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At least 1,495 records · Page 83Linked to original sources

PubMed2006

Lipopolysaccharide-stimulated responses in rat aortic endothelial cells by a systems biology approach.

The vascular endothelium plays an important role in regulating immune and inflammatory responses to resist pathogens infection. Although it has been known that lipopolysaccharide (LPS) is a critical inducer of sepsis or endotoxemia, the systematic responses of LPS-stimulation in endothelial cells (ECs) are still unclear. The present study aims to analyze the late-phase responses of LPS-induced rat aortic ECs by using systematic biology approaches, including rat cDNA microarray, 2-DE and MALDI-TOF MS/MS, and cytokine protein array. Furthermore, to improve the efficiency of analysis of the bulk systematic data of rat, we designed a set of bioinformatic tools to convert and integrate these rat data into the corresponding human genes or proteins IDs based on BioCarta, KEGG, and Gene Ontology databases. Using the systematic analysis, it was shown that LPS could promote some signaling or metabolic pathways as well as pathophysiologic phenomena of proliferation, atherogenesis, inflammation, and apoptosis through activated nuclear factor-kappaB pathway in ECs. Interestingly, ECs also activated the mediators of anti-inflammation, antiapoptosis, and antioxidation to protect themselves. Moreover, the expressions of altered genes, proteins, and their involvement in the hypothetical signaling pathway can provide further understanding of inflammation associated responses in ECs.

Animals↗

PubMed2000

Healthcare, molecular tools and applied genome research.

Biotechnology 2000 offered a rare opportunity for scientists from academia and industry to present and discuss data in fields as diverse as environmental biotechnology and applied genome research. The healthcare section of the meeting encompassed a number of gene therapy delivery systems that are successfully treating genetic disorders. Beta-thalassemia is being corrected in mice by continous erythropoeitin delivery from engineered muscles cells, and from naked DNA electrotransfer into muscles, as described by Dr JM Heard (Institut Pasteur, Paris, France). Dr Reszka (Max-Delbrueck-Centrum fuer Molekulare Medizin, Berlin, Germany), meanwhile, described a treatment for liver metastasis in the form of a drug carrier emolization system, DCES (Max-Delbrueck-Centrum fuer Molekulare Medizin), composed of surface modified liposomes and a substance for chemo-occlusion, which drastically reduces the blood supply to the tumor and promotes apoptosis, necrosis and antiangiogenesis. In the molecular tools section, Willem Stemmer (Maxygen Inc, Redwood City, CA, USA) gave an insight into the importance that techniques, such as molecular breeding (DNA shuffling), have in the evolution of molecules with improved function, over a range of fields including pharmaceuticals, vaccines, agriculture and chemicals. Technologies, such as ribosome display, which can incorporate the evolution and the specific enrichment of proteins/peptides in cycles of selection, could play an enormous role in the production of novel therapeutics and diagnostics in future years, as explained by Andreas Plückthun (Institute of Biochemistry, University of Zurich, Switzerland). Applied genome research offered technologies, such as the 'in vitro expression cloning', described by Dr Zwick (Promega Corp, Madison, WI, USA), are providing a functional analysis for the overwhelming flow of data emerging from high-throughput sequencing of genomes and from high-density gene expression microarrays (DNA chips). The importance of bioinformatics was stressed throughout the conference. In particular, its applications in the storage, analysis and visualization of data, but also the linkage of databases and data mining tools. It is the storage and linkage that generates insight into disease processes, enabling the nomination of candidate drug targets.

Journal Article↗

PubMed2025

Target and biomarker exploration portal for drug discovery.

MOTIVATION: The discovery of novel drug targets and precision biomarkers remains a major challenge in drug development, with traditional differential expression analysis often overlooking key regulatory proteins. Here, we present a novel, web-based bioinformatics tool, the Target and Biomarker Exploration Portal (TBEP), designed to accelerate the drug discovery process by integrating large-scale biomedical data with network analysis techniques. RESULTS: TBEP harnesses machine-learning approaches to mine and combine multimodal datasets, including human genetics, functional genomics, and protein-protein interaction networks, to decode causal disease mechanisms and uncover novel therapeutic targets and precision biomarkers for specific phenotypes. A unique feature of the tool is its ability to process large-scale data in real-time, facilitated by an efficient cloud-based architecture. Additionally, the tool incorporates an integrated large language model (LLM), which assists researchers in exploring and interpreting complex biological relationships within the generated networks and multi-omics data using natural language (English). By offering an intuitive, interactive interface, the LLM enhances the exploration of biological insights, making it easier for scientists to derive actionable conclusions. This powerful integration of network analysis, multi-omics data, and LLM provides a robust framework for accelerating the identification of novel drug targets. AVAILABILITY AND IMPLEMENTATION: The tool is publicly available at https://tbep.missouri.edu. The source code, documentation and installation instructions are available at GitHub repository: https://github.com/mizzoudbl/tbep.

