinxton, UK--Setting the analysis frame.

The Bioinformatics Committee of the HUPO Brain Proteome Project (HUPO BPP) meets regularly to execute the post-lab analyses of the data produced in the HUPO BPP pilot studies. On July 7, 2005 the members came together for the 5th time at the European Bioinformatics Institute (EBI) in Hinxton, UK, hosted by Rolf Apweiler. As a main result, the parameter set of the semi-automated data re-analysis of MS/MS spectra has been elaborated and the subsequent work steps have been defined.

Computational Biology↗
PubMed2004

A bioinformatics-based functional analysis shows that the specifically androgen-regulated gene SARG contains an active direct repeat androgen response element in the first intron.

We characterized the specifically androgen-regulated gene (SARG), which is expressed in the androgen receptor (AR) and glucocorticoid receptor (GR) positive cell line lymph node carcinoma of the prostate-1F5 (LNCaP-1F5). SARG mRNA expression can be up-regulated by androgens, but not by glucocorticoids. SARG mRNA expression is high in prostate tissue. SARG is composed of four exons and spans a region of 14.5 kbp on chromosome 1q32.2. Transcripts of 5.5, 3.3 and 2.3 kb are the result of alternative polyadenylation. SARG mRNA splice variants lack exon 2 and vary in length of exon 1. The SARG protein has a length of 601 amino acids and is located in the cytoplasm. By screening the 18 kbp genomic sequence flanking the transcription start site we identified the imperfect direct repeat 5'-TGTGCTaacTGTTCT-3'in intron 1 as an active androgen response element (ARE-SARG+4.6). A 569 bp genomic DNA fragment containing this element functioned as an androgen-specific enhancer in transiently transfected LNCaP-1F5 cells. ARE-SARG+4.6 cooperated with flanking sequences for optimal activity. Inactivation of ARE-SARG+4.6 completely abolished the androgen response of the enhancer. Chromatin immunoprecipitation (ChIP) experiments showed chromatin structural changes of the enhancer in the presence of R1881. ARE-SARG+4.6 was able to bind to the androgen receptor, but not to the glucocorticoid receptor, correlating with its androgen-specific activity in transfections.

Alternative Splicing↗
PubMed2026

Overexpression of TCF7L2 promotes the viability and migration of MHCC-97H human hepatocellular carcinoma cells by upregulating MT-ND4L.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly aggressive cancer with high metabolic adaptability. TCF7L2, a transcription factor implicated in type 2 diabetes and cancer, is overexpressed in HCC. However, its specific role in HCC metabolic reprogramming is not well defined. We aimed to elucidate the previously unrecognized molecular mechanisms through which TCF7L2 impacts HCC progression. METHODS: To investigate the function of TCF7L2, a stable MHCC-97H cell line with TCF7L2 overexpression was established via lentiviral transduction. Cell viability and migration were assessed by Cell Counting Kit-8 (CCK-8) and Transwell assays. Transcriptomic profiling [RNA sequencing (RNA-seq)] was performed to identify differentially expressed genes (DEGs). Functional enrichment analysis [Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA)] and bioinformatics promoter analysis (the JASPAR CORE database) were conducted. Clinical correlations, survival analysis, and tumor microenvironment (TME) interrogation were performed using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and single-cell datasets [Human Protein Atlas (HPA), CellChat]. Drug sensitivity was predicted via the Genomics of Drug Sensitivity in Cancer (GDSC) database. RESULTS: TCF7L2 overexpression significantly promoted HCC cell proliferation and migration. Transcriptomic analysis revealed that TCF7L2 drives a profound metabolic shift, with key enrichments in lipid homeostasis, fatty acid β-oxidation, and the PI3K/Akt pathway. Mechanistically, TCF7L2 directly binds to the promoter of CPT1A, the rate-limiting enzyme of fatty acid oxidation, and indirectly upregulates the mitochondrial gene MT-ND4Lvia a strong positive correlation with the mitochondrial transcription factor TFAM. In clinical cohorts, TCF7L2 was overexpressed in HCC and its expression correlated positively with MT-ND4L, MKI67, and SNAI1, and served as a predictor of poor overall survival (OS). Furthermore, TCF7L2-high tumors were enriched in hepatic progenitor cell (HPC)-like niches, mediated by enhanced ANGPTL4 signaling. High TCF7L2 expression predicted increased sensitivity to PI3K/mTOR pathway inhibitors. CONCLUSIONS: TCF7L2 acts as a master metabolic regulator in HCC, coordinating lipid catabolism and mitochondrial biogenesis to drive aggressive tumor behavior. It further remodels the TME towards an HPC-like state and predicts sensitivity to metabolic-targeted therapies. These findings identify TCF7L2 as a key prognostic biomarker and a promising therapeutic target.

