Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “network analysis”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,279 records · Page 71Linked to original sources
PubMed2000

Geometric analysis of population rhythms in synaptically coupled neuronal networks.

We develop geometric dynamical systems methods to determine how various components contribute to a neuronal network's emergent population behaviors. The results clarify the multiple roles inhibition can play in producing different rhythms. Which rhythms arise depends on how inhibition interacts with intrinsic properties of the neurons; the nature of these interactions depends on the underlying architecture of the network. Our analysis demonstrates that fast inhibitory coupling may lead to synchronized rhythms if either the cells within the network or the architecture of the network is sufficiently complicated. This cannot occur in mutually coupled networks with basic cells; the geometric approach helps explain how additional network complexity allows for synchronized rhythms in the presence of fast inhibitory coupling. The networks and issues considered are motivated by recent models for thalamic oscillations. The analysis helps clarify the roles of various biophysical features, such as fast and slow inhibition, cortical inputs, and ionic conductances, in producing network behavior associated with the spindle sleep rhythm and with paroxysmal discharge rhythms. Transitions between these rhythms are also discussed.

Cerebral Cortex↗
PubMed2005

A coherent framework for multiresolution analysis of biological networks with "memory": Ras pathway, cell cycle, and immune system.

Various biological processes exhibit characteristics that vary dramatically in response to different input conditions or changes in the history of the process itself. One of the examples studied here, the Ras-PKC-mitogen-activated protein kinase (MAPK) bistable pathway, follows two distinct dynamics (modes) depending on duration and strength of EGF stimulus. Similar examples are found in the behavior of the cell cycle and the immune system. A classification methodology, based on time-frequency analysis, was developed and tested on these systems to understand global behavior of biological processes. Contrary to most traditionally used statistical and spectral methods, our approach captures complex functional relations between parts of the systems in a simple way. The resulting algorithms are capable of analyzing and classifying sets of time-series data obtained from in vivo or in vitro experiments, or in silico simulation of biological processes. The method was found to be considerably stable under stochastic noise perturbation and, therefore, suitable for the analysis of real experimental data.

Algorithms↗
PubMed2006

Utility of nuclear allele networks for the analysis of closely related species in the genus Carabus, subgenus Ohomopterus.

Nuclear DNA sequence data for diploid organisms are potentially a rich source of phylogenetic information for disentangling the evolutionary relationships of closely related organisms, but present special phylogenetic problems owing to difficulties arising from heterozygosity and recombination. We analyzed allelic relationships for two nuclear gene regions (phosphoenolpyruvate carboxykinase and elongation factor-1a), along with a mitochondrial gene region (NADH dehydrogenase subunit 5), for an assemblage of closely related species of carabid beetles (Carabus subgenus Ohomopterus). We used a network approach to examine whether the nuclear gene sequences provide substantial phylogenetic information on species relationships and evolutionary history. The mitochondrial gene genealogy strongly contradicted the morphological species boundary as a result of introgression of heterospecific mitochondria. Two nuclear gene regions showed high allelic diversity within species, and this diversity was partially attributable to recombination between various alleles and high variability in the intron region. Shared nuclear alleles among species were rare and were considered to represent shared ancestral polymorphism. Despite the presence of recombination, nuclear allelic networks recovered species monophyly more often and presented genetic differentiation patterns (low to high) among species more clearly. Overall, nuclear gene networks provide clear evidence for separate biological species and information on the phylogenetic relationships among closely related carabid beetles.

Alleles↗
PubMed1992

Analysis of United Network for Organ Sharing (UNOS) United States of America (USA) Pancreas Transplant Registry data according to multiple variables.