Drug Discovery↗

PubMed2006

CRSD: a comprehensive web server for composite regulatory signature discovery.

Transcription factors (TFs) and microRNAs play important roles in the regulation of human gene expression, and the study of their combinatory regulations of gene expression is a new research field. We constructed a comprehensive web server, the composite regulatory signature database (CRSD), that can be applied in investigating complex regulatory behaviors involving gene expression signatures (GESs), microRNA regulatory signatures (MRSs) and TF regulatory signatures (TRSs). Six well-known and large-scale databases, including the human UniGene, mature microRNAs, putative promoter, TRANSFAC, pathway and Gene Ontology (GO) databases, were integrated to provide the comprehensive analysis in CRSD. Two new genome-wide databases, of MRSs and TRSs, were also constructed and further integrated into CRSD. To accomplish the microarray data analysis at one go, several methods, including microarray data pretreatment, statistical and clustering analysis, iterative enrichment analysis and motif discovery, were closely integrated in the web server, which has not been the case in previous studies. Our implementation showed that the published literature could demonstrate the results of genome-wide enrichment analysis. We conclude that CRSD is a powerful and useful bioinformatic web server and may provide new insights into gene regulation networks. CRSD and the online tutorial are publicly available at http://biochip.nchu.edu.tw/crsd1/.

3' Untranslated Regions↗

PubMed1998

Mass spectrometric identification and microcharacterization of proteins from electrophoretic gels: strategies and applications.

The entire genomic DNA sequences of a number of prokaryotic and eukaryotic species are now available and many more, including the human genome, will be completed in the near future. The state-of-life of a cell at any given time, however, is defined by its protein composition, i.e., its proteome. Gel electrophoresis, mass spectrometry, and bioinformatics will be important tools for protein and proteome analysis in the post-genome era. Protein identification from electrophoretic gels by mass spectrometric peptide mapping or peptide sequencing combined with sequence database searching is established and has been applied to numerous biological systems. We describe current strategies and selected applications in molecular and cell biology. The next challenges are detailed structure/function analyses, which include studying the molecular composition of multiprotein complexes and characterization of secondary modifications of proteins. The advantages and limitations of a number of mass spectrometry-based strategies designed for microcharacterization of low amounts of protein from electrophoretic gels are discussed and illustrated by examples.

Amino Acid Sequence↗

PubMed2005

SELDI-TOF-MS: the proteomics and bioinformatics approaches in the diagnosis of breast cancer.

Breast cancer has never had any good serum tumor markers. Therefore, we developed and evaluated a proteomics approach to searching for new biomarkers and building diagnostic models. SELDI-TOF-MS ProteinChip was used to detect the serum protein patterns of 49 breast cancer patients, 51 patients with benign breast diseases, and 33 healthy women. The diagnostic models were developed and validated using bioinformatics tools such as artificial neural networks and discriminant analysis. In total, four models were built and their sensitivities and specificities were satisfactory. The abilities of these models to diagnose stage I breast cancer were not worse than for stages II-IV (P>0.05). Four candidate biomarkers of breast cancer were found. The high sensitivity and specificity achieved by this method show great potential for the early detection of breast cancer and facilitation of discovering new and improved biomarkers.

Adult↗

PubMed2005

Novel biological networks modulated by complement.