MHCC-97H hepatocellular carcinoma cells (MHCC-97H ↗
PubMed2026

Integrated bioinformatics and SEM analysis reveal GPAM as a key mediator of fibrosis in NAFLD with metabolic dysfunction.

Nonalcoholic fatty liver disease (NAFLD) is a complex condition influenced by metabolic and genetic factors, yet the shared genetic architecture underlying its progression remains poorly understood. The aim of this study was to employ genomic structural equation modeling (GSEM) to elucidate the genetic architecture linking NAFLD with key metabolic traits-including insulin resistance, body mass index (BMI), hemoglobin A1c (HbA1c), and liver fibrosis using summary statistics from large-scale genome-wide association studies. By harmonizing 2.18 million variants across five genome-wide association studies (GWAS) datasets, we identified 134 genome-wide significant loci that mapped to 24 genes. GSEM revealed a latent genetic structure composed of two distinct dimensions: a metabolic regulation factor primarily driven by insulin resistance, BMI, and HbA1c; and a structural pathology factor specifically associated with liver fibrosis. These factors explained 65.5% and 78.1% of the genetic variance in BMI and fibrosis, respectively, with minimal correlation (rg = 0:07), indicating their genetic distinctness. Additionally, integrating Mendelian randomization with liver transcriptome profiling, we characterized how the 24 genes contribute to disease and identified mitochondrial glycerol-3-phosphate acyltransferase (GPAM) as the key gene that causally links lipid metabolism to fibrogenesis. In conclusion, we present the first genetically grounded mechanism for the progression of NAFLD to fibrosis. This mechanism encompasssses genetic variants, dysregulated gene expression, metabolic disturbances, and the processes involved in fibrotic remodeling. This research establishes a genetic framework for understanding the pathogenesis of NAFLD and highlights novel therapeutic targets for intervention.

Non-alcoholic Fatty Liver Disease↗
PubMed2005

Applying instructional design theories to bioinformatics education in microarray analysis and primer design workshops.

The need to support bioinformatics training has been widely recognized by scientists, industry, and government institutions. However, the discussion of instructional methods for teaching bioinformatics is only beginning. Here we report on a systematic attempt to design two bioinformatics workshops for graduate biology students on the basis of Gagne's Conditions of Learning instructional design theory. This theory, although first published in the early 1970s, is still fundamental in instructional design and instructional technology. First, top-level as well as prerequisite learning objectives for a microarray analysis workshop and a primer design workshop were defined. Then a hierarchy of objectives for each workshop was created. Hands-on tutorials were designed to meet these objectives. Finally, events of learning proposed by Gagne's theory were incorporated into the hands-on tutorials. The resultant manuals were tested on a small number of trainees, revised, and applied in 1-day bioinformatics workshops. Based on this experience and on observations made during the workshops, we conclude that Gagne's Conditions of Learning instructional design theory provides a useful framework for developing bioinformatics training, but may not be optimal as a method for teaching it.

Computational Biology↗
PubMed2006

Beyond Mfold: recent advances in RNA bioinformatics.

Computational analysis of RNA secondary structure is a classical field of biosequence analysis, which has recently gained momentum due to the manyfold regulatory functions of RNA that have become apparent. We present five recent computational approaches that address the problems of synoptic folding space analysis, pseudoknot prediction, structure alignment, comparative structure prediction, and miRNA target prediction. All these programs are in current use and are available via the Bielefeld Bioinformatics Server at .