As of 1992, more than 4,200 pancreas transplants were reported to the International Pancreas Transplant Registry. Of these, more than 2,600 were performed in the United States, and of these, more than 2,100 have been transplanted since the inception of the UNOS Registry in October 1987. The analyses here are only of the UNOS data. Pancreas transplants performed in conjunction with a liver (either cluster or noncluster) or a heart were excluded from the analysis, and only those performed as a solitary procedure or in conjunction with a kidney were included. Emphasis was placed on those performed with the bladder drainage (BD) technique (96%). In the overall analysis of BD cadaveric pancreas transplants (n = 1,879), 1-year patient survival and pancreas graft function survival rates were 91% and 71%, respectively, 87% and 66% at 2 years, and 81% and 59% at 3 years. There were no differences according to gender, but 1-year graft survival rates were significantly higher in recipients 45 years or younger (72%) (n = 1,679) than in those older than 45 (64%) (n = 200). There were no significant differences according to graft preservation times of less than 12 (n = 749), 12-24 (n = 940), 24-30 (n = 79), and more than 30 (n = 9) hours, function rates at 1 year being 71%, 72%, 72%, and 44%, respectively. When analyzed according to the 3 major recipient categories (simultaneous pancreas/kidney transplants [SPK] [n = 1604]; pancreas after kidney transplants [PAK] [n = 166]; and pancreas transplants alone [PTA] [n = 109]), patient survival rates were no different (91%, 92%, and 92% at 1 year, respectively), but pancreas graft survival rates were significantly higher in the SPK than in the PAK and PTA categories (75%, 48%, and 49%, at 1 year, respectively). In the SPK group, kidney graft survival rates at 1 year were 84%. Outcomes were also compared according to whether induction immunotherapy included ALG, OKT3, or neither. In the SPK category, there was no difference among the protocols, with 1-year graft survival rates being 76% in the ALG (n = 838), 76% in the OKT3 (n = 416), and 72% in the Neither (n = 299) group.(ABSTRACT TRUNCATED AT 400 WORDS)

Adult↗
PubMed2001

Synthesis and structure-activity relationships of a new model of arylpiperazines. Study of the 5-HT(1a)/alpha(1)-adrenergic receptor affinity by classical hansch analysis, artificial neural networks, and computational simulation of ligand recognition.

A classical quantitative structure-activity relationship (Hansch) study and artificial neural networks (ANNs) have been applied to a training set of 32 substituted phenylpiperazines with affinity for 5-HT(1A) and alpha(1)-adrenergic receptors, to evaluate the structural requirements that are responsible for 5-HT(1A)/alpha(1) selectivity. The resulting models provide a significant correlation of electronic, steric, and hydrophobic parameters with the biological affinities. Although the derived linear Hansch correlations give good statistics and acceptable predictions, the introduction of nonlinear relationships in the analysis gives more solid models and more accurate predictions. In the ANN models on the basis of the obtained 3D plots, the 5-HT(1A) affinity has a nonlinear dependence on F, V(o), V(m), and pi(o), although the nonlinear relationship is not far from a planar one. The alpha(1)-adrenergic receptor affinity has a clear nonlinear dependence on F, V(o), V(m), pi(o), and pi(m). A comparison of both analyses gives an additional understanding for 5-HT(1A)/alpha(1) selectivity: (a) high F values increase the binding affinity for 5-HT(1A) receptors and decrease the affinity for alpha(1) sites; (b) the hydrophobicity at the meta-position has only influence for the alpha(1)-adrenergic receptor; (c) the meta-position seems to be implicated in the 5-HT(1A)/alpha(1) selectivity. While the 5-HT(1A) receptor is able to accommodate bulky substituents in the region of its active site, the steric requirements of the alpha(1)-adrenergic receptor at this position are more restricted. This information was used for the design of the new ligand EF-7412 (33) (5-HT(1A): K(i exptl) = 27 nM, alpha(1): K(i exptl) > 1000 nM; 5-HT(1A): K(i pred) (ANN) = 36 nM, alpha(1): K(i pred ANN) = 2745 nM) which was characterized as an antagonist in vivo in pre- and postsynaptic 5-HT(1A)R sites. Computational simulations of the complex between EF-7412 (33) and a 3D model of the transmembrane domain of the 5-HT(1A) receptor allowed us to define the molecular details of the ligand-receptor interaction that includes: (i) the ionic interaction between the protonated amine of the ligand and Asp 3.32; (ii) the hydrogen bonds between the m-NHSO(2)Et group of the ligand and Asn 7.39; and the hydrogen bonds between the hydantoin moiety of the ligand and (iii) Thr 3.37, (iv) Ser 5.42, and (v) Thr 5.43. These QSAR and ANN results in combination with computational simulations of ligand recognition will be useful for the design of potent selective 5-HT(1A) ligands.