The almost complete deciphering of the human genome has paved the way for the application of new technology platforms in understanding the contribution of complex biological pathways to human pathophysiology and disease. In the post-genomic era, the concept of systems biology has gained significant momentum and biomedical research is now being conducted on an integrated and cross-disciplinary platform that pulls together its resources from diverse fields such as computational biology, bioinformatics, functional genomics, structural biology, and proteomics. In this perspective, the identity of established biologic systems is being re-examined in the light of novel findings that suggest novel associations between otherwise unrelated pathways and individual proteins. Complement exemplifies such a system that, transcending its innate immune identity, has forged functional associations with multiple pathways and networks in modulating basic biologic processes. In the present article, we provide a global overview of these unusual system associations of complement with the aid of a powerful and high-throughput bioinformatics platform. Using a novel approach called systems literature analysis that allows the rapid extraction of text-based associations between genes and pathways from the ever expanding scientific article database, we have selected a broad range of biologic processes modulated by complement proteins and have constructed an integrated map of complement-mediated networks that incorporates well over 85 diverse biologic pathways. Expanding the complement cascade beyond its approximately 35 designated components, we discuss protein-protein interactions involving novel ligands and associations with signaling cascades and cellular networks that affect both inflammatory and non-inflammatory processes. This integrated consideration of complement within a unified 'systems biology' framework underscores the concept that innate immunity goes well beyond the protection of 'self' extending links to critical developmental, homeostatic, and metabolic processes.

Complement System Proteins↗

PubMed2003

A microscope-based screening platform for large-scale functional protein analysis in intact cells.

A modular microscope-based screening platform, with applications in large-scale analysis of protein function in intact cells is described. It includes automated sample preparation, image acquisition, data management and analysis, and the genome-wide automated retrieval of bioinformatic information. The modular nature of the system ensures that it is rapidly adaptable to new biological questions or sets of proteins. Two automated functional assays addressing protein secretion and the integrity of the Golgi complex were developed and tested. This shows the potential of the system in large-scale, cell-based functional proteomic projects.

Automation↗

PubMed2006

BiologicalNetworks: visualization and analysis tool for systems biology.

Systems level investigation of genomic scale information requires the development of truly integrated databases dealing with heterogeneous data, which can be queried for simple properties of genes or other database objects as well as for complex network level properties, for the analysis and modelling of complex biological processes. Towards that goal, we recently constructed PathSys, a data integration platform for systems biology, which provides dynamic integration over a diverse set of databases [Baitaluk et al. (2006) BMC Bioinformatics 7, 55]. Here we describe a server, BiologicalNetworks, which provides visualization, analysis services and an information management framework over PathSys. The server allows easy retrieval, construction and visualization of complex biological networks, including genome-scale integrated networks of protein-protein, protein-DNA and genetic interactions. Most importantly, BiologicalNetworks addresses the need for systematic presentation and analysis of high-throughput expression data by mapping and analysis of expression profiles of genes or proteins simultaneously on to regulatory, metabolic and cellular networks. BiologicalNetworks Server is available at http://brak.sdsc.edu/pub/BiologicalNetworks.

Computer Graphics↗

PubMed2004

An update of the HLA genomic region, locus information and disease associations: 2004.

The human major histocompatibility (MHC) genomic region at chromosomal position 6p21 encodes the six classical transplantation HLA genes and many other genes that have important roles in the regulation of the immune system as well as in some fundamental cellular processes. This small segment of the human genome has been associated with more than 100 diseases, including common diseases--such as diabetes, rheumatoid arthritis, psoriasis, asthma and various autoimmune disorders. The MHC 3.6 Mb genomic sequence was first reported in 1999 with the annotation of 224 gene loci. The locus and allelic information of the MHC continue to be updated by identifying newly mapped expressed genes and pseudogenes based on comparative genomics, SNP analysis and cDNA projects. Since 1999, new innovations in bioinformatics and gene-specific functional databases and studies on the MHC genes have resulted in numerous changes to gene names and better ways to update and link the MHC gene symbols, names and sequences together with function, variation and disease associations. In this study, we present a brief overview of the MHC genomic structure and the recent information that we have gathered on the MHC gene loci via LocusLink at the National Centre for Biological Information (http://www.ncbi.nih.gov/.) and the MHC genes' association with various diseases taken from publications and records in public databases, such as the Online Mendelian Inheritance in Man and the Genetic Association Database.

Computational Biology↗

PubMed2025

Differential expression of plasma proteins and pathway enrichments in pediatric diabetic ketoacidosis.