Animals↗
PubMed2006

Advanced molecular profiling in vivo detects novel function of dickkopf-3 in the regulation of bone formation.

UNLABELLED: A bioinformatics-based analysis of endochondral bone formation model detected several genes upregulated in this process. Among these genes the dickkopf homolog 3 (Dkk3) was upregulated and further studies showed that its expression affects in vitro and in vivo osteogenesis. This study indicates a possible role of Dkk3 in regulating bone formation. INTRODUCTION: Endochondral bone formation is a complex biological process involving numerous chondrogenic, osteogenic, and angiogenic proteins, only some of which have been well studied. Additional key genes may have important roles as well. We hypothesized that to identify key genes and signaling pathways crucial for bone formation, a comprehensive gene discovery strategy should be applied to an established in vivo model of osteogenesis. MATERIALS AND METHODS: We used in vivo implanted C3H10T1/2 cells that had been genetically engineered to express human bone morphogenetic protein-2 (BMP2) in a tetracycline-regulated system that controls osteogenic differentiation. Oligonucleotide microarray data from the implants (n = 4 repeats) was analyzed using coupled two-way clustering (CTWC) and statistical methods. For studying the effects of dickkopf homolog 3 (Dkk3) in chondrogenesis and osteogenesis, C3H10T1/2 mesenchymal progenitors were used. RESULTS: The CTWC revealed temporal expression of Dkk3 with other chondrogenesis-, osteogenesis-, and Wnt-related genes. Quantitative RT-PCR confirmed the expression of Dkk3 in the implants. C3H10T1/2 cells that expressed Dkk3 in the presence of BMP2 displayed lower levels of alkaline phosphatase and collagen I mRNA expression than control C3H10T1/2 cells that did not express Dkk3. Interestingly, the levels of collagen II mRNA expression, Alcian blue staining, and glucose aminoglycans (GAGs) production were not influenced by Dkk3 expression. In vivo microCT and bioluminescence imaging revealed that co-expression of Dkk3 and BMP2 by implanted C3H10T1/2 cells induced the formation of significantly lower quantities of bone than cells expressing only BMP2. CONCLUSIONS: A bioinformatics analysis enabled the identification of Dkk3 as a pivotal gene with a novel function in endochondral bone formation. Our results showed that Dkk3 might have inhibitory effects on osteogenesis, but no effect on chondrogenesis, indicating that Dkk3 plays a regulatory role in endochondral bone formation. Further mechanistic studies are required to reveal the mechanism of action of Dkk3 in endochondral bone formation.

Adaptor Proteins, Signal Transducing↗
PubMed2002

Bioinformatics methods for the analysis of expression arrays: data clustering and information extraction.

Expression arrays facilitate the monitoring of changes in the expression patterns of large collections of genes. The analysis of expression array data has become a computationally-intensive task that requires the development of bioinformatics technology for a number of key stages in the process, such as image analysis, database storage, gene clustering and information extraction. Here, we review the current trends in each of these areas, with particular emphasis on the development of the related technology being carried out within our groups.

Abstracting and Indexing↗
PubMed2004

The bioinformatics challenges in comparative analysis of cereal genomes-an overview.

Comparative genomic analysis is the cornerstone of in silico-based approaches to understanding biological systems and processes across cereal species, such as rice, wheat and barley, in order to identify genes of agronomic interest. The size of the genomic repositories is nearly doubling every year, and this has significant implications on the way bioinformatics analyses are carried out. In this overview the concepts and technology underpinning bioinformatics as applied to comparative genomic analysis are considered in the context of other manuscripts appearing in this issue of Functional and Integrative Genomics.

Computational Biology↗
PubMed2002

Combining structural and bioinformatics methods for the analysis of functionally important residues in DNA glycosylases.