Animals↗
PubMed1987

Analysis of microvascular network in bulbar conjunctiva by image processing.

A digital image processing procedure has been developed for obtaining quantitative morphometric data on the microcirculatory network in the human bulbar conjunctiva. Highlights of this semi-automated approach include: 1. extraction of morphometric information that cannot be readily obtained by manual methods--length, diameter, and diffusion distributions; 2. speed and consistency in data generation--only 10 minutes are required to scan and to analyze 6.7 mm2 of conjunctiva microvasculature. The variation was less than 5% when images of the same area in the same eye were subjected to analysis at different times; 3. avoid the human bias factor--the data obtained by repeated analysis of the same negative varied by less than 0.02%.

Conjunctiva↗
PubMed2002

Application of a Kohonen neural network to the analysis of data regarding the alkylation of toluene with methanol catalyzed by ZSM-5 type zeolites.

para-Xylene is widely used in chemical industry. It can be synthesized by alkylation of toluene with methanol using zeolite ZSM-5 as catalyst. The proportion of para-xylene, among its other isomers and other reaction byproducts, depends on the reaction conditions. As this process still remains largely empirical, we attempted to build a theoretical model able to predict the para-xylene yield under specific reaction conditions. We have consequently collected data regarding this reaction from the literature and exploited the potency of a particular artificial neural network (ANN), the counter-propagation ANN based on the Kohonen technique. The results show that such an approach is suitable to establish a predictive model of the yield in para-xylene on the basis of reaction parameters. The quality of the model could be further improved by considering a larger valuable data set, e.g. including experiments characterized by a low yield in para-xylene.

Journal Article↗
PubMed1988

Control analysis of metabolic networks. 1. Homogeneous functions and the summation theorems for control coefficients.

1. The summation theorem CJ1 + ... + CJn = 1 for flux control coefficients CJi is shown to be equivalent to the assumption that flux J is a homogeneous function of degree 1 of enzyme concentrations E1,..., En, that is to the assumption J (tE1,..., tEn) = tJ (E1,..., En) for any t not equal to 0. Likewise, the summation theorem CXj1 + ... + CXjn = 0 for concentration control coefficients CXj1 is equivalent to homogeneity of degree 0 of steady-state metabolite concentrations Xj, or Xj (tE1,..., tEn) = Xj (E1,..., En). From this equivalence it is obvious that metabolic control analysis applies only to homogeneous systems. 2. The summation theorem for flux control coefficients is shown to be equivalent to that for concentration control coefficients, provided all reaction rates vi are homogeneous functions of enzyme concentrations Ei. 3. The equivalence between homogeneity of flux J and the summation theorem for flux control coefficients is used to analyse branching of fluxes in metabolic pathways in terms of flux control coefficients.

Enzymes↗
PubMed2025

Mechanism of action of curculigoside ameliorating osteoporosis: an analysis based on network pharmacology and experimental validation.