BACKGROUND: In children with type 1 diabetes (T1D), diabetic ketoacidosis (DKA) triggers a significant inflammatory response; however, the specific effector proteins and signaling pathways involved remain largely unexplored. This pediatric case-control study utilized plasma proteomics to explore protein alterations associated with severe DKA and to identify signaling pathways that associate with clinical variables. METHODS: We conducted a proteome analysis of plasma samples from 17 matched pairs of pediatric patients with T1D; one cohort with severe DKA and another with insulin-controlled diabetes. Proximity extension assays were used to quantify 3072 plasma proteins. Data analysis was performed using multivariate statistics, machine learning, and bioinformatics. RESULTS: This study identified 214 differentially expressed proteins (162 upregulated, 52 downregulated; adj P < 0.05 and a fold change > 2), reflecting cellular dysfunction and metabolic stress in severe DKA. We characterized protein expression across various organ systems and cell types, with notable alterations observed in white blood cells. Elevated inflammatory pathways suggest an enhanced inflammatory response, which may contribute to the complications of severe DKA. Additionally, upregulated pathways related to hormone signaling and nitrogen metabolism were identified, consistent with increased hormone release and associated metabolic processes, such as glycogenolysis and lipolysis. Changes in lipid and fatty acid metabolism were also observed, aligning with the lipolysis and ketosis characteristic of severe DKA. Finally, several signaling pathways were associated with clinical biochemical variables. CONCLUSIONS: Our findings highlight differentially expressed plasma proteins and enriched signaling pathways that were associated with clinical features, offering insights into the pathophysiology of severe DKA.

Humans↗

PubMed2001

Analysis of the Arabidopsis mitochondrial proteome.

The complete set of nuclear genes that encode proteins targeted to mitochondria in plants is currently undefined and thus the full range of mitochondrial functions in plants is unknown. Analysis of two-dimensional gel separations of Arabidopsis cell culture mitochondrial protein revealed approximately 100 abundant proteins and 250 low-abundance proteins. Comparison of subfractions of mitochondrial protein on two-dimensional gels provided information on the soluble, membrane, or integral membrane locations of this protein set. A total of 170 protein spots were excised, trypsin-digested, and matrix-assisted laser desorption ionization/time of flight mass spectrometry spectra obtained. Using this dataset, 91 of the proteins were identified by searching translated Arabidopsis genomic databases. Of this set, 81 have defined functions based on sequence comparison. These functions include respiratory electron transport, tricarboxylic acid cycle metabolism, amino acid metabolism, protein import, processing, and assembly, transcription, membrane transport, and antioxidant defense. A total of 10 spectra were matched to Arabidopsis putative open reading frames for which no specific function has been determined. A total of 64 spectra did not match to an identified open reading frame. Analysis of full-length putative protein sequences using bioinformatic tools to predict subcellular targeting (TargetP, Psort, and MitoProt) revealed significant variation in predictions, and also a lack of mitochondrial targeting prediction for several characterized mitochondrial proteins.

Arabidopsis↗

PubMed2004

Prospecting for new group A streptococcal vaccine candidates.

BACKGROUND & OBJECTIVES: Most group A streptococcal (GAS) vaccine strategies focused on the surface M protein of the GAS. However, vaccine based on M protein have some drawbacks. In the present study, we used two approaches to identify new proteins and peptides that may have utility as vaccine candidates. METHODS: A whole gel elution procedure was used to separate GAS surface antigens into 9 size fractionated pools. Mice were vaccinated with each pool and antibody titre, opsonic ability and protective capacity measured. In an alternative approach BioInformatics was used to identify putative GAS surface proteins. Peptides from within these proteins were then selected on the basis of predicted antigenicity or location. These peptides were conjugated to keyhole lymphocyanin (KLH) and immunogenicity measured in a mouse model. RESULTS: One pool of GAS surface proteins (approximately 29kDa) induced antibodies that were both opsonic and potentially protective. Immunoflourescent microscopy demonstrated that these antibodies bound to the surface of M1 GAS. Amino acid sequencing subsequently identified superoxide dismutase as the major antigen in this pool. A BioInformatic search of the M1 GAS genome and subsequent analysis identified several peptides that fulfilled criteria as potential vaccine candidates. Each peptide when conjugated to KLH was able to induce a strong antibody response. INTERPRETATION & CONCLUSION: Several new antigens were identified that may have potential as vaccine targets. A future GAS vaccine may have multiple peptide epitopes, providing protection against multiple GAS strains.

Amino Acid Sequence↗

PubMed2004

[Effects of siwu tang on protein expression of bone marrow of blood deficiency mice induced by irradiation].

