scholarly journals An entropic characterization of protein interaction networks and cellular robustness

2006 ◽  
Vol 3 (11) ◽  
pp. 843-850 ◽  
Author(s):  
Thomas Manke ◽  
Lloyd Demetrius ◽  
Martin Vingron
Keyword(s):  
Protein Interaction ◽  
Large Scale ◽  
Global Network ◽  
Molecular Networks ◽  
Local Network ◽  
Large Contribution ◽  
Fundamental Relation ◽  
Cellular Behaviour ◽  
Network Entropy

The structure of molecular networks is believed to determine important aspects of their cellular function, such as the organismal resilience against random perturbations. Ultimately, however, cellular behaviour is determined by the dynamical processes, which are constrained by network topology. The present work is based on a fundamental relation from dynamical systems theory, which states that the macroscopic resilience of a steady state is correlated with the uncertainty in the underlying microscopic processes, a property that can be measured by entropy. Here, we use recent network data from large-scale protein interaction screens to characterize the diversity of possible pathways in terms of network entropy. This measure has its origin in statistical mechanics and amounts to a global characterization of both structural and dynamical resilience in terms of microscopic elements. We demonstrate how this approach can be used to rank network elements according to their contribution to network entropy and also investigate how this suggested ranking reflects on the functional data provided by gene knockouts and RNAi experiments in yeast and Caenorhabditis elegans . Our analysis shows that knockouts of proteins with large contribution to network entropy are preferentially lethal. This observation is robust with respect to several possible errors and biases in the experimental data. It underscores the significance of entropy as a fundamental invariant of the dynamical system, and as a measure of structural and dynamical properties of networks. Our analytical approach goes beyond the phenomenological studies of cellular robustness based on local network observables, such as connectivity. One of its principal achievements is to provide a rationale to study proxies of cellular resilience and rank proteins according to their importance within the global network context.

scholarly journals Network-based characterization of disease–disease relationships in terms of drugs and therapeutic targets

2020 ◽  
Vol 36 (Supplement_1) ◽  
pp. i516-i524
Author(s):  
Midori Iida ◽  
Michio Iwata ◽  
Yoshihiro Yamanishi
Keyword(s):  
Large Scale ◽  
Expression Patterns ◽  
Therapeutic Targets ◽  
Molecular Networks ◽  
Supplementary Information ◽  
New Associations ◽  
Disease States ◽  
Molecular Features ◽  
Novel Approach

Abstract Motivation Disease states are distinguished from each other in terms of differing clinical phenotypes, but characteristic molecular features are often common to various diseases. Similarities between diseases can be explained by characteristic gene expression patterns. However, most disease–disease relationships remain uncharacterized. Results In this study, we proposed a novel approach for network-based characterization of disease–disease relationships in terms of drugs and therapeutic targets. We performed large-scale analyses of omics data and molecular interaction networks for 79 diseases, including adrenoleukodystrophy, leukaemia, Alzheimer's disease, asthma, atopic dermatitis, breast cancer, cystic fibrosis and inflammatory bowel disease. We quantified disease–disease similarities based on proximities of abnormally expressed genes in various molecular networks, and showed that similarities between diseases could be explained by characteristic molecular network topologies. Furthermore, we developed a kernel matrix regression algorithm to predict the commonalities of drugs and therapeutic targets among diseases. Our comprehensive prediction strategy indicated many new associations among phenotypically diverse diseases. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Noncoding-RNA-Mediated Regulation in Response to Macronutrient Stress in Plants

2021 ◽  
Vol 22 (20) ◽  
pp. 11205
Author(s):  
Ziwei Li ◽  
Peng Tian ◽  
Tengbo Huang ◽  
Jianzi Huang
Keyword(s):  
Noncoding Rna ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Theoretical Study ◽  
Functional Characterization ◽  
Molecular Networks ◽  
Plant Responses ◽  
Crop Breeding ◽  
Target Module

Macronutrient elements including nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), and sulfur (S) are required in relatively large and steady amounts for plant growth and development. Deficient or excessive supply of macronutrients from external environments may trigger a series of plant responses at phenotypic and molecular levels during the entire life cycle. Among the intertwined molecular networks underlying plant responses to macronutrient stress, noncoding RNAs (ncRNAs), mainly microRNAs (miRNAs) and long ncRNAs (lncRNAs), may serve as pivotal regulators for the coordination between nutrient supply and plant demand, while the responsive ncRNA-target module and the interactive mechanism vary among elements and species. Towards a comprehensive identification and functional characterization of nutrient-responsive ncRNAs and their downstream molecules, high-throughput sequencing has produced massive omics data for comparative expression profiling as a first step. In this review, we highlight the recent findings of ncRNA-mediated regulation in response to macronutrient stress, with special emphasis on the large-scale sequencing efforts for screening out candidate nutrient-responsive ncRNAs in plants, and discuss potential improvements in theoretical study to provide better guidance for crop breeding practices.

scholarly journals An accurate and robust algorithm for solvent-excluded surface computation

2018 ◽  
Author(s):  
Lincong Wang
Keyword(s):  
Protein Interaction ◽  
Large Scale ◽  
Geometrical Property ◽  
Membrane Lipid ◽  
Solvent Interaction ◽  
Geometrical Properties ◽  
Different Types ◽  
Small Molecule Compound ◽  
Numerical Precision