OBJECTIVE: This study aimed to predict and verify the mechanism of curculigoside in treating osteoporosis using network pharmacology, molecular docking technology, and micro-CT technology. METHODS: Herb databases were searched to identify and screen potential targets of curculigoside. The GeneCards platform was utilized to mine osteoporosis-related targets. Cytoscape 3.6.0 software was employed to construct a compound-target-disease network. A protein-protein interaction (PPI) network for curculigoside in osteoporosis treatment was established, and core targets were screened. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and GO biological process analyses were performed using the Metascape database. Finally, molecular docking and micro-CT were used to validate core targets relevant to osteoporosis. RESULTS: A total of 166 potential curculigoside targets and 4,313 osteoporosis-related targets were identified, with 91 common targets. Ten key targets, including matrix metalloproteinase (MMP)3, MMP9, interleukin (IL)-6, and caspase-3, were screened. KEGG pathway enrichment analysis indicated involvement in 10 pathways, such as the Rap1 signaling pathway and tumor necrosis factor (TNF) signaling pathway. Molecular docking results demonstrated strong binding affinity between curculigoside and the core targets. Micro-CT analysis revealed that curculigoside not only improved BMD, BV/TV, BS/BV, and Tb.Th but also reduced Tb.Sp in osteoporotic bone. CONCLUSIONS: Curculigoside is likely to treat osteoporosis through targets such as MMP3, MMP9, IL-6, and caspase-3, acting on signaling pathways including Rap1 and TNF. These results indicate that curculigoside exhibits multitarget and multipathway characteristics in osteoporosis treatment, providing a theoretical basis for further clinical investigation.

Osteoporosis↗
PubMedDate not supplied

Quantitative analysis of dendritic networks of Purkinje neurons during aging.

This study examined quantitative parameters of Golgi-Cox stained Purkinje dendritic networks in Fischer 344 rats of three different ages. Topological patterns of branching, metric parameters of the networks, and spine densities on terminal dendritic branches of the networks were measured and analyzed relative to age of the animals. The data suggested that the networks were topologically stable at all ages, but decreases in spine density on terminal branches, in length per terminal branch, in total length of terminal branches, and in total length of the entire network were shown. Decreases in spine density were found in cells of both older groups of rats; however, decreases in length parameters were significant only in the cells of rats in the intermediate age group.

Aging↗
PubMed2026

In silico analysis based on network pharmacology and biomolecular informatics to explore the mechanism of action of Erjing Pills (from Shengji Zonglu) in the treatment of leukotrichia.

This study aimed to explore the core active ingredients and potential molecular mechanisms of Erjing Pills, a prescription in the classic work of Traditional Chinese Medicine, "Shengji Zonglu," in the treatment of leukotrichia by utilizing network pharmacology and biomolecular docking techniques. The chemical components and potential targets of Chinese herbal medicines were analyzed through databases such as the Traditional Chinese Medicine Systems Pharmacology Database. The targets related to leukotrichia were collected using GeneCards. The intersection targets were obtained using RStudio. The protein-protein interaction (PPI) network map and the "drug-component-target-disease" visualization network were generated using Cytoscape and STRING to screen the core components and key targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were carried out using the Database for Annotation, Visualization and Integrated Discovery and RStudio. Finally, molecular docking verification was performed by AutoDock and PyMOL (Schrödinger LLC). The key active ingredients of Erjing Pills in the treatment of leukotrichia are β-sitosterol, quercetin, baicalein, and stigmasterol. The top 5 PPI core target proteins, in order, are AKT serine/threonine kinase 1, interleukin 6, tumor protein p53, cysteine-aspartic acid protease 3, and interleukin 1 beta. The Gene Ontology enrichment analysis suggests that the biological processes mainly include responses to exogenous stimuli, membrane rafts, and DNA-binding transcription factor binding. The Kyoto Encyclopedia of Genes and Genomes pathways involve signal pathways such as lipid and atherosclerosis, hepatitis B, Kaposi sarcoma virus infection, chemical carcinogenesis, and human cytomegalovirus infection. The molecular docking results indicate that most of the main active ingredients in Erjing Pills have relatively stable binding activities with the key targets, such as AKT serine/threonine kinase 1, interleukin 6, tumor protein p53, cysteine-aspartic acid protease 3, and interleukin 1 beta, in the PPI network. The active ingredients of Erjing Pills may interfere with the pathological process of leukotrichia by regulating key targets and signal pathways. This study provides a theoretical basis for the clinical application of Erjing Pills and indicates the direction for subsequent experimental research.