An essential function of DNA glycosylases is the recognition and excision of damaged bases in DNA, thereby preserving genomic integrity. Lesion recognition is a multistep process, which is only partially revealed by structural analysis of the catalytically competent complex. The functional role of additional residues can be predicted by combining structural data with analysis of amino acid conservation. The following postulate underlies this approach: if a family or superfamily can be broken into subgroups with different substrate specificities, residues highly conserved between these subgroups represent those important for enzyme catalysis and structure maintenance while residues highly conserved within a subgroup but not between subgroups represent residues important for substrate specificity. We review the bioinformatics approach used for this quantitative analysis and describe its application to the Nth superfamily and Fpg family of DNA glycosylases. These results serve as a starting point in planning site-directed mutagenesis experiments to elucidate the functional role of similar and dissimilar residues in DNA repair and other proteins.

Amino Acid Sequence↗
PubMed2007

DiscoverySpace: an interactive data analysis application.

DiscoverySpace is a graphical application for bioinformatics data analysis. Users can seamlessly traverse references between biological databases and draw together annotations in an intuitive tabular interface. Datasets can be compared using a suite of novel tools to aid in the identification of significant patterns. DiscoverySpace is of broad utility and its particular strength is in the analysis of serial analysis of gene expression (SAGE) data. The application is freely available online.

Animals↗
PubMed2006

LegumeDB1 bioinformatics resource: comparative genomic analysis and novel cross-genera marker identification in lupin and pasture legume species.

The identification of markers in legume pasture crops, which can be associated with traits such as protein and lipid production, disease resistance, and reduced pod shattering, is generally accepted as an important strategy for improving the agronomic performance of these crops. It has been demonstrated that many quantitative trait loci (QTLs) identified in one species can be found in other plant species. Detailed legume comparative genomic analyses can characterize the genome organization between model legume species (e.g., Medicago truncatula, Lotus japonicus) and economically important crops such as soybean (Glycine max), pea (Pisum sativum), chickpea (Cicer arietinum), and lupin (Lupinus angustifolius), thereby identifying candidate gene markers that can be used to track QTLs in lupin and pasture legume breeding. LegumeDB is a Web-based bioinformatics resource for legume researchers. LegumeDB analysis of Medicago truncatula expressed sequence tags (ESTs) has identified novel simple sequence repeat (SSR) markers (16 tested), some of which have been putatively linked to symbiosome membrane proteins in root nodules and cell-wall proteins important in plant-pathogen defence mechanisms. These novel markers by preliminary PCR assays have been detected in Medicago truncatula and detected in at least one other legume species, Lotus japonicus, Glycine max, Cicer arietinum, and (or) Lupinus angustifolius (15/16 tested). Ongoing research has validated some of these markers to map them in a range of legume species that can then be used to compile composite genetic and physical maps. In this paper, we outline the features and capabilities of LegumeDB as an interactive application that provides legume genetic and physical comparative maps, and the efficient feature identification and annotation of the vast tracks of model legume sequences for convenient data integration and visualization. LegumeDB has been used to identify potential novel cross-genera polymorphic legume markers that map to agronomic traits, supporting the accelerated identification of molecular genetic factors underpinning important agronomic attributes in lupin.

Chromosome Mapping↗
PubMed2004

Applying task analysis to describe and facilitate bioinformatics tasks.

OBJECTIVE: To document bioinformatics tasks currently per-formed by researchers in genomics and proteomics in an effort to recognize unmet informatics needs and challenges, identify system features that would enhance the performance of those tasks, and inform the development of new bioinformatics tools. DESIGN: A cross-sectional study of bioinformatics tasks performed by OHSU investigators involved in genomics and proteomics research was conducted using task analysis techniques. RESULTS: Four major categories emerged from 22 bioinformatics tasks reported by 6 research laboratories. These were: 1) gene analysis, 2) protein analysis, 3) biostatistical analysis, and 4) literature searching. Analysis of the data also raised the following challenging issues: 1) lack of procedural documentation, 2) use of home-grown strategies to accomplish goals, 3) individual needs and preferences, and 4) lack of awareness of existing bioinformatics tools. CONCLUSION: Task analysis was effective at documenting bioinformatics tasks performed by researchers in the fields of genomics and proteomics, at identifying potentially desirable system features and useful bioinformatics tools, and at providing a better understanding of some of the unmet needs and challenges faced by these researchers.