AbstractThe solvent-excluded surface (SES1) of a molecule is an important geometrical property relevant to its solvation in aqueous solution and its interactions with other molecules. In this paper we present an accurate and robust analytic algorithm suitable for a large-scale SES analysis. The accuracy and robustness of our algorithm are made possible by an iterative strategy for the treatments of probe-probe intersections, probe-probe overlaps and limited numerical precision. The accuracy and robustness of our algorithm in turn make it possible to analyze on a large-scale the SESs for different types of proteins and various sets of ligand-protein interaction interfaces. The results illustrate the usefulness of SES and SES-defined physical and geometrical properties for the characterization of protein-solvent interaction and ligand-protein interaction where ligand could be either small molecule compound, or membrane lipid, or DNA or protein.

scholarly journals AutoAnalyze in Systems Biology

2019 ◽  
Vol 13 ◽  
pp. 117793221881845
Author(s):  
Christian Saad ◽  
Bernhard Bauer ◽  
Ulrich R Mansmann ◽  
Jian Li
Keyword(s):  
Large Scale ◽  
Genetic Data ◽  
Global Network ◽  
Molecular Networks ◽  
Scale Model ◽  
Efficient Computation ◽  
Efficient Treatment ◽  
Large Scale Model ◽  
Reaction Equations

AutoAnalyze is a highly customizable framework for the visualization and analysis of large-scale model graphs. Originally developed for use in the automotive domain, it also supports efficient computation within molecular networks represented by reaction equations. A static analysis approach is used for efficient treatment-condition-specific simulation. The chosen method relies on the computation of a global network data-flow resulting from the evaluation of individual genetic data. The approach facilitates complex analyses of biological components from a molecular network under specific therapeutic perturbations, as demonstrated in a case study. In addition to simulating the complex networks in a stable and reproducible way, kinetic constants can also be fine-tuned using a genetic algorithm and built-in statistical tools.

Some applications of electron beam microanalysis techniques in VLSI process evaluation

1983 ◽  
Vol 41 ◽  
pp. 160-161
Author(s):  
Simon Thomas
Keyword(s):  
Integrated Circuits ◽  
Process Evaluation ◽  
Large Scale ◽  
Technology Development ◽  
Analytical Techniques ◽  
Successful Implementation ◽  
Analysis Of Failures ◽  
Characterization Of Materials ◽  
Circuits Vlsi

Trends in the technology development of very large scale integrated circuits (VLSI) have been in the direction of higher density of components with smaller dimensions. The scaling down of device dimensions has been not only laterally but also in depth. Such efforts in miniaturization bring with them new developments in materials and processing. Successful implementation of these efforts is, to a large extent, dependent on the proper understanding of the material properties, process technologies and reliability issues, through adequate analytical studies. The analytical instrumentation technology has, fortunately, kept pace with the basic requirements of devices with lateral dimensions in the micron/ submicron range and depths of the order of nonometers. Often, newer analytical techniques have emerged or the more conventional techniques have been adapted to meet the more stringent requirements. As such, a variety of analytical techniques are available today to aid an analyst in the efforts of VLSI process evaluation. Generally such analytical efforts are divided into the characterization of materials, evaluation of processing steps and the analysis of failures.

Characterization of seawater reverse osmosis fouled membranes from large scale commercial desalination plant

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Reverse Osmosis ◽  
Large Scale ◽  
Retention Rate ◽  
Local Level ◽  
Microscopic Analysis ◽  
Transmembrane Pressure ◽  
Hydraulic Permeability ◽  
Seawater Reverse Osmosis ◽  
A Chain

The objective of this work is to study the ageing state of a used reverse osmosis (RO) membrane taken in Algeria from the Benisaf Water Company seawater desalination unit. The study consists of an autopsy procedure used to perform a chain of analyses on a membrane sheet. Wear of the membrane is characterized by a degradation of its performance due to a significant increase in hydraulic permeability (25%) and pressure drop as well as a decrease in salt retention (10% to 30%). In most cases the effects of ageing are little or poorly known at the local level and global measurements such as (flux, transmembrane pressure, permeate flow, retention rate, etc.) do not allow characterization. Therefore, a used RO (reverse osmosis) membrane was selected at the site to perform the membrane autopsy tests. These tests make it possible to analyze and identify the cause as well as to understand the links between performance degradation observed at the macroscopic scale and at the scale at which ageing takes place. External and internal visual observations allow seeing the state of degradation. Microscopic analysis of the used membranes surface shows the importance of fouling. In addition, quantification and identification analyses determine a high fouling rate in the used membrane whose foulants is of inorganic and organic nature. Moreover, the analyses proved the presence of a biofilm composed of protein.

Characterization of Interconnect Defects Using Scanning Thermal Conductivity Microscopy

2004 ◽  
Author(s):  
H.W. Ho ◽  
J.C.H. Phang ◽  
A. Altes ◽  
L.J. Balk
Keyword(s):  
Thermal Conductivity ◽  
Integrated Circuits ◽  
Large Scale

Abstract In this paper, scanning thermal conductivity microscopy is used to characterize interconnect defects due to electromigration. Similar features are observed both in the temperature and thermal conductivity micrographs. The key advantage of the thermal conductivity mode is that specimen bias is not required. This is an important advantage for the characterization of defects in large scale integrated circuits. The thermal conductivity micrographs of extrusion, exposed and subsurface voids are presented and compared with the corresponding topography and temperature micrographs.

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