Drugs, Chinese Herbal↗
PubMed1984

The analysis of coupling networks in a complex oligosaccharide mixture derived from the Fc region of rabbit immunoglobulin G using 1H-1H correlated NMR spectroscopy combined with double quantum NMR spectroscopy.

In glycoproteins, even for those containing a single glycosylation site, diversity is manifest in the occurrence of a family of structurally-related yet distinct oligosaccharides. To date this 'microheterogeneity' is universal in mammalian glycoproteins. A method is described, using 1H-1H correlated and double quantum nuclear magnetic resonance NMR spectroscopy, for the assignment of proton resonances within a mixture of complex-type oligosaccharides derived from the Fc region of rabbit immunoglobulin G. The ability to assign resonances in heterogeneous populations will be of importance in the chemical shift analysis of the 1H-NMR spectra of glycopeptides since these cannot generally be separated on the basis of their carbohydrate sequence. The resulting assignments will be necessary before conformational studies on glycopeptides using nuclear Overhauser effects can be made.

Animals↗
PubMedDate not supplied

Chaperone networks in bacteria: analysis of protein homeostasis in minimal cells.

The prevention of aberrant behavior of proteins is fundamental to cellular life. Protein homeostatic processes are present in cells to stabilize protein conformations, refold misfolded proteins, and degrade proteins that might be detrimental to the cell. Molecular chaperones and proteases perform a major role in these processes. In bacteria, the main cytoplasmic components involved in protein homeostasis include the chaperones trigger factor, DnaK/DnaJ/GrpE, GroEL/GroES, HtpG, as well as ClpB and the proteases ClpXP, ClpAP, HslUV, Lon, and FtsH. Based on recent genome sequencing efforts, it was surprising to find that the Mycoplasma, a genus proposed to include a minimal form of cellular life, do not contain certain major members of the protein homeostatic network, including GroEL/GroES. We propose that, in mycoplasmas, there has been a fundamental shift towards favoring processes that promote protein degradation rather than protein folding. The arguments are based on two different premises: (1) the regulation of stress response in Mycoplasma and (2) the unique characteristics of the Mycoplasma proteome.

Bacterial Proteins↗
PubMed2004

Gene expression analysis on biochemical networks using the Potts spin model.

MOTIVATION: Microarray technology allows us to profile the expression of a large subset or all genes of a cell. Biochemical research over the last three decades has elucidated an increasingly complete image of the metabolic architecture. For less complex organisms, such as Escherichia coli, the biochemical network has been described in much detail. Here, we investigate the clustering of such networks by applying gene expression data that define edge lengths in the network. RESULTS: The Potts spin model is used as a nearest neighbour based clustering algorithm to discover fragmentation of the network in mutants or in biological samples when treated with drugs. As an example, we tested our method with gene expression data from E.coli treated with tryptophan excess, starvation and trpyptophan repressor mutants. We observed fragmentation of the tryptophan biosynthesis pathway, which corresponds well to the commonly known regulatory response of the cells.

Algorithms↗
PubMed2003

Analysis of metabolic networks using a pathway distance metric through linear programming.

The solution of the shortest path problem in biochemical systems constitutes an important step for studies of their evolution. In this paper, a linear programming (LP) algorithm for calculating minimal pathway distances in metabolic networks is studied. Minimal pathway distances are identified as the smallest number of metabolic steps separating two enzymes in metabolic pathways. The algorithm deals effectively with circularity and reaction directionality. The applicability of the algorithm is illustrated by calculating the minimal pathway distances for Escherichia coli small molecule metabolism enzymes, and then considering their correlations with genome distance (distance separating two genes on a chromosome) and enzyme function (as characterised by enzyme commission number). The results illustrate the effectiveness of the LP model. In addition, the data confirm that propinquity of genes on the genome implies similarity in function (as determined by co-involvement in the same region of the metabolic network), but suggest that no correlation exists between pathway distance and enzyme function. These findings offer insight into the probable mechanism of pathway evolution.