Computational Biology↗
PubMed2004

Development of an expressed sequence tag (EST) resource for wheat (Triticum aestivum L.): EST generation, unigene analysis, probe selection and bioinformatics for a 16,000-locus bin-delineated map.

This report describes the rationale, approaches, organization, and resource development leading to a large-scale deletion bin map of the hexaploid (2n = 6x = 42) wheat genome (Triticum aestivum L.). Accompanying reports in this issue detail results from chromosome bin-mapping of expressed sequence tags (ESTs) representing genes onto the seven homoeologous chromosome groups and a global analysis of the entire mapped wheat EST data set. Among the resources developed were the first extensive public wheat EST collection (113,220 ESTs). Described are protocols for sequencing, sequence processing, EST nomenclature, and the assembly of ESTs into contigs. These contigs plus singletons (unassembled ESTs) were used for selection of distinct sequence motif unigenes. Selected ESTs were rearrayed, validated by 5' and 3' sequencing, and amplified for probing a series of wheat aneuploid and deletion stocks. Images and data for all Southern hybridizations were deposited in databases and were used by the coordinators for each of the seven homoeologous chromosome groups to validate the mapping results. Results from this project have established the foundation for future developments in wheat genomics.

Blotting, Southern↗
PubMed2005

Computational analysis of protein tyrosine phosphatases: practical guide to bioinformatics and data resources.

The exponential growth of sequence data has become a challenge to database curators and end-users alike and biologists seeking to utilize the data effectively are faced with numerous analysis methods. Here, with practical examples from our bioinformatics analysis of the protein tyrosine phosphatases (PTPs), we show how computational analysis can be exploited to fuel hypothesis-driven experimental research through the exploration of online databases. We cover the following elements: (i) similarity searches and strategies to collect a non-redundant database of tyrosine-specific PTP domains; (ii) utilization of this database to classify human, fly, and worm PTPs (based on alignments and phylogenetic analysis); (iii) three-dimensional structural analysis to identify conserved regions (structure-function) and non-conserved selectivity-determining regions (substrate specificity); and (iv) genomic analysis, including mapping of exon structure, identification of pseudogenes, and exploration of disease databases. We discuss the importance of manual curation, illustrating examples in which pseudogenes give rise to predicted proteins in GenBank and note that domain servers, such as PFAM and SMART, erroneously include dual-specificity and lipid phosphatases in their collection of tyrosine-specific PTPs. To capitalize on our annotated set of 402 PTP domains (from 47 species and five phyla), we identify sequence conservation across taxonomic categories and explore structure-function relationships among tandem domain receptor-like PTPs. We define three Src homology 2 domain-containing PTP genes in stingray, zebrafish, and fugu and speculate on their evolutionary relationship with human pseudogenes. Our annotated sequences, along with a web service for phylogenetic classification of PTP domains, are available online (http://ptp.cshl.edu and http://science.novonordisk.com/ptp).

Amino Acid Sequence↗
PubMed2001

Bioinformatic tools for DNA/protein sequence analysis, functional assignment of genes and protein classification.

The development of efficient DNA sequencing methods has led to the achievement of the DNA sequence of entire genomes from (to date) 55 prokaryotes, 5 eukaryotic organisms and 10 eukaryotic chromosomes. Thus, an enormous amount of DNA sequence data is available and even more will be forthcoming in the near future. Analysis of this overwhelming amount of data requires bioinformatic tools in order to identify genes that encode functional proteins or RNA. This is an important task, considering that even in the well-studied Escherichia coli more than 30% of the identified open reading frames are hypothetical genes. Future challenges of genome sequence analysis will include the understanding of gene regulation and metabolic pathway reconstruction including DNA chip technology, which holds tremendous potential for biomedicine and the biotechnological production of valuable compounds. The overwhelming volume of information often confuses scientists. This review intends to provide a guide to choosing the most efficient way to analyze a new sequence or to collect information on a gene or protein of interest by applying current publicly available databases and Web services. Recently developed tools that allow functional assignment of genes, mainly based on sequence similarity of the deduced amino acid sequence, using the currently available and increasing biological databases will be discussed.

Computational Biology↗