OBJECTIVE: To observe the effects of siwu tang on protein expression of bone marrow of blood deficiency mice and provide the theoretical and experimental basis for understanding the molecular mechanism of blood enriching function of siwu tang. METHOD: Blood deficiency mice were established by using 3.5 Gy 60Co gamma-ray. With proteomic technologies including two-dimensional electrophoresis, image analysis, in-gel digestion, peptide mass fingerprinting and bioinformatics the proteins of bone marrow of blood deficiency mice were isolated, analyzed, and identified. RESULT: Siwu tang could reverse 10 up-regulated and 4 down-regulated proteins of blood deficiency mice bone marrow. Seven of the proteins were likely to be lymphocyte specific protein 1, proteasome 26S ATPase subunit 4, hematopoietic cell protein-tyrosine phosphatase, glyceraldehyde-3-phosphate dehydrogenase, growth factor receptor binding protein 14 and lgals12 respectively. CONCLUSION: Siwu tang can regulate the protein expression of bone marrow of blood deficiency mice and thus promote the growth and differentiation of hematopoietic cells and then exert its effects on blood enriching function.

Adaptor Proteins, Signal Transducing↗

PubMed2006

Extracting haplotypes from diploid organisms.

Each diploid organism has two alleles at every gene locus. In sexual organisms such as most plants, animals and fungi, the two alleles in an individual may be genetically very different from each other. DNA sequence data from individual alleles (called a haplotype) can provide powerful information to address a variety of biological questions and guide many practical applications. The advancement in molecular technology and computational tools in the last decade has made obtaining large-scale haplotypes feasible. This review summarizes the two basic approaches for obtaining haplotypes and discusses the associated techniques and methods. The first approach is to experimentally obtain diploid sequence information and then use computer algorithms to infer haplotypes. The second approach is to obtain haplotype sequences directly through experimentation. The advantages and disadvantages of each approach are discussed. I then discussed a specific example on how the direct approach was used to obtain haplotype information to address several fundamental biological questions of a pathogenic yeast. With increasing sophistication in both bioinformatics tools and high-throughput molecular techniques, haplotype analysis is becoming an integrated component in biomedical research.

Animals↗

PubMed2006

Fuzzy Hidden Markov Models: a new approach in multiple sequence alignment.

This paper proposes a novel method for aligning multiple genomic or proteomic sequences using a fuzzyfied Hidden Markov Model (HMM). HMMs are known to provide compelling performance among multiple sequence alignment (MSA) algorithms, yet their stochastic nature does not help them cope with the existing dependence among the sequence elements. Fuzzy HMMs are a novel type of HMMs based on fuzzy sets and fuzzy integrals which generalizes the classical stochastic HMM, by relaxing its independence assumptions. In this paper, the fuzzy HMM model for MSA is mathematically defined. New fuzzy algorithms are described for building and training fuzzy HMMs, as well as for their use in aligning multiple sequences. Fuzzy HMMs can also increase the model capability of aligning multiple sequences mainly in terms of computation time. Modeling the multiple sequence alignment procedure with fuzzy HMMs can yield a robust and time-effective solution that can be widely used in bioinformatics in various applications, such as protein classification, phylogenetic analysis and gene prediction, among others.

Base Sequence↗

PubMed2006

The INFOBIOMED Network of Excellence: facilitating training and mobility in biomedical informatics in Europe.

In this paper we present the work carried out within INFOBIOMED, the European Network of Excellence (NoE) in Biomedical Informatics, to facilitate training and mobility in the area. An analysis of past experiences in both Medical Informatics and Bioinformatics has led to various actions. In this scenario, we have elaborated three actions: (1) a survey of the training and mobility situation, needs and actions to be taken, (2) a Biomedical Informatics course database (ICD), and (3) a Mobility Brokerage Service (MBS). We describe the use of Web Services to build the MBS, designed to facilitate the exchange of professionals within the consortium, belonging to ten European countries. The goal of INFOBIOMED is to expand these initiatives to other NoEs and institutions within the European Union.

Europe↗

PubMed2003

Informatics and multivariate analysis of toxicogenomics data.

The application of genomics methods to toxicology holds great promise. Toxicogenomics data mapping gene expression to predict toxicity and understand mechanisms are emerging, with data suggesting the possibility to classify, and eventually predict, toxic responses. The overall process of informatics analysis of microarray data is summarized. The relationship between the bioinformatics of gene expression and toxicogenomics is discussed, with reference to emerging themes that may be important as the field of toxicogenomics evolves. Emerging themes include the choice and validation of statistical methods, the use of gene annotation and the impact of genome sequence projects.

Animals↗