Algorithms↗
PubMed2005

Genetical genomics analysis of a yeast segregant population for transcription network inference.

Genetic analysis of gene expression in a segregating population, which is expression profiled and genotyped at DNA markers throughout the genome, can reveal regulatory networks of polymorphic genes. We propose an analysis strategy with several steps: (1) genome-wide QTL analysis of all expression profiles to identify eQTL confidence regions, followed by fine mapping of identified eQTL; (2) identification of regulatory candidate genes in each eQTL region; (3) correlation analysis of the expression profiles of the candidates in any eQTL region with the gene affected by the eQTL to reduce the number of candidates; (4) drawing directional links from retained regulatory candidate genes to genes affected by the eQTL and joining links to form networks; and (5) statistical validation and refinement of the inferred network structure. Here, we apply an initial implementation of this strategy to a segregating yeast population. In 65, 7, and 28% of the identified eQTL regions, a single candidate regulatory gene, no gene, or more than one gene was retained in step 3, respectively. Overall, 768 putative regulatory links were retained, 331 of which are the strongest candidate links, as they were retained in the expression correlation analysis and were located within or near an eQTL subregion identified by a multimarker analysis separating multiple linked QTL. One or several biological processes were statistically significantly overrepresented in independent network structures or in highly interconnected subnetworks. Most of the transcription factors found in the inferred network had a putative regulatory link to only one other gene or exhibited cis-regulation.

DNA↗
PubMed2000

A digital image analysis and neural network based system for identification of third-stage parasitic strongyle larvae from domestic animals.

A competitive learning vector quantization artificial neural network (ANN) was trained to identify third-stage parasitic strongyle larvae from domestic animals on the basis of quantitative data obtained from processed digital images of larvae. For this reason, various quantitative features obtained from processed digital images of larvae were tested as to whether they are variant or invariant to the shape taken by the motile larvae during image recording. A total of 255 images of 57 individual larvae in various shapes belonging to five genera were recorded. Following image processing, 16 features were measured, of which seven were selected as invariant to larva shape. By trial and error, two of those features, 'area' and 'perimeter', along with the quantitative features used in conventional identification, 'overall body length', 'width' and 'extension of sheath' (tip of larva to tip of sheath), were used as an effective training data set for the ANN. This ANN coupled with an image analysis facility and a knowledge relational database became the basis for developing a computer-based larva identification system whose overall identification performance was 91.9%. The advantages of this system are its speed and objectivity. The objectivity of the system is based on the fact that it is not subject to inter- and intra-observer variability arising from the user's profile of competency in interpreting subjective and non-quantifiable descriptions. The limitations of the system are that it cannot handle raw images but only data extracted from images, its performance depends on the reliability of the input vectors used as training data for the ANN, and its use is restricted only to well-equipped laboratories due to its requirement for expensive instrumentation.

Animals↗
PubMed2004

Quantitative analysis of signaling networks.

The response of biological cells to environmental change is coordinated by protein-based signaling networks. These networks are to be found in both prokaryotes and eukaryotes. In eukaryotes, the signaling networks can be highly complex, some networks comprising of 60 or more proteins. The fundamental motif that has been found in all signaling networks is the protein phosphorylation/dephosphorylation cycle--the cascade cycle. At this time, the computational function of many of the signaling networks is poorly understood. However, it is clear that it is possible to construct a huge variety of control and computational circuits, both analog and digital from combinations of the cascade cycle. In this review, we will summarize the great versatility of the simple cascade cycle as a computational unit and towards the end give two examples, one prokaryotic chemotaxis circuit and the other, the eukaryotic MAPK cascade.

Animals↗